- Michael J. Vinarcik is the Director (Digital Architecture and Requirements Engineering) in SAIC's Engineering Innovat... moreMichael J. Vinarcik is the Director (Digital Architecture and Requirements Engineering) in SAIC's Engineering Innovation Factory, an adjunct professor at the University of Detroit Mercy, and a visiting professor at CIDESI (Mexico City). He has thirty years of automotive and defense engineering experience. He received a BS (Metallurgical Engineering) from the Ohio State University, an MBA from the University of Michigan, and an MS (Product Development) from the University of Detroit Mercy.
Michael has presented at NDIA Ground Vehicle Systems Engineering and Technology Symposia, INCOSE and American Society for Engineering Education regional conferences, and a tutorial at the 2010 INCOSE International Symposium. He contributed chapters to Industrial Applications of X-ray Diffraction, Taguchi’s Quality Engineering Handbook, and Case Studies in System of Systems, Enterprise Systems, and Complex Systems Engineering; he also contributed a case study to the Systems Engineering Body of Knowledge (SEBoK).
Michael is a licensed Professional Engineer (Michigan) and holds INCOSE ESEP-Acq, OCSMP: Model Builder – Advanced, Booz Allen Hamilton Systems Engineering Expert Belt, ASQ Certified Quality Engineer, and ASQ Certified Reliability Engineer certifications. He is a Fellow of the Engineering Society of Detroit, chaired the 2010-2011 INCOSE Great Lakes Regional Conferences, and was the 2012 President of the INCOSE Michigan Chapter. He co-led INCOSE’s Model Based Conceptual Design Working Group and is the current INCOSE Treasurer and the President and Founder of Sigma Theta Mu, the systems honor society.edit
The Department of Defense's Digital Engineering Strategy (adopted in June 2018) has five goals: 1. Formalize the development, integration, and use of models to inform enterprise and program decision making 2. Provide an enduring,... more
The Department of Defense's Digital Engineering Strategy (adopted in June 2018) has five goals: 1. Formalize the development, integration, and use of models to inform enterprise and program decision making 2. Provide an enduring, authoritative source of truth 3. Incorporate technological innovation to improve the engineering practice 4. Establish a supporting infrastructure and environment to perform activities, collaborate, and communicate across stakeholders 5. Transform the culture and workforce to adopt and support digital engineering across the life cycle. 1 For this strategy to succeed, stakeholders must willingly participate in the cultural transformation and use system models as they are intended: as living, dynamic, integrated sources of information that communicate intent with rigor and clarity. Moving from disjointed documents and air-gapped information sources to a single source of truth is important. However, the explosive growth in system complexity is causing a new, unwanted emergent behavior: In an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it. 2 Because stakeholders are becoming overwhelmed with information from multiple sources, effective system modeling cannot solely focus on the creation of competently executed, integrated system models. It must also facilitate the creation of visualizations and derived products that allow stakeholders to efficiently identify and consume relevant information.
Research Interests:
Effective instruction in system modeling requires an emphasis on hands-on exercises. This paper presents lessons learned from coordinating and grading eight collaborative and integrated SysML models; in addition, it includes extracts from... more
Effective instruction in system modeling requires an emphasis on hands-on exercises. This paper presents lessons learned from coordinating and grading eight collaborative and integrated SysML models; in addition, it includes extracts from team projects and metrics related to model size and style conformance.
Research Interests:
The creation of descriptive models using SysML is a skill-focused discipline; the outcomes of a modeling effort depend upon the abilities of the modelers contributing to it. Ongoing shortages of skilled modelers are inhibiting the... more
The creation of descriptive models using SysML is a skill-focused discipline; the outcomes of a modeling effort depend upon the abilities of the modelers contributing to it. Ongoing shortages of skilled modelers are inhibiting the transition of systems engineering to a model-based discipline.
This paper illustrates the use of validation rules to support instruction (both stand-alone modeling exercises and a larger, collaborative modeling project). Validation rules have proven to be effective in reducing modeler errors when added incrementally in parallel with concepts introduced in class. The rules simplify grading (since the instructor can focus on value-added content instead of semantic correctness). In addition, the rules conform to the Seven Keys to Effective Feedback proposed by Grant Wiggins:
1. Goal-Referenced (Error reduction/style conformance)
2. Tangible and Transparent (Rules clearly explain what is wrong)
3. Actionable (Error messages direct the modeler how to fix the issue)
4. User-Friendly (Private feedback that marks elements with to simplify repair)
5. Timely (On demand and rapid feedback eliminates errors before they accumulate)
6. Ongoing (Available throughout the course of any modeling project)
7. Consistent (All students receive the same feedback).
The rules were continuously updated throughout the term in which they were introduced; students corrected new errors and improved their model quality as they executed their term projects. Extracts from six team projects will be presented and contrasted with selected past projects (subjected to the same validation rules) to demonstrate the efficacy of the approach. Several models published by notable SysML modelers will also be analyzed.
This paper illustrates the use of validation rules to support instruction (both stand-alone modeling exercises and a larger, collaborative modeling project). Validation rules have proven to be effective in reducing modeler errors when added incrementally in parallel with concepts introduced in class. The rules simplify grading (since the instructor can focus on value-added content instead of semantic correctness). In addition, the rules conform to the Seven Keys to Effective Feedback proposed by Grant Wiggins:
1. Goal-Referenced (Error reduction/style conformance)
2. Tangible and Transparent (Rules clearly explain what is wrong)
3. Actionable (Error messages direct the modeler how to fix the issue)
4. User-Friendly (Private feedback that marks elements with to simplify repair)
5. Timely (On demand and rapid feedback eliminates errors before they accumulate)
6. Ongoing (Available throughout the course of any modeling project)
7. Consistent (All students receive the same feedback).
The rules were continuously updated throughout the term in which they were introduced; students corrected new errors and improved their model quality as they executed their term projects. Extracts from six team projects will be presented and contrasted with selected past projects (subjected to the same validation rules) to demonstrate the efficacy of the approach. Several models published by notable SysML modelers will also be analyzed.
Research Interests:
The Department of Defense's Digital Engineering Strategy (adopted in June 2018) has five goals: 1. Formalize the development, integration, and use of models to inform enterprise and program decision making 2. Provide an enduring,... more
The Department of Defense's Digital Engineering Strategy (adopted in June 2018) has five goals: 1. Formalize the development, integration, and use of models to inform enterprise and program decision making 2. Provide an enduring, authoritative source of truth 3. Incorporate technological innovation to improve the engineering practice 4. Establish a supporting infrastructure and environment to perform activities, collaborate, and communicate across stakeholders 5. Transform the culture and workforce to adopt and support digital engineering across the life cycle. 1 For this strategy to succeed, stakeholders must willingly participate in the cultural transformation and use system models as they are intended: as living, dynamic, integrated sources of information that communicate intent with rigor and clarity. Moving from disjointed documents and air-gapped information sources to a single source of truth is important. However, the explosive growth in system complexity is causing a new, unwanted emergent behavior: In an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it. 2 Because stakeholders are becoming overwhelmed with information from multiple sources, effective system modeling cannot solely focus on the creation of competently executed, integrated system models. It must also facilitate the creation of visualizations and derived products that allow stakeholders to efficiently identify and consume relevant information.
Research Interests:
Competent execution of descriptive models in SysML, the system modeling language, facilitates rigor and analysis in support of systems architecture and engineering activities. However, this requires mastery of SysML, the selected... more
Competent execution of descriptive models in SysML, the system modeling language, facilitates rigor and analysis in support of systems architecture and engineering activities. However, this requires mastery of SysML, the selected modeling tool, and the method used. A semester-long course is not long enough to provide students with adequate time and experience to independently construct a high-quality model.
This paper details the content and use of the hypermodel profile, originally released by the author in 2017. It contains an organizational structure, stereotypes, queries, analysis aids, metrics, and quality checks that can be leveraged by students. Use of the profile allows students to focus on the intellectual content of their assignments while modeling in compliance to a provided style guide. It permits them to experience the benefits of automated quality checks, detailed inferential queries, and other modeling aids without having to have the advanced knowledge to construct them independently. This approach also exposes students to the full benefits of a sophisticated model and encourages them to explore and gain deeper insights into their system of interest.
The specifics of the hypermodel profile will be presented, including its organization, content, and customizations. Guidelines for its use will be presented in conjunction with lessons learned from its use at the University of Detroit Mercy in the Master of Science Product Development, Systems Engineering Certificate, and Advanced Electric Vehicle programs.
This paper details the content and use of the hypermodel profile, originally released by the author in 2017. It contains an organizational structure, stereotypes, queries, analysis aids, metrics, and quality checks that can be leveraged by students. Use of the profile allows students to focus on the intellectual content of their assignments while modeling in compliance to a provided style guide. It permits them to experience the benefits of automated quality checks, detailed inferential queries, and other modeling aids without having to have the advanced knowledge to construct them independently. This approach also exposes students to the full benefits of a sophisticated model and encourages them to explore and gain deeper insights into their system of interest.
The specifics of the hypermodel profile will be presented, including its organization, content, and customizations. Guidelines for its use will be presented in conjunction with lessons learned from its use at the University of Detroit Mercy in the Master of Science Product Development, Systems Engineering Certificate, and Advanced Electric Vehicle programs.
Research Interests:
Document-Intensive Systems Engineering (DISE) is inadequate to the task of developing complicated and complex systems. Model-Based Systems Engineering (MBSE) was created to address this gap. System modeling software continues to grow in... more
Document-Intensive Systems Engineering (DISE) is inadequate to the task of developing complicated and complex systems. Model-Based Systems Engineering (MBSE) was created to address this gap. System modeling software continues to grow in power and capability but there is a shortage of individuals capable of using these tools to their fullest potential. This dearth of talent is slowing the transformation of systems engineering to a model-based discipline. A muddle of publications that obscure high-quality content compounds this problem. Every moment spent on a low-value paper or book robs practitioners of growth. This presentation will share a curated collection of heuristics, resources, and techniques aimed at maximizing the return on an individual's investment. Case studies, philosophy, and discussions from antiquity to today will be compiled into an integrated program for personal development. An emphasis will be placed on resources to help students and practitioners to understand the problem at hand, its context, and how to assess it in a systems context.
Research Interests:
System modeling is continuing to grow in importance as the enabling discipline for digital engineering. Descriptive system models can be used as the “central nervous system” of a system development effort (to federate a constellation of... more
System modeling is continuing to grow in importance as the enabling
discipline for digital engineering. Descriptive system models can be used as the “central nervous system” of a system development effort (to federate a constellation of analytical models and other engineering content).
Hypermodeling is a methodology focused on maximizing model elegance through the efficient generation of a descriptive system model (with appropriate supporting content). It emphasizes the most simple, direct approach to rigorously capturing relevant information. Hypermodels use a limited set of model elements, relationships, and properties and seek to maximize the amount of information derived from the model.
The NeMO hypermodel, an example built by students at the University of
Detroit Mercy, provides a comprehensive demonstration of this approach and includes behavioral, structural, and analytic information as well as metrics and requirements.
It is hoped that this large example will serve as a focus for discussion and experimentation in the system modeling community. Links to hypermodeling tutorial videos are available for study and comment at the hypermodeling website: http://hypermodeling.systems.
discipline for digital engineering. Descriptive system models can be used as the “central nervous system” of a system development effort (to federate a constellation of analytical models and other engineering content).
Hypermodeling is a methodology focused on maximizing model elegance through the efficient generation of a descriptive system model (with appropriate supporting content). It emphasizes the most simple, direct approach to rigorously capturing relevant information. Hypermodels use a limited set of model elements, relationships, and properties and seek to maximize the amount of information derived from the model.
The NeMO hypermodel, an example built by students at the University of
Detroit Mercy, provides a comprehensive demonstration of this approach and includes behavioral, structural, and analytic information as well as metrics and requirements.
It is hoped that this large example will serve as a focus for discussion and experimentation in the system modeling community. Links to hypermodeling tutorial videos are available for study and comment at the hypermodeling website: http://hypermodeling.systems.
Research Interests:
Model-Based Systems Engineering (MBSE) has grown in popularity since the introduction of SysML a decade ago. Pockets of modeling excellence have developed within many government, industrial, and educational organizations. Few, if any,... more
Model-Based Systems Engineering (MBSE) has grown in popularity since the introduction of SysML a decade ago. Pockets of modeling excellence have developed within many government, industrial, and educational organizations. Few, if any, have achieved " wall-to-wall " adoption. This paper will focus on a key component of a successful system modeling efforts: the individuals who must translate sound systems engineering into robust, useful system models. The author routinely teaches systems architecture, systems engineering, and system modeling and will share methods and techniques for identifying and growing modeling talent. Success depends as much upon mindset and approach as it does upon understanding tool user interfaces and modeling conventions. Published texts, class exercises, videos, and case studies can be used to shape engineers' problem-solving methods. In addition, a craft system (with apprentice, journeyman, and master modelers engaged in interlocking skill development and mentoring) has shown significant promise as a way to increase the number of competent modelers. Best practices, high-value resources, and working groups (such as those organized by the International Council on Systems Engineering) will be highlighted.
Research Interests:
Best Paper Award, Systems Engineering Division Model Based Systems Engineering (MBSE) is transforming how systems engineering is practiced. System modeling with SysML (the Systems Modeling Language) drives rigor and crispness into the... more
Best Paper Award, Systems Engineering Division
Model Based Systems Engineering (MBSE) is transforming how systems engineering is practiced. System modeling with SysML (the Systems Modeling Language) drives rigor and crispness into the formulation of system behavior, structure, and parametrics. The author has introduced MBSE into the Systems Architecture and Systems Engineering courses that are part of the MS Product Development (MPD) program at the University of Detroit Mercy. This presentation will discuss lessons learned over the course of several years, culminating in the capstone project from the Spring 2016 Systems Engineering course.
In that course, students were required to model a polar exploration submarine, starting from a handful of system elements provided by the instructor. Over the course of the exercise, the students matured the model, increasing its detail and complexity through organic growth. The final outcome was a respectable fraction of the size of large, professionally executed efforts (such as the 30 meter telescope model still under development).
The significant advantages in clarity, consistency, and overall integrity of a model-driven systems engineering effort will be highlighted; an emphasis will be placed on derived work products (tables, matrices, and derived properties) and their ability to provide relevant content to stakeholders.
Model Based Systems Engineering (MBSE) is transforming how systems engineering is practiced. System modeling with SysML (the Systems Modeling Language) drives rigor and crispness into the formulation of system behavior, structure, and parametrics. The author has introduced MBSE into the Systems Architecture and Systems Engineering courses that are part of the MS Product Development (MPD) program at the University of Detroit Mercy. This presentation will discuss lessons learned over the course of several years, culminating in the capstone project from the Spring 2016 Systems Engineering course.
In that course, students were required to model a polar exploration submarine, starting from a handful of system elements provided by the instructor. Over the course of the exercise, the students matured the model, increasing its detail and complexity through organic growth. The final outcome was a respectable fraction of the size of large, professionally executed efforts (such as the 30 meter telescope model still under development).
The significant advantages in clarity, consistency, and overall integrity of a model-driven systems engineering effort will be highlighted; an emphasis will be placed on derived work products (tables, matrices, and derived properties) and their ability to provide relevant content to stakeholders.
Research Interests:
As systems become more complicated, managing them from conceptual design through disposal has become significantly more difficult. Traditional process- and document-based methods often struggle to cope with the realities of designing and... more
As systems become more complicated, managing them from conceptual design through disposal has become significantly more difficult. Traditional process- and document-based methods often struggle to cope with the realities of designing and fielding modern engineered systems; relevant information can become segmented and out-of-sync, leading to costly errors.
The International Council on Systems Engineering initiated a Model-Based Systems Engineering initiative nearly fifteen years ago; one of the fruits of this effort is the System Modeling Language (SysML). Modern SysML tools are quite mature and have considerable capabilities to capture, characterize, and connect information.
A number of efforts are currently underway to maximize the value of SysML models, including the development of visualization, co-simulation, and robust model integration. An entire ecosystem of adjacent tools is evolving that will significantly impact the practice of systems engineering within the next five years. The author will present an integrated look at publically-available information about existing worldwide efforts and their implications for systems engineering practitioners.
The International Council on Systems Engineering initiated a Model-Based Systems Engineering initiative nearly fifteen years ago; one of the fruits of this effort is the System Modeling Language (SysML). Modern SysML tools are quite mature and have considerable capabilities to capture, characterize, and connect information.
A number of efforts are currently underway to maximize the value of SysML models, including the development of visualization, co-simulation, and robust model integration. An entire ecosystem of adjacent tools is evolving that will significantly impact the practice of systems engineering within the next five years. The author will present an integrated look at publically-available information about existing worldwide efforts and their implications for systems engineering practitioners.
Research Interests:
This article describes a deep space mission where more forthright information exchanges between teamed but rival agencies could have preserved the original plan as well as saved much time and money. The topic may be of particular interest... more
This article describes a deep space mission where more forthright information exchanges between teamed but rival agencies could have preserved the original plan as well as saved much time and money. The topic may be of particular interest to those involved in institutional collaborations where there are vested interests in protecting rather than sharing information.
For addition information, refer to the closely related topics of Information Management, Organizing Business and Enterprises to Perform Systems Engineering and Fundamentals of Services.
For addition information, refer to the closely related topics of Information Management, Organizing Business and Enterprises to Perform Systems Engineering and Fundamentals of Services.
Research Interests:
Systems Architecture (SA) is a key discipline in Systems Engineering; robust architectures enable success and flawed architectures limit performance. However, SA is challenging to teach students because it is less of a “hard” science. At... more
Systems Architecture (SA) is a key discipline in Systems Engineering; robust architectures enable
success and flawed architectures limit performance. However, SA is challenging to teach students because it is less of a “hard” science. At the University of Detroit Mercy, students in the MS Product Development (MPD) and Advanced Electric Vehicle (AEV) Certificate programs are exposed to a full term of SA. This class stresses the development of heuristics through exposure to mini case studies, class discussions, and several projects (including a field trip to the Henry Ford Museum to study multiple examples of competing historical architectures). The capstone project in this class requires teams of students to create a new architecture for a given set of criteria. One recent final project involved the creation of a space probe architecture that could meet
mission objectives given a challenging set of constraints and the creation of DODAF Viewpoints to communicate the architecture.
success and flawed architectures limit performance. However, SA is challenging to teach students because it is less of a “hard” science. At the University of Detroit Mercy, students in the MS Product Development (MPD) and Advanced Electric Vehicle (AEV) Certificate programs are exposed to a full term of SA. This class stresses the development of heuristics through exposure to mini case studies, class discussions, and several projects (including a field trip to the Henry Ford Museum to study multiple examples of competing historical architectures). The capstone project in this class requires teams of students to create a new architecture for a given set of criteria. One recent final project involved the creation of a space probe architecture that could meet
mission objectives given a challenging set of constraints and the creation of DODAF Viewpoints to communicate the architecture.
Research Interests:
Robust systems architecture (SA) and systems engineering (SE) processes are necessary for the development of successful engineering systems. Many notable product failures can be traced to breakdowns in the architectural or systems... more
Robust systems architecture (SA) and systems engineering (SE) processes are necessary for the development of successful engineering systems. Many notable product failures can be traced to
breakdowns in the architectural or systems engineering practices of the design team.
Despite the increased emphasis being placed on systems engineering, many systems engineering
textbooks and references focus on speci?c tools (such as requirements or interface management
systems). The few case studies included in these works are typically not exhaustive.
Well-constructed case studies can be used as the kernel of discussion among peers in the workplace. This case features a discussion about NASA’s CONTOUR mission; its failure illustrates a number of important SE principles.
breakdowns in the architectural or systems engineering practices of the design team.
Despite the increased emphasis being placed on systems engineering, many systems engineering
textbooks and references focus on speci?c tools (such as requirements or interface management
systems). The few case studies included in these works are typically not exhaustive.
Well-constructed case studies can be used as the kernel of discussion among peers in the workplace. This case features a discussion about NASA’s CONTOUR mission; its failure illustrates a number of important SE principles.
Research Interests:
The Joint Light Tactical Vehicle (JLTV) Family of Vehicles (FoV) is the central component of the Army’s long - term Tactical Wheeled Vehicle (TWV) strategy. The program’s objective is to balance critical weight and transportability... more
The Joint Light Tactical Vehicle (JLTV) Family of Vehicles (FoV) is the central component of the Army’s long - term Tactical Wheeled Vehicle (TWV) strategy. The program’s objective is to balance critical weight and transportability restrictions within performance, protection, and payload requirements of the United States Army and Marine Corps.
One of the challenges faced by the JLTV program is the need to balance the “Iron Triangle” of performance, protection, and payload while managing the disparate requirements of the domestic services and international partners. The JLTV team developed processes to manage the cost, performance, and schedule risks associated with each of the three contractors participating in the Technology Development phase. This paper will describe the risk management processes and tools developed on the JLTV program to manage and mitigate these contractor risks and extract those that could impact the entire program.
One of the challenges faced by the JLTV program is the need to balance the “Iron Triangle” of performance, protection, and payload while managing the disparate requirements of the domestic services and international partners. The JLTV team developed processes to manage the cost, performance, and schedule risks associated with each of the three contractors participating in the Technology Development phase. This paper will describe the risk management processes and tools developed on the JLTV program to manage and mitigate these contractor risks and extract those that could impact the entire program.
Research Interests:
Robust systems architecture (SA) and systems engineering (SE) processes are necessary for the development of successful engineering systems. Many notable product failures can be traced to breakdowns in the architectural or systems... more
Robust systems architecture (SA) and systems engineering (SE) processes are necessary for the development of successful engineering systems. Many notable product failures can be traced to breakdowns in the architectural or systems engineering practices of the design team. Despite the increased emphasis being placed on systems engineering, many systems engineering textbooks and references focus on specific tools (such as requirements or interface management systems). The few case studies included in these works are typically not exhaustive. However, for individuals in a given working environment, developing expertise in a specific tool not used by one's workgroup adds little value. The presenters believe that it is more useful to help individuals cultivate an intuitive understanding of architectural and systems engineering issues. For that reason, they have augmented traditional SE textbooks and teaching resources with mini- and maxi-case studies. Using topics drawn from throughout human history (from ancient tombs and medieval cathedrals to the Airbus A380/Boeing 787 and NASA space missions), the presenters showcase both notable successes and failures. This enhances learning and retention of key topics and enables students to internalize key SA/SE principles. Cases may be presented using a variety of media (including PowerPoint slides, audio-visual presentations, or show-and-tell artifacts). They may be used as lead-ins to a traditional classroom lecture or as the kernel of a roundtable discussion among peers in the workplace. This tutorial will demonstrate the principles the presenters use to identify case study candidates, research methods used to develop the framework of the presentations, and techniques used to develop a holistic SE mindset. Several case studies will be interleaved with the presentation; one maxi-case (intended to be the focus of an entire class period) will be presented as the capstone of the tutorial.
Research Interests:
The discipline of systems engineering is receiving more attention from both the academic and practicing engineering communities. Many high-profile engineering failures (including several recent NASA missions and a variety of product... more
The discipline of systems engineering is receiving more attention from both the academic and practicing engineering communities. Many high-profile engineering failures (including several recent NASA missions and a variety of product recalls) have all been traced to breakdowns in systems engineering.
However, the architecture of an engineering system has an even greater impact on its performance, robustness, and properties. Outstanding systems engineering and detail design cannot salvage an architecture that is fundamentally flawed. Despite architecture’s importance, many organizations do not explicitly explore alternatives and “jump” directly to systems-level design. This prematurely collapses the design space and squanders the opportunity to explore alternatives at the least costly phase in the design process.
Therefore, it is important to educate engineering managers about the key role that both systems architecture and systems engineering play in the success or failure of an engineering system. It is the belief of the authors that this may be accomplished reasonably well in a single course in programs where a more in-depth course sequence is not a realistic option. Although combining these topics restricts the depth at which either may be taught, there are natural synergies that allow this combination.
The goal of this combined course is to familiarize the engineering management students with both systems architecture and systems engineering, to understand the common pitfalls associated with each, and to begin to develop a mindset that continually considers architectural and systems engineering consequences of management decisions. The course focuses more on the “what” and “why” of systems architecture and systems engineering and less on the “how.” Detailed discussion of specific tools (such as DOORS) is omitted or significantly abbreviated to allow more time to be spent on fundamentals and case studies.
However, the architecture of an engineering system has an even greater impact on its performance, robustness, and properties. Outstanding systems engineering and detail design cannot salvage an architecture that is fundamentally flawed. Despite architecture’s importance, many organizations do not explicitly explore alternatives and “jump” directly to systems-level design. This prematurely collapses the design space and squanders the opportunity to explore alternatives at the least costly phase in the design process.
Therefore, it is important to educate engineering managers about the key role that both systems architecture and systems engineering play in the success or failure of an engineering system. It is the belief of the authors that this may be accomplished reasonably well in a single course in programs where a more in-depth course sequence is not a realistic option. Although combining these topics restricts the depth at which either may be taught, there are natural synergies that allow this combination.
The goal of this combined course is to familiarize the engineering management students with both systems architecture and systems engineering, to understand the common pitfalls associated with each, and to begin to develop a mindset that continually considers architectural and systems engineering consequences of management decisions. The course focuses more on the “what” and “why” of systems architecture and systems engineering and less on the “how.” Detailed discussion of specific tools (such as DOORS) is omitted or significantly abbreviated to allow more time to be spent on fundamentals and case studies.
Research Interests:
Research Interests:
Good systems architecture and systems engineering processes are key enablers for the development of innovative, robust engineering systems. Many product failures can be traced directly to breakdowns in the architectural or systems... more
Good systems architecture and systems engineering processes are key enablers for the development of innovative, robust engineering systems. Many product failures can be traced directly to breakdowns in the architectural or systems engineering practices of the design team.
Despite the increased emphasis on systems engineering, most systems engineering textbooks tend to focus on specific tools (such as requirements or interface management systems) or describe the systems engineering and systems architecting process in a rather generic discussion. Case studies are typically brief and relatively sparse.
A typical teaching approach is to introduce a tool, illustrate how the tool can be applied, introduce another tool, etc. However, cultivating expertise in specific tools that may not be in use by a student’s employer adds little value – particularly if the student misses the holistic understanding of the topic because he is focusing on details of the tool. The authors believe that it is more useful to focus on teaching students to intuitively understand architectural and systems engineering issues. For that reason, they have adopted a case-based approach to teaching these topics.
Using topics drawn from history (ancient tombs and medieval cathedrals) and current events (the Airbus A380/Boeing 787 and the Ansari X Prize Competition), the authors present a broad spectrum of cases to their students. This engages the students, sparks classroom discussion, and enhances learning and retention of key topics.
The cases are presented using a variety of media (including PowerPoint slides, audio-visual presentations, or show-and-tell artifacts). The cases are typically used as lead-ins to the lecture, allowing the instructor to draw upon the outcomes (both positive and negative) of the case to illustrate key learning principles in the main lecture. Relevant and useful tools are still taught (such as QFD, Design Structure Matrices, functional decomposition, etc.) but the case studies provide interesting, motivational examples illustrating the need for such tools and the authors find it useful to ask the students to discuss how the tools of today might be (or have been) utilized in the design of the subjects of the case studies.
Case studies are also assigned as homework, allowing the students to research a topic and draw their own conclusions from their research and the course material. These assignments are sufficiently structured to foster students’ development but allow them some latitude to explore the topic. The purpose is to develop their analytical skills and encourage holistic viewpoints rather than requiring simple rote learning.
This paper will summarize several of the specific case studies which the authors use and discuss how each one is tied to specific topics and learning objectives of the courses. This case-based approach has been applied to separate, semester long courses in Systems Architecture and Systems Engineering as well as a condensed version of those two courses (a single semester course entitled Systems Architecture and Systems Engineering).
Despite the increased emphasis on systems engineering, most systems engineering textbooks tend to focus on specific tools (such as requirements or interface management systems) or describe the systems engineering and systems architecting process in a rather generic discussion. Case studies are typically brief and relatively sparse.
A typical teaching approach is to introduce a tool, illustrate how the tool can be applied, introduce another tool, etc. However, cultivating expertise in specific tools that may not be in use by a student’s employer adds little value – particularly if the student misses the holistic understanding of the topic because he is focusing on details of the tool. The authors believe that it is more useful to focus on teaching students to intuitively understand architectural and systems engineering issues. For that reason, they have adopted a case-based approach to teaching these topics.
Using topics drawn from history (ancient tombs and medieval cathedrals) and current events (the Airbus A380/Boeing 787 and the Ansari X Prize Competition), the authors present a broad spectrum of cases to their students. This engages the students, sparks classroom discussion, and enhances learning and retention of key topics.
The cases are presented using a variety of media (including PowerPoint slides, audio-visual presentations, or show-and-tell artifacts). The cases are typically used as lead-ins to the lecture, allowing the instructor to draw upon the outcomes (both positive and negative) of the case to illustrate key learning principles in the main lecture. Relevant and useful tools are still taught (such as QFD, Design Structure Matrices, functional decomposition, etc.) but the case studies provide interesting, motivational examples illustrating the need for such tools and the authors find it useful to ask the students to discuss how the tools of today might be (or have been) utilized in the design of the subjects of the case studies.
Case studies are also assigned as homework, allowing the students to research a topic and draw their own conclusions from their research and the course material. These assignments are sufficiently structured to foster students’ development but allow them some latitude to explore the topic. The purpose is to develop their analytical skills and encourage holistic viewpoints rather than requiring simple rote learning.
This paper will summarize several of the specific case studies which the authors use and discuss how each one is tied to specific topics and learning objectives of the courses. This case-based approach has been applied to separate, semester long courses in Systems Architecture and Systems Engineering as well as a condensed version of those two courses (a single semester course entitled Systems Architecture and Systems Engineering).
Research Interests:
In the early 20th century, engineers were closely coupled to the products they created. Tinkerers and inventors built upon their existing experiences and innovated. Many grew up working on farm implements or other mechanical devices and... more
In the early 20th century, engineers were closely coupled to the products they created. Tinkerers and inventors built upon their existing experiences and innovated. Many grew up working on farm implements or other mechanical devices and developed a deep, intuitive understanding of how mechanisms worked. As the century progressed, the propagation of the automobile gave several generations of engineers the opportunity to develop their skills by rebuilding engines, tinkering with suspensions, and performing general maintenance. Today, in the generation of video games and automobiles so complex that few owners venture to work on them, many new engineering graduates have not had sufficient hands-on experiences to develop a strong intuitive understanding of mechanical and electrical systems. They have neither soldered their own crystal radios nor built their own machinery; a general deglamorizing of skilled trades has reduced or eliminated shop classes and students are now more at home in a virtual world. It is now possible for engineers to design parts they never see or touch-not to mention fabricate; this often results in a poor overall understanding of the system being designed and contributes to the proliferation of poor designs. Unfortunately, this gap has led to a generation of engineers who lack sufficient intuitive knowledge about systems. This allows errors to slip by undetected and leads to suboptimization. To offset this, the Masters in Product Development (MPD) program at the University of Detroit-Mercy engages its students in design challenges. These activities allow the participants to apply their coursework and demonstrate their mastery of the material; they also allow them to gain knowledge about fabrication techniques. This paper will discuss several of the design challenges used during the MPD January Experience (an intensive, two-week "boot camp" that combines coursework and a hands-on team design project). These events build esprit d'corps and jumpstart the program; each Experience culminates in a friendly competition at the end of the session. Design projects used during other MPD courses will also be discussed. For many of the student teams, the rather humbling experience of having to fabricate something which they designed widens their perspectives on engineering.
Research Interests:
1 Brymer Chin, Distinguished Member of Technical Staff , Lucent Technologies, 67 Whippany Road, Room 15B-029A, Whippany, NJ 07981, bhchin@lucent.com 2 George Dellagiarino, Geologist – Team Leader, U.S. Minerals Management Service, 381... more
1 Brymer Chin, Distinguished Member of Technical Staff , Lucent Technologies, 67 Whippany Road, Room 15B-029A, Whippany, NJ 07981, bhchin@lucent.com 2 George Dellagiarino, Geologist – Team Leader, U.S. Minerals Management Service, 381 Elden Street MS 4070, Herndon, VA 20170, george.dellagiarino@mms.gov 3 Katarina Midelfort, Ph.D. student, Biological Engineering Division, Massachusetts Institute of Technology, 377A Cardinal Medeiros Avenue #3, Cambridge, MA 02141, katarina@mit.edu 4 Michael Vinarcik, Interior Trim Engineer, Ford Motor Company, 20032 Weyher Street, Livonia, MI 48152, mvinarci@ford.com 5 Mirolee Zieba, Bachelor of Science – Molecular Biology and Biochemistry, Rensselaer Polytechnic Institute, 47 Gore Rd, Raymond, ME 04071 ziebam@rpi.edu 6 Carol B. Muller, Ph.D., Founder and CEO, MentorNet, c/o COE, SJSU, One Washington Square, San Jose, CA 95192-0080, cbmuller@mentornet.net Abstract MentorNet (www.MentorNet.net), the EMentoring Network for Women in Engineering and Sc...
Research Interests:
The cost of cybercrime is measured in trillions of dollars (Forbes, 2023) and the risk to national security due to cyber attack is equally grave. An essential step in reducing the risk posed by cyber threats is to craft appropriately... more
The cost of cybercrime is measured in trillions of dollars (Forbes, 2023) and the risk to national security due to cyber attack is equally grave. An essential step in reducing the risk posed by cyber threats is to craft appropriately modularized and inherently secure system architectures and ensuring that as-written code reflects design intent. This presentation will explore the use of architectural analysis to create inherent resistance to cybersecurity threats by identifying possible attack vectors and interdicting them. It will then demonstrate how automated architecture-to-code matching can verify that the integrity of the design was not compromised by downstream development processes. An example case study will be presented that illustrates a full lifecycle (from concept through implementation) supported by automated and human-in-the-loop analysis.
https://www.forbes.com/sites/chuckbrooks/2023/03/05/cybersecurity-trends--statistics-for-2023-more-treachery-and-risk-ahead-as-attack-surface-and-hacker-capabilities-grow/?sh=2ddcc48919db
https://www.forbes.com/sites/chuckbrooks/2023/03/05/cybersecurity-trends--statistics-for-2023-more-treachery-and-risk-ahead-as-attack-surface-and-hacker-capabilities-grow/?sh=2ddcc48919db
Research Interests:
The transition of systems engineering from a document-centric to a model-based discipline has been compared with the migration from drafting boards to computer-aided design (CAD). A more apt comparison may be to the craft of... more
The transition of systems engineering from a document-centric to a model-based discipline has been compared with the migration from drafting boards to computer-aided design (CAD). A more apt comparison may be to the craft of blacksmithing. Blacksmiths in antiquity lacked fundamental understanding of the iron-carbon phase diagram, the impact of alloying elements, and access to modern equipment such as power hammers, gas-fired forges, and other laborsaving devices. These craftsmen still were valued members of their community who provided value and innovation (such as in the American West, where the town blacksmith repaired tools, shod horses, and created bespoke products for the populace).
Contestants on Forged in Fire, a television program featuring competitive bladesmithing, have access to all of the metallurgical theory and modern equipment available, as well as generations of best practices...yet many still make easily avoidable blunders. The application of individual skill and knowledge still determines the outcome of each contest...and the practice of system modeling circa 2022 is similar, in that outcomes are still heavily dependent upon the skill of the individuals involved.
This presentation will explore the evolution in the author’s pedagogy during more than a decade of teaching systems architecture, systems engineering, and systems modeling. It will examine the early use of diagram-centric modeling in support of individual document-based projects, subsequent attempts to model single systems collaboratively, and current practice, in which teams of students are responsible for constructing a complete, consistent, federated system-of-systems model. The value of structured, hands-on lessons (“bringing a hammer to the anvil”) supported by task-based videos will be explored. Models from each epoch will be assessed for size, scope, and quality (including the application of the latest validation rules to earlier models to identify and quantify latent errors). The impact of automated validation rules as an instructional and grading aid will be presented and guidelines for structuring language, tool, and process lessons will be included.
Contestants on Forged in Fire, a television program featuring competitive bladesmithing, have access to all of the metallurgical theory and modern equipment available, as well as generations of best practices...yet many still make easily avoidable blunders. The application of individual skill and knowledge still determines the outcome of each contest...and the practice of system modeling circa 2022 is similar, in that outcomes are still heavily dependent upon the skill of the individuals involved.
This presentation will explore the evolution in the author’s pedagogy during more than a decade of teaching systems architecture, systems engineering, and systems modeling. It will examine the early use of diagram-centric modeling in support of individual document-based projects, subsequent attempts to model single systems collaboratively, and current practice, in which teams of students are responsible for constructing a complete, consistent, federated system-of-systems model. The value of structured, hands-on lessons (“bringing a hammer to the anvil”) supported by task-based videos will be explored. Models from each epoch will be assessed for size, scope, and quality (including the application of the latest validation rules to earlier models to identify and quantify latent errors). The impact of automated validation rules as an instructional and grading aid will be presented and guidelines for structuring language, tool, and process lessons will be included.
Research Interests:
In 1913-1914, Theodore Roosevelt set off into the unknown and explored the River of Doubt in the Amazon Basin. Although he was successful in charting the river, the expedition was hindered by planning errors, terrain, and the specter of... more
In 1913-1914, Theodore Roosevelt set off into the unknown and explored the River of Doubt in the Amazon Basin. Although he was successful in charting the river, the expedition was hindered by planning errors, terrain, and the specter of attacks by the indigenous population. Roosevelt’s health was permanently compromised by the strain of the adventure. Organizations embarking on digital transformations also step off into the unknown and can suffer avoidable missteps as they adapt their tools, processes, and culture. This presentation will highlight best practices, showcase available resources, and demonstrate the potential of successful digital engineering efforts.
Research Interests:
The success of digital engineering depends upon the creation of well-crafted descriptive architectures as a foundational element of the digital thread. These curated collections of design intent can be used to conduct trade studies,... more
The success of digital engineering depends upon the creation of well-crafted descriptive architectures as a foundational element of the digital thread. These curated collections of design intent can be used to conduct trade studies, develop requirements, and drive downstream design activities. Gaps, inconsistencies, or errors in architectures generate wasted efforts (at best), increase test and integration costs (most likely), or induce latent failures that appear during the operation of a system.
Since 2019, SAIC has provided its Digital Engineering Validation Tool as a service to the worldwide SysML community. Its automated validation rules ensure compliance with the SAIC style guide, detect errors in language usage, and identify gaps and inconsistencies in the descriptive architecture.
This presentation will explore the application of the current validation ruleset to models created by students at the University of Detroit Mercy from 2016-2023. The modeling approach taught to the students was consistent throughout this period; however, the models developed before 2018 were not validated. The latent errors in these models will be quantified and an initial set of analyses and conclusions will be presented to illustrate the value of automated validation rules in eliminating errors, ensuring style guide conformance, and enforcing behavioral/structural integrity.
Since 2019, SAIC has provided its Digital Engineering Validation Tool as a service to the worldwide SysML community. Its automated validation rules ensure compliance with the SAIC style guide, detect errors in language usage, and identify gaps and inconsistencies in the descriptive architecture.
This presentation will explore the application of the current validation ruleset to models created by students at the University of Detroit Mercy from 2016-2023. The modeling approach taught to the students was consistent throughout this period; however, the models developed before 2018 were not validated. The latent errors in these models will be quantified and an initial set of analyses and conclusions will be presented to illustrate the value of automated validation rules in eliminating errors, ensuring style guide conformance, and enforcing behavioral/structural integrity.
Research Interests:
Although Robert Frost was the first to use this phrase, it echoes long held homespun wisdom that clear boundaries foster respectful and productive relations between adjacent individuals (provided they are not impermeable). As the ongoing... more
Although Robert Frost was the first to use this phrase, it echoes long
held homespun wisdom that clear boundaries foster respectful and productive relations between adjacent individuals (provided they are not impermeable). As the ongoing digital transformation of engineering continues, stakeholders must balance the need to protect intellectual property and sensitive information with the benefits
inherent in sharing content with the digital thread.
This presentation will provide insights into how pragmatic model stewardship and organization can facilitate the development of consistent and complete federated models. The utility of a common library of shared content and surrogate elements will be demonstrated by an example collection of SysML descriptive architecture models. Two sets of automated validation rules will be discussed; one set ensures that shared surrogate elements are correct and complete, the second set tests the consistency between the interfaces represented in the federation model and the individual stakeholder models. These rules will also be applied to previously released federated models to determine if errors had leaked past manual reviews
held homespun wisdom that clear boundaries foster respectful and productive relations between adjacent individuals (provided they are not impermeable). As the ongoing digital transformation of engineering continues, stakeholders must balance the need to protect intellectual property and sensitive information with the benefits
inherent in sharing content with the digital thread.
This presentation will provide insights into how pragmatic model stewardship and organization can facilitate the development of consistent and complete federated models. The utility of a common library of shared content and surrogate elements will be demonstrated by an example collection of SysML descriptive architecture models. Two sets of automated validation rules will be discussed; one set ensures that shared surrogate elements are correct and complete, the second set tests the consistency between the interfaces represented in the federation model and the individual stakeholder models. These rules will also be applied to previously released federated models to determine if errors had leaked past manual reviews
Research Interests:
The Telephone Game is an icebreaker activity in which an individual phrase or sentence is passed down a chain of participants, one whisper at a time. By the time the final player announces what he has heard, the content has typically... more
The Telephone Game is an icebreaker activity in which an individual phrase or sentence is passed down a chain of participants, one whisper at a time. By the time the final player announces what he has heard, the content has typically morphed significantly from the initial statement. While this may be an amusing party game, degradation of design intent through misinterpretation and low fidelity transformations can negatively impact the success of product development efforts.
This presentation will demonstrate the use of Design Structure Matrices (DSM) to analyze and partition descriptive SysML models. This approach can be used to support Modular Open Systems Architecture (MOSA) development efforts. In addition, the DSM can be used to establish dependency rules that can be applied to software, ensuring that the as coded result matches the as architected design intent. An example cyberphysical system (a notional drone and open source control software) will be used as the basis for this discussion. Lessons learned and best practices for stewarding the SysML and code synchronization will be presented.
This presentation will demonstrate the use of Design Structure Matrices (DSM) to analyze and partition descriptive SysML models. This approach can be used to support Modular Open Systems Architecture (MOSA) development efforts. In addition, the DSM can be used to establish dependency rules that can be applied to software, ensuring that the as coded result matches the as architected design intent. An example cyberphysical system (a notional drone and open source control software) will be used as the basis for this discussion. Lessons learned and best practices for stewarding the SysML and code synchronization will be presented.
Research Interests:
This presentation will discuss the current state of the practice of Model-Based Systems Engineering and Digital Engineering in 2022. It will present the advantages of applying automated validation to system models, the opportunities... more
This presentation will discuss the current state of the practice of Model-Based Systems Engineering and Digital Engineering in 2022. It will present the advantages of applying automated validation to system models, the opportunities inherent in validation-assisted training, the use of semantic broker technology to exchange data throughout the digital thread, and lessons learned from federating and analyzing descriptive architectures. Case studies, lessons learned, and examples illustrating key points will be shared to emphasize the value that can be achieved through competent system modeling and stewardship of the digital thread.
Research Interests:
System modeling is a skills-based discipline that relies upon talented individuals to transform knowledge and information about a system-of-interest into rigorous system models. A shortage of these individuals is slowing the adoption of... more
System modeling is a skills-based discipline that relies upon talented individuals to transform knowledge and information about a system-of-interest into rigorous system models. A shortage of these individuals is slowing the adoption of Model-Based Systems Engineering (MBSE). Traditional classroom-based training has been unable to fill the pipeline with adequate numbers of capable practitioners.
This presentation will showcase a hands-on, project-based approach to creating skilled system modelers. It illustrates the utility of developing an end-to-end system model (from use cases and conceptual to physical architecture) in giving junior modelers hands-on experience and the confidence to lead MBSE efforts.
Two junior modelers were given the task of modeling the Ranger lunar probes from the 1960s. This system-of-interest was well-documented and free of security or intellectual property concerns. Research was necessary to locate key system attributes (serving as a surrogate for interaction with subject-matter experts) and the existing architectural information was translated into SysML. The project was supported by SAIC’s Digital Engineering Profile; its customizations were used to capture relevant information and its validation rules supported the construction of a clean, consistent model.
By the time they concluded the project, the modelers had gained a visceral understanding of good modeling practices and are well-positioned to lead system modeling efforts. They also learned valuable lessons about model organization and consistency that would have been impossible to internalize through lecture or examinations. The use of the SAIC DE Profile's validation rules provided them with timely, consistent feedback on their model and modeling techniques. The modelers also identified several bugs and oversights in the ruleset and contributed directly to improving its quality.
This presentation will include examples drawn from the Ranger model as well as a timeline showing model growth and maturation vs. hours expended by the modeling team. Key lessons learned will be presented in the context of developing an organization-specific internal modeler development program. This approach is easily scalable to fill an organization's pipeline with competent system modelers.
This presentation will showcase a hands-on, project-based approach to creating skilled system modelers. It illustrates the utility of developing an end-to-end system model (from use cases and conceptual to physical architecture) in giving junior modelers hands-on experience and the confidence to lead MBSE efforts.
Two junior modelers were given the task of modeling the Ranger lunar probes from the 1960s. This system-of-interest was well-documented and free of security or intellectual property concerns. Research was necessary to locate key system attributes (serving as a surrogate for interaction with subject-matter experts) and the existing architectural information was translated into SysML. The project was supported by SAIC’s Digital Engineering Profile; its customizations were used to capture relevant information and its validation rules supported the construction of a clean, consistent model.
By the time they concluded the project, the modelers had gained a visceral understanding of good modeling practices and are well-positioned to lead system modeling efforts. They also learned valuable lessons about model organization and consistency that would have been impossible to internalize through lecture or examinations. The use of the SAIC DE Profile's validation rules provided them with timely, consistent feedback on their model and modeling techniques. The modelers also identified several bugs and oversights in the ruleset and contributed directly to improving its quality.
This presentation will include examples drawn from the Ranger model as well as a timeline showing model growth and maturation vs. hours expended by the modeling team. Key lessons learned will be presented in the context of developing an organization-specific internal modeler development program. This approach is easily scalable to fill an organization's pipeline with competent system modelers.
Research Interests:
Effective instruction in system modeling requires an emphasis on hands-on exercises. This paper presents lessons learned from coordinating and grading eight collaborative and integrated SysML models; in addition, it includes extracts from... more
Effective instruction in system modeling requires an emphasis on hands-on exercises. This paper presents lessons learned from coordinating and grading eight collaborative and integrated SysML models; in addition, it includes extracts from team projects and metrics related to model size and style conformance.
Research Interests:
Juval Löwy’s Righting Software (RS) postulates that software projects fail because of poor practices and an excessive focus on functional decomposition. He stresses the elicitation of higher-level behavioral needs and a systems... more
Juval Löwy’s Righting Software (RS) postulates that software projects fail because of poor practices and an excessive focus on functional decomposition. He stresses the elicitation of higher-level behavioral needs and a systems organization approach that focuses on encapsulating variability to minimize the coupling between software elements.
Use of system modeling in SysML enables rigorous identification and characterization of the functions, flows (matter/energy/information), and parametrics that govern a system’s structure and behavior. This content, when represented in a well-formed system model (especially when supplemented with automated validation rules that detects errors, inconsistencies, and gaps), can be used to analyze the system-of-interest to expose efficient and effective partitioning.
This presentation will showcase the application of Design Structure Matrix (DSM) techniques to system models. Architectures constructed with RS’s principles will be compared and contrasted with examples generated by applying DSMs.
Use of system modeling in SysML enables rigorous identification and characterization of the functions, flows (matter/energy/information), and parametrics that govern a system’s structure and behavior. This content, when represented in a well-formed system model (especially when supplemented with automated validation rules that detects errors, inconsistencies, and gaps), can be used to analyze the system-of-interest to expose efficient and effective partitioning.
This presentation will showcase the application of Design Structure Matrix (DSM) techniques to system models. Architectures constructed with RS’s principles will be compared and contrasted with examples generated by applying DSMs.
Research Interests:
The continuing transformation of systems engineering from a document-intensive (DISE) to model-based (MBSE) discipline is enabling richer systems analysis. System models are inherently unambiguous and rigorous representations of design... more
The continuing transformation of systems engineering from a document-intensive (DISE) to model-based (MBSE) discipline is enabling richer systems analysis. System models are inherently unambiguous and rigorous representations of design intent (especially when supplemented with automated validation rules that detects errors, inconsistencies, and gaps). They enable direct analysis by specialty engineering (such as reliability & maintainability, ESOH, and cybersecurity).
State-machine behavioral representations are particularly useful for ESOH and cybersecurity analysis. This presentation builds upon techniques described in prior NDIA papers on failure mode and effects analysis, cybersecurity, and pragmatic hazard identification and risk management to demonstrate the value that can be extracted from a system model in support of these stakeholders.
State-machine behavioral representations are particularly useful for ESOH and cybersecurity analysis. This presentation builds upon techniques described in prior NDIA papers on failure mode and effects analysis, cybersecurity, and pragmatic hazard identification and risk management to demonstrate the value that can be extracted from a system model in support of these stakeholders.
Research Interests:
The digital transformation currently underway in nearly every commercial, defense, and government domain is unlocking much-needed capabilities but faces cultural and technical obstacles. Enabling the cultural shift needed to allow systems... more
The digital transformation currently underway in nearly every commercial, defense, and government domain is unlocking much-needed capabilities but faces cultural and technical obstacles. Enabling the cultural shift needed to allow systems thinking and robust systems engineering to permeate organizations can be just as daunting as overcoming the barriers to the creation of the digital thread. Leading an organization to success requires a combination of personal factors, including wisdom, grit, and audacity.
This presentation will draw leadership lessons from four trailblazing voyages: Sir Ernest Shackleton’s Imperial Trans-Antarctic Expedition, the naval architecture revolution wrought by Sir Jackie Fisher’s HMS Dreadnought, Hugo Eckener’s circumnavigation of the globe in the LZ127 Graf Zeppelin, and Operation Sunshine, USS Nautilus’s submerged transit of the North Pole. Key principles from each of these related to personnel, technology, operations, and leadership will be applied to our modern transformation challenges.
This presentation will draw leadership lessons from four trailblazing voyages: Sir Ernest Shackleton’s Imperial Trans-Antarctic Expedition, the naval architecture revolution wrought by Sir Jackie Fisher’s HMS Dreadnought, Hugo Eckener’s circumnavigation of the globe in the LZ127 Graf Zeppelin, and Operation Sunshine, USS Nautilus’s submerged transit of the North Pole. Key principles from each of these related to personnel, technology, operations, and leadership will be applied to our modern transformation challenges.
Research Interests:
A SysML model of architecture is commonly considered the core of most digital engineering transformations. However, the power of a well-defined architecture is often not fully exploited. Early analysis of architecture using design... more
A SysML model of architecture is commonly considered the core of most digital engineering transformations. However, the power of a well-defined architecture is often not fully exploited. Early analysis of architecture using design structure matrices (DSM) can help quantify inter-component coupling, identify undesirable cycles, and determine ideal component cohesion; in the past this analysis had to be constructed manually. As tool interoperability improves, the friction associated with data interchange is reduced.
Lattix, a leading DSM tool, recently improved its SysML importer and this enables competently-executed architecture models to be analyzed in a matter of moments. Algorithms in Lattix can suggest alternative architectures before any costly design or development is initiated. Furthermore, once code begins to be developed and upgraded over time, the as-written code can be compared against the intended architecture. This enables generation of work lists and impact analyses (to transitive closure) to identify discrepancies and provide suggested fixes.
In Agile and DevOps environments, architectural analysis can be automated so that every time an architect checks in a new version of the system model, the results of the analysis are immediately available so that remedial actions can be taken before technical debt accrues. Architecture degradation (both as-designed and as-coded) is prevented and the power of a good architecture maintained throughout the lifecycle.
Lattix, a leading DSM tool, recently improved its SysML importer and this enables competently-executed architecture models to be analyzed in a matter of moments. Algorithms in Lattix can suggest alternative architectures before any costly design or development is initiated. Furthermore, once code begins to be developed and upgraded over time, the as-written code can be compared against the intended architecture. This enables generation of work lists and impact analyses (to transitive closure) to identify discrepancies and provide suggested fixes.
In Agile and DevOps environments, architectural analysis can be automated so that every time an architect checks in a new version of the system model, the results of the analysis are immediately available so that remedial actions can be taken before technical debt accrues. Architecture degradation (both as-designed and as-coded) is prevented and the power of a good architecture maintained throughout the lifecycle.
Research Interests:
There is a pressing need to develop improved training methods for developing competent system modelers. A shortage of talent is slowing the widespread adoption of model-based systems engineering (MBSE). This presentation will present... more
There is a pressing need to develop improved training methods for developing competent system modelers. A shortage of talent is slowing the widespread adoption of model-based systems engineering (MBSE). This presentation will present lessons learned and outcomes associated with university and corporate training and development programs constructed around the use of experiential learning and automated validation rules. The master’s level SysML course at the University of Detroit Mercy was recently converted to an asynchronous, online format. It consists of seven weeks of basic modeling fundamentals; the second half of the term is spent collaboratively modeling a system-of-interest. The Fall 2019 topic of these models was the Mars Society’s University Rover Challenge. Prototype validation rules were matured and expanded based upon the modeling exercises in this course; by the end of the term, three of the five modeling teams submitted models with zero errors and zero maturation warnings (zero/zero models). The rules were internalized and further refined by SAIC and released publicly as the SAIC Digital Engineering Profile. To demonstrate their usefulness in training modelers in a corporate setting, two junior modelers with no system modeling experience were given the task of modeling the Ranger lunar probe from the 1960s. They researched aspects of the probe’s architecture and collaboratively developed a system model that spanned from the concept to physical architecture spaces. Information about model maturity (size vs. hours expended and errors/warnings will be provided). Their modeling also exposed bugs and corner cases in the validation rules and materially contributed to the maturation of both the customizations and rule set. Lessons learned from both the academic and corporate settings will be presented (including suggestions for using and expanding upon the provided SAIC Digital Engineering Profile). Examples will be drawn from the Mars Rover and Ranger models (publicly released by the University of Detroit Mercy and SAIC, respectively) and their utility as references in modeler training will be explored.
Research Interests:
In December 2019, SAIC released version 1.0 of its Digital Engineering Validation Tool. This was the largest public release of validation rules to date; since then, additional versions have added an example model, model-based style... more
In December 2019, SAIC released version 1.0 of its Digital Engineering Validation Tool. This was the largest public release of validation rules to date; since then, additional versions have added an example model, model-based style guide, conversion of many rules to Rhapsody, and the inclusion of a classification and data rights profile. Feedback from the worldwide modeling community indicates that it is in daily use in multiple large organizations and is positively impacting model quality. The pedagogical use of the profile and rules was featured in Treadstone: A Process for Improving Modeling Prowess Using Validation Rules (2020 American Society for Engineering Education Annual Conference and Exposition).
This presentation will highlight the evolution of the profile and validation suite; it will also discuss the newly-added classification and data rights features and further explore the use of the content to train modelers. Lessons learned from a Fall 2020 large-scale collaborative modeling effort (a system-of-systems model federated from eight student team system models) at the University of Detroit Mercy will be featured.
This presentation will highlight the evolution of the profile and validation suite; it will also discuss the newly-added classification and data rights features and further explore the use of the content to train modelers. Lessons learned from a Fall 2020 large-scale collaborative modeling effort (a system-of-systems model federated from eight student team system models) at the University of Detroit Mercy will be featured.
Research Interests:
Research Interests:
Text-based requirements sets may not be complete, consistent, or correct. This presentation showcases how an initial set of text-based requirements may be analyzed and singularized using a SysML model. The 2019 University Rover... more
Text-based requirements sets may not be complete, consistent, or correct. This presentation showcases how an initial set of text-based requirements may be analyzed and singularized using a SysML model. The 2019 University Rover Challenge requirements were used as the basis for student projects at the University of Detroit Mercy; a pre-release version of SAIC's Digital Engineering Validation Tool was used to support requirements analysis and associated architectural modeling. This presentation will show the results of this analysis by four student teams and the resulting growth and singularization of requirements. The impact of automatic validation and modeling best practices will also be illustrated.
Research Interests:
The construction of robust descriptive and executable systems architectures, often in SysML, the systems modeling language, is an important part of modern model-based systems engineering. To be effective, these architecture models must... more
The construction of robust descriptive and executable systems architectures, often in SysML, the systems modeling language, is an important part of modern model-based systems engineering. To be effective, these architecture models must be constructed to high standards of precision and completeness (since other elements of the digital thread will use them as a connective hub). Meeting this challenge is difficult to do manually; automated validation is essential to detect errors and inconsistencies.
SAIC has advanced the discipline by freely releasing a set of validation rules that ensure the consistency, completeness, and robustness of SysML models. However, there is still the compelling need to make these architectures useful and relevant to downstream engineering activities and other stakeholders.
This case study shows how a systems architecture, robustly executed in conformance with an established methodology and ontology, can be federated into a multivendor tool ecosystem. Relevant information about software features can be seamlessly synchronized with agile development tools, impact analysis for requirements changes can be rapidly conducted by pulling atomic bits of information from CAD, architecture, and other sources. This federated, authoritative information is shared with analysis software without the “air gaps” that kill momentum and increase the potential for introducing errors. All these exercises will be shown in the context of the Aras Innovator Platform, maintaining rigorous configuration control to facilitate impact analysis if other aspects of the federated data undergo changes.
SAIC has advanced the discipline by freely releasing a set of validation rules that ensure the consistency, completeness, and robustness of SysML models. However, there is still the compelling need to make these architectures useful and relevant to downstream engineering activities and other stakeholders.
This case study shows how a systems architecture, robustly executed in conformance with an established methodology and ontology, can be federated into a multivendor tool ecosystem. Relevant information about software features can be seamlessly synchronized with agile development tools, impact analysis for requirements changes can be rapidly conducted by pulling atomic bits of information from CAD, architecture, and other sources. This federated, authoritative information is shared with analysis software without the “air gaps” that kill momentum and increase the potential for introducing errors. All these exercises will be shown in the context of the Aras Innovator Platform, maintaining rigorous configuration control to facilitate impact analysis if other aspects of the federated data undergo changes.
Research Interests:
The creation of descriptive models using SysML is a skill-focused discipline; the outcomes of a modeling effort depend upon the abilities of the modelers contributing to it. Ongoing shortages of skilled modelers are inhibiting the... more
The creation of descriptive models using SysML is a skill-focused discipline; the outcomes of a modeling effort depend upon the abilities of the modelers contributing to it. Ongoing shortages of skilled modelers are inhibiting the transition of systems engineering to a model-based discipline.
This paper illustrates the use of validation rules to support instruction (both stand-alone modeling exercises and a larger, collaborative modeling project). Validation rules have proven to be effective in reducing modeler errors when added incrementally in parallel with concepts introduced in class. The rules simplify grading (since the instructor can focus on value-added content instead of semantic correctness). In addition, the rules conform to the Seven Keys to Effective Feedback proposed by Grant Wiggins:
1. Goal-Referenced (Error reduction/style conformance)
2. Tangible and Transparent (Rules clearly explain what is wrong)
3. Actionable (Error messages direct the modeler how to fix the issue)
4. User-Friendly (Private feedback that marks elements with to simplify repair)
5. Timely (On demand and rapid feedback eliminates errors before they accumulate)
6. Ongoing (Available throughout the course of any modeling project)
7. Consistent (All students receive the same feedback).
The rules were continuously updated throughout the term in which they were introduced; students corrected new errors and improved their model quality as they executed their term projects. Extracts from six team projects will be presented and contrasted with selected past projects (subjected to the same validation rules) to demonstrate the efficacy of the approach. Several models published by notable SysML modelers will also be analyzed.
This paper illustrates the use of validation rules to support instruction (both stand-alone modeling exercises and a larger, collaborative modeling project). Validation rules have proven to be effective in reducing modeler errors when added incrementally in parallel with concepts introduced in class. The rules simplify grading (since the instructor can focus on value-added content instead of semantic correctness). In addition, the rules conform to the Seven Keys to Effective Feedback proposed by Grant Wiggins:
1. Goal-Referenced (Error reduction/style conformance)
2. Tangible and Transparent (Rules clearly explain what is wrong)
3. Actionable (Error messages direct the modeler how to fix the issue)
4. User-Friendly (Private feedback that marks elements with to simplify repair)
5. Timely (On demand and rapid feedback eliminates errors before they accumulate)
6. Ongoing (Available throughout the course of any modeling project)
7. Consistent (All students receive the same feedback).
The rules were continuously updated throughout the term in which they were introduced; students corrected new errors and improved their model quality as they executed their term projects. Extracts from six team projects will be presented and contrasted with selected past projects (subjected to the same validation rules) to demonstrate the efficacy of the approach. Several models published by notable SysML modelers will also be analyzed.
Research Interests:
The 1960s were a formative decade for systems engineering: the Apollo Program, Boeing 747, North American XB-70, Lockheed SR-71, the IBM System/360, and other iconic programs helped shaped the discipline through their successes and... more
The 1960s were a formative decade for systems engineering: the Apollo Program, Boeing 747, North American XB-70, Lockheed SR-71, the IBM System/360, and other iconic programs helped shaped the discipline through their successes and failures. This presentation will touch on the context, practices, outcomes, and lessons learned from several prominent programs and how they impacted systems engineering practice. It will include discussions of how limitations of Document-Intensive Systems Engineering (DISE) were overcome, what modern model-based practitioners can learn from these cases, and a curated list of suggested readings.
Research Interests:
The growing emphasis on Digital Engineering and the resultant strategic shift are placing increased demands on system modelers. Incomplete or flawed documents can be “worked around” to drive a program to success; one cannot “work around”... more
The growing emphasis on Digital Engineering and the resultant strategic shift are placing increased demands on system modelers. Incomplete or flawed documents can be “worked around” to drive a program to success; one cannot “work around” an incomplete or flawed system model in a federated ecosystem of digital information. This paper will explore the impact of modeling practices on model value and the subsequent impact on ROI. Multiple models will be constructed from the same source material using different methods and practices. Element counts, hours expended, uncorrected gaps, and other metrics will be explored to illustrate that suboptimal methods have a lasting impact on modeling outcomes from both the model builder and model consumer perspectives. Estimates for the change in overall value to a large scale program will be estimated to illustrate the degradation in real and perceived value associated with poor modeling practices.
Once a tool and language have been selected, the only factors system modelers can use to shape the outcome of their work are the methods they employ. Methods not only impact the quality of the model but also directly impact the cost to... more
Once a tool and language have been selected, the only factors system modelers can use to shape the outcome of their work are the methods they employ. Methods not only impact the quality of the model but also directly impact the cost to construct and maintain it. Numerous competing methodologies and style guides exist and it is difficult for novice practitioners to identify the most practical approach for any given project. In addition, the negative impacts of modeling decisions may not surface until the model has grown significantly (with associated larger costs to correct these deficiencies). This presentation will explore what makes a system model useful, tidy, and easy to reuse. Validation rules and quality checks will be proposed that can be used to automate some aspects of model curation; principles of model modularity, openness, and data rights will also be discussed.
Research Interests:
A compilation of thoughts about system modeling and engineering (drawn from my other extant work).
Research Interests:
The Department of Defense's Digital Engineering Strategy (adopted in June 2018) has five goals: 1. Formalize the development, integration, and use of models to inform enterprise and program decision making 2. Provide an enduring,... more
The Department of Defense's Digital Engineering Strategy (adopted in June 2018) has five goals: 1. Formalize the development, integration, and use of models to inform enterprise and program decision making 2. Provide an enduring, authoritative source of truth 3. Incorporate technological innovation to improve the engineering practice 4. Establish a supporting infrastructure and environment to perform activities, collaborate, and communicate across stakeholders 5. Transform the culture and workforce to adopt and support digital engineering across the life cycle. 1 For this strategy to succeed, stakeholders must willingly participate in the cultural transformation and use system models as they are intended: as living, dynamic, integrated sources of information that communicate intent with rigor and clarity. Moving from disjointed documents and air-gapped information sources to a single source of truth is important. However, the explosive growth in system complexity is causing a new, unwanted emergent behavior: In an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it. 2 Because stakeholders are becoming overwhelmed with information from multiple sources, effective system modeling cannot solely focus on the creation of competently executed, integrated system models. It must also facilitate the creation of visualizations and derived products that allow stakeholders to efficiently identify and consume relevant information.
Research Interests:
Competent execution of descriptive models in SysML, the system modeling language, facilitates rigor and analysis in support of systems architecture and engineering activities. However, this requires mastery of SysML, the selected... more
Competent execution of descriptive models in SysML, the system modeling language, facilitates rigor and analysis in support of systems architecture and engineering activities. However, this requires mastery of SysML, the selected modeling tool, and the method used. A semester-long course is not long enough to provide students with adequate time and experience to independently construct a high-quality model.
This paper details the content and use of the hypermodel profile, originally released by the author in 2017. It contains an organizational structure, stereotypes, queries, analysis aids, metrics, and quality checks that can be leveraged by students. Use of the profile allows students to focus on the intellectual content of their assignments while modeling in compliance to a provided style guide. It permits them to experience the benefits of automated quality checks, detailed inferential queries, and other modeling aids without having to have the advanced knowledge to construct them independently. This approach also exposes students to the full benefits of a sophisticated model and encourages them to explore and gain deeper insights into their system of interest.
The specifics of the hypermodel profile will be presented, including its organization, content, and customizations. Guidelines for its use will be presented in conjunction with lessons learned from its use at the University of Detroit Mercy in the Master of Science Product Development, Systems Engineering Certificate, and Advanced Electric Vehicle programs.
This paper details the content and use of the hypermodel profile, originally released by the author in 2017. It contains an organizational structure, stereotypes, queries, analysis aids, metrics, and quality checks that can be leveraged by students. Use of the profile allows students to focus on the intellectual content of their assignments while modeling in compliance to a provided style guide. It permits them to experience the benefits of automated quality checks, detailed inferential queries, and other modeling aids without having to have the advanced knowledge to construct them independently. This approach also exposes students to the full benefits of a sophisticated model and encourages them to explore and gain deeper insights into their system of interest.
The specifics of the hypermodel profile will be presented, including its organization, content, and customizations. Guidelines for its use will be presented in conjunction with lessons learned from its use at the University of Detroit Mercy in the Master of Science Product Development, Systems Engineering Certificate, and Advanced Electric Vehicle programs.
Research Interests:
The value of competently-executed system models will continue to increase as digital transformation efforts gain momentum in aerospace, defense, automotive, and other industries. However, for organizations to reap the full value of their... more
The value of competently-executed system models will continue to increase as digital transformation efforts gain momentum in aerospace, defense, automotive, and other industries. However, for organizations to reap the full value of their modeling investment, modelers must create internally consistent models that not only support concept exploration and analysis but also conform to modeling guides, ontologies, and constraints levied by middleware and the need for data interchange.
This presentation will emphasize pragmatic usage of model customization to support decision-making and model queries; it will also demonstrate methods to generate meaningful model metrics and develop validation suites that ensure model quality.
This presentation will emphasize pragmatic usage of model customization to support decision-making and model queries; it will also demonstrate methods to generate meaningful model metrics and develop validation suites that ensure model quality.
Research Interests:
Document-Intensive Systems Engineering (DISE) is inadequate to the task of developing complicated and complex systems. Model-Based Systems Engineering (MBSE) was created to address this gap. System modeling software continues to grow in... more
Document-Intensive Systems Engineering (DISE) is inadequate to the task of developing complicated and complex systems. Model-Based Systems Engineering (MBSE) was created to address this gap. System modeling software continues to grow in power and capability but there is a shortage of individuals capable of using these tools to their fullest potential. This dearth of talent is slowing the transformation of systems engineering to a model-based discipline. A muddle of publications that obscure high-quality content compounds this problem. Every moment spent on a low-value paper or book robs practitioners of growth. This presentation will share a curated collection of heuristics, resources, and techniques aimed at maximizing the return on an individual's investment. Case studies, philosophy, and discussions from antiquity to today will be compiled into an integrated program for personal development. An emphasis will be placed on resources to help students and practitioners to understand the problem at hand, its context, and how to assess it in a systems context.
Research Interests:
Emergent properties must be considered throughout the development of modern, complex systems. Applying remedies after designs are mature is more costly (consider the costs of adding a tuned mass damper to mitigate noise, vibration, and... more
Emergent properties must be considered throughout the development of modern, complex systems. Applying remedies after designs are mature is more costly (consider the costs of adding a tuned mass damper to mitigate noise, vibration, and harshness (NVH) in an automobile vs. changing the architecture to eliminate a noise path). Cybersecurity suffers from a similar problem, in that late application of controls is less robust and more costly than hardening a system by eliminating vulnerabilities in its architecture.
This presentation documents methods to characterize attack surfaces using the Systems Modelling Lanuguage (SysML). In addition to more conventional approaches (such as modeling interfaces for hardware and software attack vector analysis), the authors present a methodology to characterize system vulnerabilities using state machines. These analyses, resident in the integrated system model (ISM) for the system under development, directly support the architecture and systems engineering effort. This ensures that cybersecurity is considered holistically and is embedded into the architecting process.
This presentation also builds upon hypermodeling, the primary author’s integrated modeling approach that seeks to maximize the return on a system modeling effort by focusing on efficiency and effectiveness to maximize the elegance of an integrated system model.
This presentation documents methods to characterize attack surfaces using the Systems Modelling Lanuguage (SysML). In addition to more conventional approaches (such as modeling interfaces for hardware and software attack vector analysis), the authors present a methodology to characterize system vulnerabilities using state machines. These analyses, resident in the integrated system model (ISM) for the system under development, directly support the architecture and systems engineering effort. This ensures that cybersecurity is considered holistically and is embedded into the architecting process.
This presentation also builds upon hypermodeling, the primary author’s integrated modeling approach that seeks to maximize the return on a system modeling effort by focusing on efficiency and effectiveness to maximize the elegance of an integrated system model.
Research Interests:
Boardgames have undergone a Renaissance recently due to improved production values, a better understanding of what makes games "fun," and the development of modern game mechanics. Wargames are also experiencing an upsurge in popularity... more
Boardgames have undergone a Renaissance recently due to improved production values, a better understanding of what makes games "fun," and the development of modern game mechanics. Wargames are also experiencing an upsurge in popularity due to the growth of the card-driven wargame genre which leverages abstraction and customized cards to simulate friction (in the von Clauswitz sense) and imperfect information.
Both types of games also can be used as training aids or to facilitate explorations of policy and doctrine...but their development often still depends on the skill of the designers involved. This presentation will demonstrate the application of systems architecture and modeling techniques to the domain of boardgame and wargame design. It will emphasize state machines and efficient ways to represent game elements, probabilities, and behaviors within an integrated system model.
Both types of games also can be used as training aids or to facilitate explorations of policy and doctrine...but their development often still depends on the skill of the designers involved. This presentation will demonstrate the application of systems architecture and modeling techniques to the domain of boardgame and wargame design. It will emphasize state machines and efficient ways to represent game elements, probabilities, and behaviors within an integrated system model.
Research Interests:
A look back at key development in system modeling since the last No Magic World Symposium in 2017.
Research Interests:
The construction of a descriptive model for a system can be a daunting task; the System Modeling Language (SysML) is generally useful but often needs domain extensions to bring maximum value to a project. Modeling tools are fiendishly... more
The construction of a descriptive model for a system can be a daunting task; the System Modeling Language (SysML) is generally useful but often needs domain extensions to bring maximum value to a project. Modeling tools are fiendishly complex (at least from a novice's perspective) and can be intimidating. Developing a mindset that sees the model as an organic entity and not a disconnected set of diagrams can be difficult. Methods and processes are often proprietary or cluttered with flaws. Successful system modeling requires a seamless fusion of language, tool capability, and method.
This tutorial presents the hypermodeling approach: a pragmatic, direct approach to system architecture and modeling crafted in support of multiple development programs. Hypermodeling is built on several bedrock principles:
Tables and matrices are the primary work products; diagrams are secondary
Capability definition first
Physical architectures that realize the logical architecture
Subordinate the method to what the modeling tool does well
“Don’t rob the computer of its opportunity to help you”: maximizing the use of derived information
Hypermodeling succeeds because the model is structured to facilitate metachain navigation and other structured queries. This approach allows a speed of execution, real-time quality checks, and meaningful maturity metrics.
Example videos and a demonstration model will be shared as part of this presentation; time will also be set aside to allow discussion with the audience.
This tutorial presents the hypermodeling approach: a pragmatic, direct approach to system architecture and modeling crafted in support of multiple development programs. Hypermodeling is built on several bedrock principles:
Tables and matrices are the primary work products; diagrams are secondary
Capability definition first
Physical architectures that realize the logical architecture
Subordinate the method to what the modeling tool does well
“Don’t rob the computer of its opportunity to help you”: maximizing the use of derived information
Hypermodeling succeeds because the model is structured to facilitate metachain navigation and other structured queries. This approach allows a speed of execution, real-time quality checks, and meaningful maturity metrics.
Example videos and a demonstration model will be shared as part of this presentation; time will also be set aside to allow discussion with the audience.
Research Interests:
Document-Intensive Systems Engineering (DISE) is being replacement by Model-Based Systems Engineering (MBSE). Modeling principles, usually using a modeling language such as the System Model Language (SysML), are being applied to ensure... more
Document-Intensive Systems Engineering (DISE) is being replacement by Model-Based Systems Engineering (MBSE). Modeling principles, usually using a modeling language such as the System Model Language (SysML), are being applied to ensure that critical information about a system’s behavior, structure, requirements, and parametrics are woven into a coherent, readily accessible repository of technical truth.
However, these new practices are often limited to large, complex system development efforts. They are equally applicable to non-traditional applications. For example, a set of business processes can be modeled and gaps/inconsistencies may be easily detected. Improved consistency and rigor is an automatic outcome of good modeling practice.
This presentation will focus on ways to harness the power of system modeling to address challenges faced by ESOH professionals, including identification of hazards, risk management, and mitigation planning.
However, these new practices are often limited to large, complex system development efforts. They are equally applicable to non-traditional applications. For example, a set of business processes can be modeled and gaps/inconsistencies may be easily detected. Improved consistency and rigor is an automatic outcome of good modeling practice.
This presentation will focus on ways to harness the power of system modeling to address challenges faced by ESOH professionals, including identification of hazards, risk management, and mitigation planning.
System modeling is difficult to learn without hands-on exercises. The experience of translating real concepts, constraints, and capabilities into modeling elements is the most effective way to develop modeling competence. This paper will... more
System modeling is difficult to learn without hands-on exercises. The experience of translating real concepts, constraints, and capabilities into modeling elements is the most effective way to develop modeling competence. This paper will discuss the first-ever two-term modeling project at the University of Detroit Mercy. Student teams were given the science goals for NASA's Next Mars Orbiter (NeMO) as the foundation of a SysML model that spanned Systems Architecture and Systems Engineering courses. This presentation will discuss the practical aspects of leading multiple student teams as they learn SysML, tool user interfaces, and underlying systems engineering concepts.
On December 31, 2016, a new term was born: "Document Intensive Systems Engineering" (DISE). Since Model-Based Systems Engineering has been practiced with SysML for a decade and the stated goal of the International Council on Systems... more
On December 31, 2016, a new term was born: "Document Intensive Systems Engineering" (DISE). Since Model-Based Systems Engineering has been practiced with SysML for a decade and the stated goal of the International Council on Systems Engineering (INCOSE) is that MBSE will become normal systems engineering practice, Model Based Systems Engineering needs to become an obsolete term. DISE was coined as a term for the traditional approach to systems engineering and should be used as SE comes to mean MBSE.
Interest in SE continues to grow as organizations continue to realize the shortcomings of DISE; however, change is difficult. Culture, mindset, talent shortages, and other factors inhibit the rapid adoption of system modeling. This talk will discuss observations, challenges, opportunities, and a vision for the near and medium-term outlook for system modeling.
Interest in SE continues to grow as organizations continue to realize the shortcomings of DISE; however, change is difficult. Culture, mindset, talent shortages, and other factors inhibit the rapid adoption of system modeling. This talk will discuss observations, challenges, opportunities, and a vision for the near and medium-term outlook for system modeling.
Research Interests:
September 2017 marks the 10th anniversary of the release of SysML 1.0; SysML 1.4 is in daily use and SysML 2.0 is under development. Model Based Systems Engineering (MBSE) is reaching a critical mass as early adopters have shown its... more
September 2017 marks the 10th anniversary of the release of SysML 1.0; SysML 1.4 is in daily use and SysML 2.0 is under development. Model Based Systems Engineering (MBSE) is reaching a critical mass as early adopters have shown its benefits and other practitioners have taken notice. Computing power has dramatically increased and tool vendors have expanded their capabilities. How does that impact those of us practicing system modeling on a daily basis?
This talk will discuss the state of MBSE practice from a practitioner’s perspective…highlighting some of the best (and worst) MBSE “in the wild,” new (or obscure) tool capabilities, what advances are on the immediate horizon, and what challenges are emerging as we enter the second decade of MBSE.
This talk will discuss the state of MBSE practice from a practitioner’s perspective…highlighting some of the best (and worst) MBSE “in the wild,” new (or obscure) tool capabilities, what advances are on the immediate horizon, and what challenges are emerging as we enter the second decade of MBSE.
Research Interests:
Safety and cybersecurity concerns are growing in importance and prominence, driven by increased sophistication of "bad actors," regulatory proliferation, and the increase in autonomous systems. Successful safety and cybersecurity... more
Safety and cybersecurity concerns are growing in importance and prominence, driven by increased sophistication of "bad actors," regulatory proliferation, and the increase in autonomous systems. Successful safety and cybersecurity engineering requires rigorous identification and mitigation of threats, hazards, and associated information. SysML, the systems modeling language, provides a robust mechanism for describe system behavior, structure, requirements, and parametrics. This presentation will focus on connecting safety requirements, hazard analysis, and cybersecurity controls to an emerging system model. End-to-end traceability and reporting will be emphasized, with a focus on derived work products that support safety and cybersecurity engineering. Note: This presentation will use a notional, unclassified example to illustrate its concepts.
Research Interests:
Note: Some of this content was previously presented at the 2016 No Magic World Symposium. System modeling is hard…and without proper guidance and oversight a system model can degenerate into a disjointed collection of artifacts. This... more
Note: Some of this content was previously presented at the 2016 No Magic World Symposium.
System modeling is hard…and without proper guidance and oversight a system model can degenerate into a disjointed collection of artifacts. This discussion will explore lessons learned, overall modeling philosophy, and the culture change and approach for an organization to maximize the benefits from system modeling. It will challenge audience members to reconsider some of their assumptions about systems engineering, the value and role of modeling, and how to maximize the return on their investment of time, resources, and funding. It will also highlight the impact that modeling can have even when undertaken by first-time modelers.
System modeling is hard…and without proper guidance and oversight a system model can degenerate into a disjointed collection of artifacts. This discussion will explore lessons learned, overall modeling philosophy, and the culture change and approach for an organization to maximize the benefits from system modeling. It will challenge audience members to reconsider some of their assumptions about systems engineering, the value and role of modeling, and how to maximize the return on their investment of time, resources, and funding. It will also highlight the impact that modeling can have even when undertaken by first-time modelers.
Research Interests:
SysML is often presented as complicated, difficult to understand, and software-biased. It has also been portrayed as solely a collection of diagrams. Nothing could be farther from the truth; although SysML has a high level of essential... more
SysML is often presented as complicated, difficult to understand, and software-biased. It has also been portrayed as solely a collection of diagrams. Nothing could be farther from the truth; although SysML has a high level of essential complexity (Brooks), the systems it described are
equally complex. This paper draws upon lessons learned from leading a system modeling effort using SysML and establishes parallels to leadership principles from Captain Jack Sparrow (a character in Disney’s Pirates of the Caribbean films). It focuses on the behaviors a successful modeler must embrace to succeed in the current transition between document-based and model-based systems engineering and emphasizes the personal nature of engineering.
equally complex. This paper draws upon lessons learned from leading a system modeling effort using SysML and establishes parallels to leadership principles from Captain Jack Sparrow (a character in Disney’s Pirates of the Caribbean films). It focuses on the behaviors a successful modeler must embrace to succeed in the current transition between document-based and model-based systems engineering and emphasizes the personal nature of engineering.
Research Interests:
While complex systems transform the landscape, the Systems Engineering discipline is also experiencing a transformation to model based discipline. In alignment with this, one of the International Council on Systems Engineering (INCOSE)... more
While complex systems transform the landscape, the Systems Engineering discipline is also experiencing a transformation to model based discipline. In alignment with this, one of the International Council on Systems Engineering (INCOSE) strategic objectives is to accelerate this transformation. INCOSE is building a broad community that promotes and advances model based methods. This model based transformation is necessary to advance the discipline and handle the seamless integration of computational algorithms and physical components across domains and traditional system boundaries. This presentation will cover current INCOSE activities as well as outline identified enablers and roadblocks for implementing transformation and advancing the practice of Model Based Systems Engineering.
We will share the impact MBSE has had on several projects, the efforts of working groups (both international and local), and lessons learned from teaching system modeling, architecture, and engineering in a university setting.
We will share the impact MBSE has had on several projects, the efforts of working groups (both international and local), and lessons learned from teaching system modeling, architecture, and engineering in a university setting.
Research Interests:
Every model element has a cost: creating, defining, connecting, and maintaining a model element is not free. A focus on efficient and economical modeling allows an organization to maximize the return on its investment in modeling tools... more
Every model element has a cost: creating, defining, connecting, and maintaining a model element is not free. A focus on efficient and economical modeling allows an organization to maximize the return on its investment in modeling tools and staff.
This tutorial is intended for intermediate modelers who wish to learn techniques for structuring a SysML model to facilitate the extraction of derived information. Topics will include:
Names are optional, documentation is mandatory
Query-based smart packages
How to use specialization to inherit properties and requirements
Dependency matrices (including implied relationships)
Metachain navigation
Modeling variants
An example model will be provided.
This tutorial is intended for intermediate modelers who wish to learn techniques for structuring a SysML model to facilitate the extraction of derived information. Topics will include:
Names are optional, documentation is mandatory
Query-based smart packages
How to use specialization to inherit properties and requirements
Dependency matrices (including implied relationships)
Metachain navigation
Modeling variants
An example model will be provided.
Research Interests:
System modeling is hard…and without proper guidance and oversight a system model can degenerate into a disjointed collection of artifacts. This discussion will explore lessons learned, overall modeling philosophy, and the culture change... more
System modeling is hard…and without proper guidance and oversight a system model can degenerate into a disjointed collection of artifacts. This discussion will explore lessons learned, overall modeling philosophy, and the culture change and approach for an organization to maximize the benefits from system modeling. It will challenge audience members to reconsider some of their assumptions about systems engineering, the value and role of modeling, and how to maximize the return on their investment of time, resources, and funding. It will also highlight the impact that modeling can have even when undertaken by first-time modelers.
Research Interests:
As Model-Based Systems Engineering (MBSE) continues to evolve, it places new tools and reporting capabilities in the hands of systems engineering practitioners. To succeed, a system modeler needs to understand systems engineering, the... more
As Model-Based Systems Engineering (MBSE) continues to evolve, it places new tools and reporting capabilities in the hands of systems engineering practitioners. To succeed, a system modeler needs to understand systems engineering, the modeling language (typically SysML), and the user interface of the modeling tool. However, even greater success can be achieved if other successful engineering techniques are harnessed.
Taguchi Methods, pioneered by Genichi Taguchi in the 1950s, have been widely used to improve the robustness of engineered systems. One of his techniques, parameter design, focuses on classifying the inputs, outputs, and ideal functions of a system. P-diagrams are typically used to capture this information. However, SysML activity diagrams are particularly well-suited to capturing this content during behavioral analysis.
This presentation will describe techniques that can be used to express traditional p-diagrams in SysML and approaches to harnessing the information to improve system robustness. Particular emphasis will be placed on the use of secondary work products (such as tables) that allow information to be extracted from the system model automatically and in a format useful to SMEs.
Taguchi Methods, pioneered by Genichi Taguchi in the 1950s, have been widely used to improve the robustness of engineered systems. One of his techniques, parameter design, focuses on classifying the inputs, outputs, and ideal functions of a system. P-diagrams are typically used to capture this information. However, SysML activity diagrams are particularly well-suited to capturing this content during behavioral analysis.
This presentation will describe techniques that can be used to express traditional p-diagrams in SysML and approaches to harnessing the information to improve system robustness. Particular emphasis will be placed on the use of secondary work products (such as tables) that allow information to be extracted from the system model automatically and in a format useful to SMEs.
Research Interests:
Traditional functional decomposition relies upon a hierarchical decomposition of functions into a tree of subfunctions. While this method and technique can be useful, the emergence of Model-Based Systems Engineering (MBSE) and SysML... more
Traditional functional decomposition relies upon a hierarchical decomposition of functions into a tree of subfunctions. While this method and technique can be useful, the emergence of Model-Based Systems Engineering (MBSE) and SysML enables the creation of a richer expression of system behavior.
This presentation will describe techniques that can be used to express system behaviors in terms of use cases, activity diagrams, and operations. It will emphasize that even while maintaining solution neutrality, a behavioral representation can be matured with subject matter expert (SME) input. The behavioral model can grow from a single use case to a detailed description, with inputs and outputs clearly defined. Particular emphasis will be placed on the use of secondary work products (such as tables) that allow information to be extracted from the system model automatically and in a format useful to SMEs.
Once the desired behaviors are fully described, they can be efficiently mapped to one or more logical architectural variants by the use of generalizations, allocations, and stereotypes. This mapping can then be compared with the previously defined functional inputs and outputs to ensure that content is appropriately mapped to the connections between logical elements.
This presentation will describe techniques that can be used to express system behaviors in terms of use cases, activity diagrams, and operations. It will emphasize that even while maintaining solution neutrality, a behavioral representation can be matured with subject matter expert (SME) input. The behavioral model can grow from a single use case to a detailed description, with inputs and outputs clearly defined. Particular emphasis will be placed on the use of secondary work products (such as tables) that allow information to be extracted from the system model automatically and in a format useful to SMEs.
Once the desired behaviors are fully described, they can be efficiently mapped to one or more logical architectural variants by the use of generalizations, allocations, and stereotypes. This mapping can then be compared with the previously defined functional inputs and outputs to ensure that content is appropriately mapped to the connections between logical elements.
Research Interests:
The proper framing of problems has a significant impact on the solutions generated to solve them. Studies have shown that individuals presented with alternatives tend to assume that the presented set of solutions is complete; this can... more
The proper framing of problems has a significant impact on the solutions generated to solve them. Studies have shown that individuals presented with alternatives tend to assume that the presented set of solutions is complete; this can lead to groupthink and insufficient exploration of a given problem’s solution space. This issue becomes particularly acute in mature industries such as defense, automotive, and durable goods.
The author believes that associative thinking is a key attribute of innovators and that this skill can be further developed by fostering the formation of heuristics. This presentation will showcase how using SysML to describe the 2015 FIRST Robotics Challenge (Recycle Rush™) helped a high school robotics team to develop its robot. The necessary functions were clearly identified and enabled the team to translate needed capabilities into their design.
The author believes that associative thinking is a key attribute of innovators and that this skill can be further developed by fostering the formation of heuristics. This presentation will showcase how using SysML to describe the 2015 FIRST Robotics Challenge (Recycle Rush™) helped a high school robotics team to develop its robot. The necessary functions were clearly identified and enabled the team to translate needed capabilities into their design.
Research Interests:
Traditional functional decomposition relies upon a hierarchical decomposition of functions into a tree of subfunctions. While this method and technique can be useful, the emergence of Model-Based Systems Engineering (MBSE) and SysML... more
Traditional functional decomposition relies upon a hierarchical decomposition of functions into a tree of subfunctions. While this method and technique can be useful, the emergence of Model-Based Systems Engineering (MBSE) and SysML enables the creation of a richer expression of system behavior.
This presentation will describe techniques that can be used to express system behaviors in terms of use cases, activity diagrams, and operations. It will emphasize that even while maintaining solution neutrality, a behavioral representation can be matured with subject matter expert (SME) input. The behavioral model can grow from a single use case to a detailed description, with inputs and outputs clearly defined. Particular emphasis will be placed on the use of secondary work products (such as tables) that allow information to be extracted from the system model automatically and in a format useful to SMEs.
This presentation will describe techniques that can be used to express system behaviors in terms of use cases, activity diagrams, and operations. It will emphasize that even while maintaining solution neutrality, a behavioral representation can be matured with subject matter expert (SME) input. The behavioral model can grow from a single use case to a detailed description, with inputs and outputs clearly defined. Particular emphasis will be placed on the use of secondary work products (such as tables) that allow information to be extracted from the system model automatically and in a format useful to SMEs.
Research Interests:
TRIZ (the Theory of Inventive Problem Solving) was developed by Genrich Altshuller; it postulates that innovation results from resolving “contradictions” in a system (for example, conflicting objectives or interactions between systems).... more
TRIZ (the Theory of Inventive Problem Solving) was developed by Genrich Altshuller; it postulates that innovation results from resolving “contradictions” in a system (for example, conflicting objectives or interactions between systems). These contradictions (often represented in a matrix form) are resolved by applying one or more of Altshuller’s “40 Principles.” Although Altshuller’s later work expanded TRIZ into ARIZ (the Algorithm for Inventive Problem Solving), it is the author’s experience that simple application of the earlier TRIZ principles is often adequate to solve many engineering problems. The advent of Model Based Systems Engineering and SysML allows systems engineers to rigorously document system structure and behavior; this enables product development teams to apply TRIZ principles without significant incremental effort. This presentation will show how to identify contradictions in the model of a system and the application of TRIZ principles to resolve those contradictions. A subset of the 40 Principles will be illustrated in SysML terms and applied to a simplified case study. Current best practices in Model Based Systems Engineering and Model Based Conceptual Design will be integrated into the demonstration.
Research Interests:
One of the most important roles of the Systems Architect is to establish and maintain a clear vision of each product under development. This vision must meet the expectations of the client or market and should serve as the "true North"... more
One of the most important roles of the Systems Architect is to establish and maintain a clear vision of each product under development. This vision must meet the expectations of the client or market and should serve as the "true North" for the development team. However, it is equally important that this vision encompass and be sensitive to architecturally significant requirements (ASRs) (as proposed by Firesmith et al. in "Method Framework for Engineering System Architectures (MFESA)"). This paper will explore a variety of successes from history that are directly attributable to ruthless adherence to satisfying ASRs and failures due to ignoring or flouting them. The author will share several heuristics intended to helping identify the critical few requirements that will determine the success of a project.
Research Interests:
Effective systems engineering is a key factor in the success of any complex system, whether it is a singular example (like NASA’s Galileo probe) or a mass-produced commodity (like automobiles, military vehicles, or consumer electronics).... more
Effective systems engineering is a key factor in the success of any complex system, whether it is a singular example (like NASA’s Galileo probe) or a mass-produced commodity (like automobiles, military vehicles, or consumer electronics). However, successful systems engineering execution is not only predicated on robust processes but on competent, skilled systems engineers. A capable systems engineer must have a broad range of experience and knowledge as well as significant depth in key areas, including knowledge of systems engineering best practices and methods. The International Council on Systems Engineering recognizes this and requires varying amounts of experience for each of its certification levels, with increased demonstrated depth and breadth required for each higher level of certification. This presentation will cover how to effectively integrate systems engineering into graduate curricula at colleges and universities.
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The ubiquitous .45 automatic (the M1911) was adopted by the United States Army on March 29, 1911. It subsequently became one of the most successful firearms in history; over 2.7 million were made for the government and countless others... more
The ubiquitous .45 automatic (the M1911) was adopted by the United States Army on March
29, 1911. It subsequently became one of the most successful firearms in history; over 2.7 million
were made for the government and countless others have been produced for the civilian market.
In addition designing to this pistol, John Moses Browning developed many other firearms that
have been in production for nearly a century, including the Auto-5 shotgun, the M2 (.50 caliber)
and M1919 (.30 caliber) machine guns, and the Browning Hi-Power. He held 128 patents and
created many innovative architectural features that are still in use today. Browning is one of the most-imitated architects and innovators in firearms history.
This presentation will discuss the principles Browning followed when designing his systems
and how they may be applied to diverse architectures today.
29, 1911. It subsequently became one of the most successful firearms in history; over 2.7 million
were made for the government and countless others have been produced for the civilian market.
In addition designing to this pistol, John Moses Browning developed many other firearms that
have been in production for nearly a century, including the Auto-5 shotgun, the M2 (.50 caliber)
and M1919 (.30 caliber) machine guns, and the Browning Hi-Power. He held 128 patents and
created many innovative architectural features that are still in use today. Browning is one of the most-imitated architects and innovators in firearms history.
This presentation will discuss the principles Browning followed when designing his systems
and how they may be applied to diverse architectures today.
Research Interests:
Research Interests:
This case study explores the radically different approaches taken by Airbus and Boeing as they developed the latest generation of their passenger aircraft. The giant Airbus A380 and the efficient Boeing 787 reflect two fundamentally... more
This case study explores the radically different approaches taken by Airbus and Boeing as they developed the latest generation of their passenger aircraft. The giant Airbus A380 and the efficient Boeing 787 reflect two fundamentally different approaches to air travel and highlight the different cultural climates, corporate structures, and assumptions made by both organizations as they bet billions of dollars and, in some ways, their futures.
The comparison and contrast of these SoS approaches, constraints (e.g., the A380 is profoundly impacted by airport infrastructure), triumphs, and pitfalls of the two aircraft will illustrate fundamental systems architectural and systems engineering principles.
The comparison and contrast of these SoS approaches, constraints (e.g., the A380 is profoundly impacted by airport infrastructure), triumphs, and pitfalls of the two aircraft will illustrate fundamental systems architectural and systems engineering principles.
Research Interests:
Chapter 42: Testing and Quality Engineering
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Presentation to GfSE (INCOSE German Chapter) discussing the SAIC Digital Engineering Validation Tool
Research Interests:
Presentation to GfSE (INCOSE German Chapter) based on a previous presentation at CIDESI.
Research Interests:
This presentation will draw upon the presenter's experiences in transforming systems engineering from a document-intensive to a model-based discipline. Highlights from past presentations, tutorials, and the Systems Architecture Guild... more
This presentation will draw upon the presenter's experiences in transforming systems engineering from a document-intensive to a model-based discipline. Highlights from past presentations, tutorials, and the Systems Architecture Guild YouTube channel will be presented to showcase state-of-the-art MBSE practices. A historical perspective will show how rapidly evolution is occurring and how practitioners must adapt to serve their programs.