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Feelings and Physics: Emotional, Psychological, and Other Soft Human Requirements, by Model-Based Systems Engineering 情感与物理：基于模型的系统工程：情感、心理和其他人类软需求
IF 1 4区 工程技术
Insight Pub Date : 2024-10-08 DOI: 10.1002/inst.12507
William D. Schindel
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引用次数: 0
Realizing the Promise of Digital Engineering: Planning, Implementing, and Evolving the Ecosystem 实现数字工程的承诺：规划、实施和发展生态系统
IF 1 4区 工程技术
Insight Pub Date : 2024-10-08 DOI: 10.1002/inst.12505
William D. Schindel
{"title":"Realizing the Promise of Digital Engineering: Planning, Implementing, and Evolving the Ecosystem","authors":"William D. Schindel","doi":"10.1002/inst.12505","DOIUrl":"https://doi.org/10.1002/inst.12505","url":null,"abstract":"<div>\u0000 \u0000 <p>Gaining benefits of digital engineering is not only about implementing digital technologies. An ecosystem for innovation is a system of systems in its own right, only partly engineered, subject to risks and challenges of evolving socio-technical systems. This paper summarizes an aid to planning, analyzing, implementing, and improving innovation ecosystems. Represented as a configurable model-based reference pattern used by collaborating INCOSE working groups, it was initially applied in targeted INCOSE case studies, and subsequently elaborated and applied to diverse commercial and defense ecosystems. Explicating the recurrent theme of consistency management underlying all historical engineering, it is revealing of digital engineering's special promise, and enhances understanding of historical as well as future engineering and life cycle management. It includes preparation of human and technical resources to effectively consume and exploit digital information assets, not just create them, capability enhancements over incremental release trains, and evolutionary steering using feedback and group learning.</p>\u0000 </div>","PeriodicalId":13956,"journal":{"name":"Insight","volume":"27 5","pages":"17-26"},"PeriodicalIF":1.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142404691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Innovation Ecosystem Dynamics, Value and Learning I: What Can Hamilton Tell Us? 创新生态系统动态、价值和学习 I：汉密尔顿能告诉我们什么？
IF 1 4区 工程技术
Insight Pub Date : 2024-10-08 DOI: 10.1002/inst.12504
William D. Schindel
{"title":"Innovation Ecosystem Dynamics, Value and Learning I: What Can Hamilton Tell Us?","authors":"William D. Schindel","doi":"10.1002/inst.12504","DOIUrl":"https://doi.org/10.1002/inst.12504","url":null,"abstract":"<div>\u0000 \u0000 <p>Held in Dublin, Ireland, IS2024 invites us to refresh understanding of contributions to systems engineering by Ireland's greatest mathematician— Sir William Rowan Hamilton (1805–1865), professor of astronomy at Trinity College Dublin and royal astronomer of Ireland. His profound contributions to science, technology, engineering, and math (STEM) deserve greater systems community attention. Supporting theory and practice, they intersect foundations and applications streams of INCOSE's future of systems engineering (FuSE) program. Strikingly, key aspects apply to systems of all types, including socio-technical and information systems. Hamilton abstracted the energy-like generator of dynamics for all systems, while also generalizing momentum. Applied to the INCOSE innovation ecosystem pattern as dynamics of learning, development, and life cycle management, this suggests an architecture for integration of the digital thread and machine learning in innovation enterprises, along with foundations of systems engineering as a dynamical system.</p>\u0000 </div>","PeriodicalId":13956,"journal":{"name":"Insight","volume":"27 5","pages":"9-16"},"PeriodicalIF":1.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142404690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Failure Analysis: Insights from Model-Based Systems Engineering 故障分析：基于模型的系统工程的启示
IF 1 4区 工程技术
Insight Pub Date : 2024-10-08 DOI: 10.1002/inst.12508
William D. Schindel
{"title":"Failure Analysis: Insights from Model-Based Systems Engineering","authors":"William D. Schindel","doi":"10.1002/inst.12508","DOIUrl":"https://doi.org/10.1002/inst.12508","url":null,"abstract":"<div>\u0000 \u0000 <p>Processes for system failure analysis (for example, FMEA) are structured, well-documented, and supported by tools. Nevertheless, we hear complaints that FMEA work feels (1) too labor intensive to encourage engagement, (2) somewhat arbitrary in identifying issues, (3) overly sensitive to the skills and background of the performing team, and (4) not building enough confidence of fully identifying the risks of system failure. In fairness to experts in the process, perhaps such complaints come from those less experienced — but even so, we should care how to describe this process to encourage better technical and experience outcomes. This paper shows how model-based systems engineering (MBSE) answers these challenges by deeper and novel integration with requirements and design. Just as MBSE powered the requirements discovery process past its earlier, more subjective performance, so also can MBSE accelerate understanding and performance of failure risk analysis — as a discipline deeply connected within the systems engineering process.</p>\u0000 </div>","PeriodicalId":13956,"journal":{"name":"Insight","volume":"27 5","pages":"44-49"},"PeriodicalIF":1.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142404694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Innovation, Risk, Agility, and Learning, Viewed as Optimal Control and Estimation 创新、风险、灵活性和学习，视为最优控制和估算
IF 1 4区 工程技术
Insight Pub Date : 2024-08-22 DOI: 10.1002/inst.12500
William D. (Bill) Schindel
{"title":"Innovation, Risk, Agility, and Learning, Viewed as Optimal Control and Estimation","authors":"William D. (Bill) Schindel","doi":"10.1002/inst.12500","DOIUrl":"https://doi.org/10.1002/inst.12500","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper summarizes how a well-understood problem—optimal control and estimation in “noisy” environments—provides a framework to advance understanding of a well-known but less well-mastered problem—system innovation life cycles and management of decision risks and learning. The ISO15288 process framework and its exposition in the IN<i>COSE Systems Engineering Handbook</i> (2015) describe system development and other life cycle processes. Concerns about improving the performance of processes in dynamic, uncertain, and changing environments are partly addressed by “agile” systems engineering approaches. Both are typically described in the procedural language of business processes, so it is not always clear whether the different approaches are fundamentally at odds, or just different sides of the same coin. Describing the target system, its environment, and the life cycle management processes using models of dynamical systems allows us to apply earlier technical tools, such as the theory of optimal control in noisy environments, to emerging innovation methods.</p>\u0000 </div>","PeriodicalId":13956,"journal":{"name":"Insight","volume":"27 4","pages":"33-42"},"PeriodicalIF":1.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
FROM THE EDITOR-IN-CHIEF 主编的话
IF 1 4区 工程技术
Insight Pub Date : 2024-08-22 DOI: 10.1002/inst.12496
William Miller
{"title":"FROM THE EDITOR-IN-CHIEF","authors":"William Miller","doi":"10.1002/inst.12496","DOIUrl":"https://doi.org/10.1002/inst.12496","url":null,"abstract":"","PeriodicalId":13956,"journal":{"name":"Insight","volume":"27 4","pages":"6-7"},"PeriodicalIF":1.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
What Is the Smallest Model of a System? 什么是系统的最小模型？
IF 1 4区 工程技术
Insight Pub Date : 2024-08-22 DOI: 10.1002/inst.12501
William D. Schindel
{"title":"What Is the Smallest Model of a System?","authors":"William D. Schindel","doi":"10.1002/inst.12501","DOIUrl":"https://doi.org/10.1002/inst.12501","url":null,"abstract":"<div>\u0000 \u0000 <p>How we <span>represent</span> systems is fundamental to the history of mathematics, science, and engineering. Model-based engineering methods shift the <span>nature</span> of representation of systems from historical prose forms to explicit data structures more directly comparable to those of science and mathematics. However, using models does not guarantee <span>simpler</span> representation—indeed a typical fear voiced about models is that they may be too complex.</p>\u0000 <p><span>Minimality</span> of system representations is of both theoretical and practical interest. The mathematical and scientific interest is that the size of a system's “minimal representation” is one definition of its complexity. The practical engineering interest is that the size and redundancy of engineering specifications challenge the effectiveness of systems engineering processes. INCOSE thought leaders have asked how systems work can be made 10:1 simpler to attract a 10:1 larger global community of practitioners. And so, we ask: What is the <span>smallest</span> model of a system?</p>\u0000 </div>","PeriodicalId":13956,"journal":{"name":"Insight","volume":"27 4","pages":"43-52"},"PeriodicalIF":1.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Got Phenomena? Science-Based Disciplines for Emerging Systems Challenges 有现象吗？应对新兴系统挑战的科学学科
IF 1 4区 工程技术
Insight Pub Date : 2024-08-22 DOI: 10.1002/inst.12498
Bill Schindel
{"title":"Got Phenomena? Science-Based Disciplines for Emerging Systems Challenges","authors":"Bill Schindel","doi":"10.1002/inst.12498","DOIUrl":"https://doi.org/10.1002/inst.12498","url":null,"abstract":"<div>\u0000 \u0000 <p>Engineering disciplines (civil, mechanical, chemical, electrical) sometimes argue their fields have “real physical phenomena”, “hard science” based laws, and first principles, claiming systems engineering lacks equivalent phenomenological foundation. We argue the opposite, and how replanting systems engineering in model-based systems engineering (MBSE) / pattern-based systems engineering (PBSE) supports emergence of new hard sciences and phenomena-based domain disciplines.</p>\u0000 <p>Supporting this perspective is the system phenomenon, wellspring of engineering opportunities and challenges. Governed by Hamilton's principle, it is a traditional path for derivation of equations of motion or physical laws of so-called “fundamental” physical phenomena of mechanics, electromagnetics, chemistry, and thermodynamics.</p>\u0000 <p>We argue that laws and phenomena of traditional disciplines are less fundamental than the system phenomenon from which they spring. This is a <span>practical</span> reminder of emerging higher disciplines, with phenomena, first principles, and physical laws. Contemporary examples include ground vehicles, aircraft, marine vessels, and biochemical networks; ahead are health care, distribution networks, market systems, ecologies, and the IoT.</p>\u0000 </div>","PeriodicalId":13956,"journal":{"name":"Insight","volume":"27 4","pages":"17-24"},"PeriodicalIF":1.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Maps or Itineraries? A Systems Engineering Insight from Ancient Navigators 地图还是路线？古代航海家对系统工程的启示
IF 1 4区 工程技术
Insight Pub Date : 2024-08-22 DOI: 10.1002/inst.12497
William D. Schindel
{"title":"Maps or Itineraries? A Systems Engineering Insight from Ancient Navigators","authors":"William D. Schindel","doi":"10.1002/inst.12497","DOIUrl":"https://doi.org/10.1002/inst.12497","url":null,"abstract":"<div>\u0000 \u0000 <p>Processes and procedures are the heart of current descriptions of systems engineering. The “vee diagram,” ISO 15288, the INCOSE <i>Systems Engineering Handbook,</i> and enterprise-specific business process models focus attention on process and procedure. However, there is a non-procedural way to view systems engineering. This approach is to describe the configuration space “navigated” by systems engineering, and what is meant by system trajectories in that space, traveled during system life cycles. This sounds abstract because we have lacked explicit maps necessary to describe this configuration space. We understand concrete steps of a procedure, so we focus there. But where do these steps take us? And what does “where” mean in this context? Clues are found in recent discoveries about ancient navigation, as well as later development of mathematics and physics. This paper, part I of a case for stronger model-based systems engineering (MBSE) semantics, focuses on the underlying configuration space inherent to systems.</p>\u0000 </div>","PeriodicalId":13956,"journal":{"name":"Insight","volume":"27 4","pages":"9-16"},"PeriodicalIF":1.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Explicating System Value through First Principles: Re-Uniting Decision Analysis with Systems Engineering 通过第一原理阐释系统价值：将决策分析与系统工程重新结合起来
IF 1 4区 工程技术
Insight Pub Date : 2024-08-22 DOI: 10.1002/inst.12499
Troy Peterson, Bill Schindel
{"title":"Explicating System Value through First Principles: Re-Uniting Decision Analysis with Systems Engineering","authors":"Troy Peterson,&nbsp;Bill Schindel","doi":"10.1002/inst.12499","DOIUrl":"https://doi.org/10.1002/inst.12499","url":null,"abstract":"<div>\u0000 \u0000 <p>System complexity continues to grow, creating many new challenges for engineers and decision makers. To maximize value delivery, “both” systems engineering and decision analysis are essential. The systems engineering profession has had a significant focus on improving systems engineering processes. While process plays an important role, the focus on process was often at the expense of foundational engineering axioms and their contribution to system value. As a consequence, systems engineers were viewed as process developers and managers versus technical leaders with a deep understanding of how system interactions are linked to stakeholder value. With the recent shift toward model-based systems engineering (MBSE), systems engineering is “getting back to basics,” focusing on value delivery via first principles, using established laws of engineering and science. This paper describes how pattern-based systems engineering (PBSE), as outlined within INCOSE's model-based systems engineering (MBSE) initiative, explicates system value through modeling of first principles, re-uniting systems engineering and decision analysis capabilities.</p>\u0000 </div>","PeriodicalId":13956,"journal":{"name":"Insight","volume":"27 4","pages":"25-32"},"PeriodicalIF":1.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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