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Systems Engineering in the Fourth Industrial Revolution


Systems Engineering in the Fourth Industrial Revolution

Big Data, Novel Technologies, and Modern Systems Engineering
1. Aufl.

von: Ron S. Kenett, Robert S. Swarz, Avigdor Zonnenshain

117,99 €

Verlag: Wiley
Format: EPUB
Veröffentl.: 06.02.2020
ISBN/EAN: 9781119513926
Sprache: englisch
Anzahl Seiten: 656

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Beschreibungen

<p><b>An up-to-date guide for using massive amounts of data and novel technologies to design, build, and maintain better systems engineering</b></p> <p><i>Systems Engineering in the Fourth Industrial Revolution: Big Data, Novel Technologies, and Modern Systems Engineering</i> offers a guide to the recent changes in systems engineering prompted by the current challenging and innovative industrial environment called the Fourth Industrial Revolution&mdash;INDUSTRY 4.0. This book contains advanced models, innovative practices, and state-of-the-art research findings on systems engineering. The contributors, an international panel of experts on the topic, explore the key elements in systems engineering that have shifted towards data collection and analytics, available and used in the design and development of systems and also in the later life-cycle stages of use and retirement.&nbsp;</p> <p>The contributors address the issues in a system in which the system involves data in its operation, contrasting with earlier approaches in which data, models, and algorithms were less involved in the function of the system. The book covers a wide range of topics including five systems engineering domains: systems engineering and systems thinking; systems software and process engineering; the digital factory; reliability and maintainability modeling and analytics; and organizational aspects of systems engineering. This important resource:</p> <ul> <li>Presents new and advanced approaches, methodologies, and tools for designing, testing, deploying, and maintaining advanced complex systems</li> <li>Explores effective evidence-based risk management practices</li> <li>Describes an integrated approach to safety, reliability, and cyber security based on system theory</li> <li>Discusses entrepreneurship as a multidisciplinary system</li> <li>Emphasizes technical merits of systems engineering concepts by providing technical models</li> </ul> <p>Written for systems engineers, <i>Systems Engineering in the Fourth Industrial Revolution </i>offers an up-to-date resource that contains the best practices and most recent research on the topic of systems engineering.</p>
<p>Preface xvii</p> <p>List of Contributors xxv</p> <p><b>1 Systems Engineering, Data Analytics, and Systems Thinking 1<br /></b><i>Ron S. Kenett, Robert S. Swarz, and Avigdor Zonnenshain</i></p> <p>1.1 Introduction 2</p> <p>1.2 The Fourth Industrial Revolution 4</p> <p>1.3 Integrating Reliability Engineering with Systems Engineering 6</p> <p>1.4 Software Cybernetics 7</p> <p>1.5 Using Modeling and Simulations 8</p> <p>1.6 Risk Management 11</p> <p>1.7 An Integrated Approach to Safety and Security Based on Systems Theory 13</p> <p>1.8 Applied Systems Thinking 15</p> <p>1.9 Summary 17</p> <p>References 18</p> <p><b>2 Applied Systems Thinking 21<br /></b><i>Robert Edson</i></p> <p>2.1 Systems Thinking: An Overview 22</p> <p>2.2 The System in Systems Thinking 24</p> <p>2.3 Applied Systems Thinking 25</p> <p>2.4 Applied Systems Thinking Approach 26</p> <p>2.5 Problem Definition: Entry Point to Applied Systems Thinking 27</p> <p>2.6 The System Attribute Framework: The Conceptagon 29</p> <p>2.7 Soft Systems Methodology 36</p> <p>2.8 Systemigram 37</p> <p>2.9 Causal Loop Diagrams 39</p> <p>2.10 Intervention Points 40</p> <p>2.11 Approach, Tools, and Methods &ndash; Final Thoughts 41</p> <p>2.12 Summary 41</p> <p>References 42</p> <p><b>3 The Importance of Context in Advanced Systems Engineering 45<br /></b><i>Adam D. Williams</i></p> <p>3.1 Introduction to Context for Advanced Systems Engineering 45</p> <p>3.2 Traditional View(s) of Context in Systems Engineering 47</p> <p>3.3 Challenges to Traditional View(s) of Context in the Fourth Industrial Revolution 48</p> <p>3.4 Nontraditional Approaches to Context in Advanced Systems Engineering 51</p> <p>3.5 <i>Context of Use</i> in Advanced Systems Engineering 60</p> <p>3.6 An Example of the Context of Use: High Consequence Facility Security 63</p> <p>3.7 Summary 70</p> <p>References 72</p> <p><b>4 Architectural Technical Debt in Embedded Systems 77<br /></b><i>Antonio Martini and Jan Bosch</i></p> <p>4.1 Technical Debt and Architectural Technical Debt 78</p> <p>4.2 Methodology 80</p> <p>4.3 Case Study Companies 81</p> <p>4.4 Findings: Causes of ATD 82</p> <p>4.5 Problem Definition: Entry Point to Applied Systems Thinking 85</p> <p>4.6 Findings: Long-Term Implications of ATD Accumulation 91</p> <p>4.7 Solutions for ATD Management 91</p> <p>4.8 Solution: A Systematic Technical Debt Map 92</p> <p>4.9 Solution: Using Automated Architectural Smells Tools for the Architectural Technical Debt Map 96</p> <p>4.10 Solution: Can We Calculate if it is Convenient to Refactor Architectural Technical Debt? 97</p> <p>4.11 Summary 100</p> <p>References 101</p> <p><b>5 Relay Race: The Shared Challenge of Systems and Software Engineering 105<br /></b><i>Amir Tomer</i></p> <p>5.1 Introduction 105</p> <p>5.2 Software-Intensive Systems 107</p> <p>5.3 Engineering of Software-Intensive Systems 109</p> <p>5.4 Role Allocation and the Relay Race Principles 110</p> <p>5.5 The Life Cycle of Software-Intensive Systems 110</p> <p>5.6 Software-Intensive System Decomposition 114</p> <p>5.7 Functional Analysis: Building a Shared Software-Intensive Architecture 120</p> <p>5.8 Summary 127</p> <p>References 131</p> <p>5.A Appendix 132</p> <p><b>6 Data-Centric Process Systems Engineering for the Chemical Industry 4.0 137<br /></b><i>Marco S. Reis and Pedro M. Saraiva</i></p> <p>6.1 The Past 50 Years of Process Systems Engineering 138</p> <p>6.2 Data-Centric Process Systems Engineering 141</p> <p>6.3 Challenges in Data-Centric Process Systems Engineering 149</p> <p>6.4 Summary 152</p> <p>References 154</p> <p><b>7 Virtualization of the Human in the Digital Factory 161<br /></b><i>Daniele Regazzoni and Caterina Rizzi</i></p> <p>7.1 Introduction 162</p> <p>7.2 The Problem 163</p> <p>7.3 Enabling Technologies 165</p> <p>7.4 Digital Human Models 168</p> <p>7.5 Exemplary Applications 173</p> <p>7.6 Summary 183</p> <p>References 1 85</p> <p><b>8 The Dark Side of Using Augmented Reality (AR) Training Systems in Industry 191<br /></b><i>Nirit Gavish</i></p> <p>8.1 The Variety of Options of AR Systems in Industry 191</p> <p>8.2 Look Out! The Threats in Using AR Systems for Training Purposes 192</p> <p>8.3 Threat #1: Physical Fidelity vs. Cognitive Fidelity 193</p> <p>8.4 Threat #2: The Effect of Feedback 194</p> <p>8.5 Threat #3: Enhanced Information Channels 195</p> <p>8.6 Summary 196</p> <p>References 197</p> <p><b>9 Condition-Based Maintenance via a Targeted Bayesian Network Meta-Model 203<br /></b><i>Aviv Gruber, Shai Yanovski, and Irad Ben-Gal</i></p> <p>9.1 Introduction 203</p> <p>9.2 Background to Condition-Based Maintenance and Bayesian Networks 206</p> <p>9.3 The Targeted Bayesian Network Learning Framework 212</p> <p>9.4 A Demonstration Case Study 213</p> <p>9.5 Summary 221</p> <p>References 224</p> <p><b>10 Reliability-Based Hazard Analysis and Risk Assessment: A Mining Engineering Case Study 227<br /></b><i>H. Sebnem Duzgun</i></p> <p>10.1 Introduction 227</p> <p>10.2 Data Collection 229</p> <p>10.3 Hazard Assessment 231</p> <p>10.4 Summary 237</p> <p>References 239</p> <p><b>11 OPCloud: An OPM Integrated Conceptual-Executable Modeling Environment for Industry 4.0 243<br /></b><i>Dov Dori, Hanan Kohen, Ahmad Jbara, Niva Wengrowicz, Rea Lavi, Natali Levi Soskin, Kfir Bernstein,</i> <i>and Uri Shani</i></p> <p>11.1 Background and Motivation 244</p> <p>11.2 What Does MBSE Need to be Agile and Ready for Industry 4.0? 248</p> <p>11.3 OPCloud:The Industry 4.0-Ready OPM Modeling Framework 249</p> <p>11.4 Main OPCloud Features 252</p> <p>11.5 Software Architecture Data Structure 260</p> <p>11.6 Development Methodology and Software Testing 262</p> <p>11.7 Model Integrity 263</p> <p>11.8 Model Complexity Metric and Comprehension 264</p> <p>11.9 Educational Perspectives of OPCloud Through edX 266</p> <p>11.10 Summary 267</p> <p>References 268</p> <p><b>12 Recent Advances Toward the Industrialization of Metal Additive Manufacturing 273<br /></b><i>Federico Mazzucato, Oliver Avram, Anna Valente, and Emanuele Carpanzano</i></p> <p>12.1 State of the Art 274</p> <p>12.2 Metal Additive Manufacturing 279</p> <p>12.3 Industrialization of Metal AM: Roadmap Setup at the ARM Laboratory 287</p> <p>12.4 Future Work 314</p> <p>12.5 Summary 315</p> <p>References 316</p> <p><b>13 Analytics as an Enabler of Advanced Manufacturing 321<br /></b><i>Ron S. Kenett, Inbal Yahav, and Avigdor Zonnenshain</i></p> <p>13.1 Introduction 322</p> <p>13.2 A Literature Review 323</p> <p>13.3 Analytic Tools in Advanced Manufacturing 326</p> <p>13.4 Challenges of Big Data and Analytic Tools in Advanced Manufacturing 330</p> <p>13.5 An Information Quality (InfoQ) Framework for Assessing Advanced Manufacturing 333</p> <p>13.6 Summary 335</p> <p>References 336</p> <p>13.A Appendix 340</p> <p><b>14 Hybrid Semiparametric Modeling: A Modular Process Systems Engineering Approach for the Integration of Available Knowledge Sources 345<br /></b><i>Cristiana Rodrigues de Azevedo, Victor Grisales D&iacute;az, Oscar Andr&eacute;s Prado-Rubio, Mark J.Willis, &nbsp;V&eacute;ronique Pr&eacute;at, Rui Oliveira, and Moritz von Stosch</i></p> <p>14.1 Introduction 346</p> <p>14.2 A Hybrid Semiparametric Modeling Framework 348</p> <p>14.3 Applications 352</p> <p>14.4 Summary 365</p> <p>Acknowledgments 367</p> <p>References 367</p> <p><b>15 System Thinking Begins with Human Factors: Challenges for the 4th Industrial Revolution 375<br /></b><i>Avi Harel</i></p> <p>15.1 Introduction 376</p> <p>15.2 Systems 378</p> <p>15.3 Human Factors 380</p> <p>15.4 Human Factor Challenges Typical of the 3rd Industrial Revolution 387</p> <p>15.5 Summary 408</p> <p>References 409</p> <p><b>16 Building More Resilient Cybersecurity Solutions for Infrastructure Systems 415<br /></b><i>Danie l Wagner</i></p> <p>16.1 A Heightened State of Vulnerability 415</p> <p>16.2 The Threat is Real 416</p> <p>16.3 A Particularly Menacing Piece of Malware 421</p> <p>16.4 Anatomy of An Attack 422</p> <p>16.5 The Evolving Landscape 424</p> <p>16.6 The Growing Threat Posed by Nuclear Facilities 425</p> <p>16.7 Not Even Close to Ready 426</p> <p>16.8 Focusing on Cyber Resiliency 428</p> <p>16.9 Enter DARPA 430</p> <p>16.10 The Frightening Prospect of &ldquo;Smart&rdquo; Cities 431</p> <p>16.11 Lessons from Petya 434</p> <p>16.12 Best Practices 436</p> <p>16.13 A Process Rather than a Product 437</p> <p>16.14 Building a Better Mousetrap 439</p> <p>16.15 Summary 440</p> <p>References 441</p> <p><b>17 Closed-Loop Mission Assurance Based on Flexible Contracts: A Fourth Industrial Revolution Imperative 445<br /></b><i>Azad M. Madni and Michael Sievers</i></p> <p>17.1 Introduction 446</p> <p>17.2 Current MA Approach 447</p> <p>17.3 Flexible Contract Construct 449</p> <p>17.4 Closed-Loop MA Approach 453</p> <p>17.5 POMDP Concept of Operations for Exemplar Problem 454</p> <p>17.6 An Illustrative Example 457</p> <p>17.7 Summary 461</p> <p>Acknowledgments 462</p> <p>References 462</p> <p><b>18 FlexTech: From Rigid to Flexible Human&ndash;Systems Integration 465<br /></b><i>Guy A. Boy</i></p> <p>18.1 Industry 4.0 and Human&ndash;Systems Integration 466</p> <p>18.2 HSI Evolution: From Interface to Interaction to Organizational Integration 468</p> <p>18.3 What Does the Term &ldquo;System&rdquo; Mean? 470</p> <p>18.4 HSI as Function Allocation 472</p> <p>18.5 The Tangibility Issue in Human-Centered Design 473</p> <p>18.6 Automation as Function Transfer 475</p> <p>18.7 From Rigid Automation to Flexible Autonomy 477</p> <p>18.8 Concluding Remarks 478</p> <p>18.9 Summary 479</p> <p>References 480</p> <p><b>19 Transdisciplinary Engineering Systems 483<br /></b><i>Nel Wognum, John Mo, and Josip Stjepandi</i><i>ć</i></p> <p>19.1 Introduction 483</p> <p>19.2 Transdisciplinary Engineering Projects 486</p> <p>19.3 Introduction to Transdisciplinary Systems 493</p> <p>19.4 Transdisciplinary System 495</p> <p>19.5 Example 1: Online Hearing Aid Service and Service Development 498</p> <p>19.6 Example 2: License Approach for 3D Printing 502</p> <p>19.7 Summary 506</p> <p>References 507</p> <p><b>20 Entrepreneurship as a Multidisciplinary Project 511<br /></b><i>Arnon Katz</i></p> <p>20.1 Introduction to Entrepreneurship 511</p> <p>20.2 Entrepreneurship as a Project 513</p> <p>20.3 Approaching Change, Risk, and Uncertainty Systematically 516</p> <p>20.4 The Need for a Systemic Transdisciplinary Concept &ndash; Conclusions of Case Studies and Experience 518</p> <p>20.5 Assimilating System Concepts in Entrepreneurship Management 523</p> <p>20.6 Overview of Entrepreneurship Elements 531</p> <p>20.7 Summary 534</p> <p>References 535</p> <p><b>21 Developing and Validating an Industry Competence and Maturity for Advanced Manufacturing Scale 537<br /></b><i>Eitan Adres, Ron S. Kenett, and Avigdor Zonnenshain</i></p> <p>21.1 Introduction to Industry Competence and Maturity for Advanced Manufacturing 538</p> <p>21.2 Maturity Levels Toward the Fourth Industrial Revolution 538</p> <p>21.3 The Dimensions of Industry Maturity for Advanced Manufacturing 540</p> <p>21.4 Validating the Construct of the Scale 541</p> <p>21.5 Analysis of Assessments from Companies in Northern Israel 544</p> <p>21.6 Identifying Strengths and Weaknesses 547</p> <p>21.7 Summary 548</p> <p>Acknowledgments 551</p> <p>References 551</p> <p><b>21.A A Literature Review on Models for Maturity Assessment of Companies and Manufacturing Plants 553</b></p> <p>21.A.1 General 553</p> <p>21.A.2 CMMI &ndash; Capability Maturity Mode Integration 553</p> <p>21.A.3 Models for Assessing Readiness Levels 554</p> <p>21.A.4 Models for Assessing the Digital Maturity of Organizations 555</p> <p>21.A.5 National Models and Standards for Assessing the Readiness of Industry 556</p> <p>21.B The IMAM Questionnaire 557</p> <p><b>22 Modeling the Evolution of Technologies 563<br /></b><i>Yair Shai</i></p> <p>22.1 Introduction to Reliability of Technologies 564</p> <p>22.2 Definitions of Technology 566</p> <p>22.3 The Birth of New Technologies 567</p> <p>22.4 Adoption and Dispersion of Technologies 574</p> <p>22.5 Aging and Obsolescence of Technologies 580</p> <p>22.6 Reliability of Technologies: A New Field of Research 582</p> <p>22.7 Quantitative Holistic Models 585</p> <p>22.8 Summary 595</p> <p>References 598</p> <p>Acronyms 603</p> <p>Biographical Sketches of Editors 609</p> <p>Index 611</p>
<p><b>RON S. KENETT</b>, <b>P<small>H</small>D</b>, is Chairman of the KPA Group, and Senior Research Fellow, Samuel Neaman Institute for National Policy Research, Technion, Israel. <p><b>ROBERT S. SWARZ, P<small>H</small>D,</b> is Professor of Practice in the Systems Engineering program of Worcester Polytechnic Institute, Massachusetts, USA. <p><b>AVIGDOR ZONNENSHAIN</b>, <b>P<small>H</small>D</b>, is Senior Research Fellow at The Gordon Center for Systems Engineering and at the Samuel Neaman Institute for National Policy Research Technion, Israel.
<p><b>AN UP-TO-DATE GUIDE FOR USING MASSIVE AMOUNTS OF DATA AND NOVEL TECHNOLOGIES TO DESIGN, BUILD, AND MAINTAIN BETTER SYSTEMS</b> <p><i>Systems Engineering in the Fourth Industrial Revolution: Big Data, Novel Technologies, and Modern Systems Engineering</i> offers a guide to the recent changes in systems engineering prompted by the current challenging and innovative industrial environment called the Fourth Industrial Revolution—INDUSTRY 4.0. This book contains advanced models, innovative practices, and state-of-the-art research findings on systems engineering. The contributors, an international panel of experts on the topic, explore the key elements in systems engineering that have shifted towards data collection and analytics, available and used in the design and development of systems and also in the later life-cycle stages of use and retirement. <p>The contributors address the issues in a system in which the system involves data in its operation, contrasting with earlier approaches in which data, models, and algorithms were less involved in the function of the system. The book covers a wide range of topics including five systems engineering domains: systems engineering and systems thinking; systems software and process engineering; the digital factory; reliability and maintainability modeling and analytics; and organizational aspects of systems engineering. This important resource: <ul> <li>Presents new and advanced approaches, methodologies, and tools for designing, testing, deploying, and maintaining advanced complex systems</li> <li>Explores effective evidence-based risk management practices</li> <li>Describes an integrated approach to safety, reliability, and cyber security based on system theory</li> <li>Discusses entrepreneurship as a multidisciplinary system</li> <li>Emphasizes technical merits of systems engineering concepts by providing technical models</li> </ul> <p>Written for systems engineers, <i>Systems Engineering in the Fourth Industrial Revolution</i> offers an up-to-date resource that contains the best practices and most recent research on the topic of systems engineering.

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