Systems Engineering in the Fourth Industrial Revolution: Big Data, Novel Technologies, and Modern Systems Engineering

An up-to-date guide for using massive amounts of data and novel technologies to design, build, and maintain better systems engineering Systems Engineering in the Fourth Industrial Revolution: Big Data, Novel Technologies, and Modern Systems Engineering 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.  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: Presents new and advanced approaches, methodologies, and tools for designing, testing, deploying, and maintaining advanced complex systems Explores effective evidence-based risk management practices Describes an integrated approach to safety, reliability, and cyber security based on system theory Discusses entrepreneurship as a multidisciplinary system Emphasizes technical merits of systems engineering concepts by providing technical models Written for systems engineers, Systems Engineering in the Fourth Industrial Revolution offers an up-to-date resource that contains the best practices and most recent research on the topic of systems engineering.

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

About the Author :
RON S. KENETT, PHD, is Chairman of the KPA Group, and Senior Research Fellow, Samuel Neaman Institute for National Policy Research, Technion, Israel. ROBERT S. SWARZ, PHD, is Professor of Practice in the Systems Engineering program of Worcester Polytechnic Institute, Massachusetts, USA. AVIGDOR ZONNENSHAIN, PHD, is Senior Research Fellow at The Gordon Center for Systems Engineering and at the Samuel Neaman Institute for National Policy Research Technion, Israel.