+353-1-416-8900REST OF WORLD
+44-20-3973-8888REST OF WORLD
1-917-300-0470EAST COAST U.S
1-800-526-8630U.S. (TOLL FREE)

Systems Engineering in the Fourth Industrial Revolution. Big Data, Novel Technologies, and Modern Systems Engineering. Edition No. 1

  • Book

  • 656 Pages
  • February 2020
  • John Wiley and Sons Ltd
  • ID: 5836613

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

Authors

Ron S. Kenett Robert S. Swarz Avigdor Zonnenshain