| 000 | 10078cam a2200637 i 4500 | ||
|---|---|---|---|
| 001 | on1122695537 | ||
| 003 | OCoLC | ||
| 005 | 20220711203620.0 | ||
| 006 | m o d | ||
| 007 | cr cnu---unuuu | ||
| 008 | 190716s2020 njua ob 001 0 eng | ||
| 010 | _a 2019030438 | ||
| 040 |
_aDLC _beng _erda _epn _cDLC _dOCLCO _dOCLCF _dN$T _dYDX _dDG1 _dUKMGB _dNOC _dSFB _dN9V _dNOC _dOCLCQ |
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_a019711832 _2Uk |
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| 019 | _a1137593325 | ||
| 020 |
_a9781119513940 _q(electronic book) |
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| 020 |
_a1119513944 _q(electronic book) |
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| 020 |
_a9781119513926 _q(electronic publication) |
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| 020 | _a1119513928 | ||
| 020 |
_a9781119513957 _q(electronic bk.) |
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| 020 |
_a1119513952 _q(electronic bk.) |
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| 020 |
_z9781119513896 _q(hardcover) |
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| 020 | _z1119513898 | ||
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| 035 |
_a(OCoLC)1122695537 _z(OCoLC)1137593325 |
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| 037 |
_a9781119513926 _bWiley |
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| 042 | _apcc | ||
| 050 | 0 | 4 |
_aTA168 _b.S8727 2020 |
| 082 | 0 | 0 |
_a620.001/1 _223 |
| 049 | _aMAIN | ||
| 245 | 0 | 0 |
_aSystems engineering in the fourth industrial revolution : _bbig data, novel technologies, and modern systems engineering / _cedited by Ron S. Kenett, Robert S. Swarz, Avigdor Zonnenshain. |
| 250 | _aFirst edition. | ||
| 264 | 1 |
_aHoboken, NJ : _bWiley, _c2020. |
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| 300 | _a1 online resource (xxviii, 622 pages) | ||
| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 504 | _aIncludes bibliographical references and index. | ||
| 520 |
_a"This book addresses the changes in systems engineering (SE) prompted by the current industrial environment. Elements of importance in this environment are the shift towards data collection, availability and use in the design and development of systems and also in the later life-cycle stages of use and retirement. In addition, the book addresses the issues in a system in which the system involves data in its operation, contrasting with earlier approaches in which data and algorithm implementation were less involved in the function of the system. These issues are a significant contrast with typical applications of SE to date, in which systems have been conceived as relatively static and long time lines have been acceptable"-- _cProvided by publisher |
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| 588 | 0 | _aOnline resource; title from digital title page (viewed on January 22, 2020). | |
| 505 | 0 | _aPreface 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 | |
| 650 | 0 |
_aSystems engineering. _95942 |
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| 650 | 7 |
_aSystems engineering. _2fast _0(OCoLC)fst01141455 _95942 |
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| 655 | 4 |
_aElectronic books. _93294 |
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| 700 | 1 |
_aKenett, Ron, _eeditor. _99315 |
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| 700 | 1 |
_aSwarz, Robert S., _eeditor. _99316 |
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| 700 | 1 |
_aZonnenshain, Avigdor, _eeditor. _99317 |
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| 776 | 0 | 8 |
_iPrint version: _tSystems engineering in the fourth industrial revolution. _bFirst edition. _dHoboken, NJ : Wiley, [2020] _z9781119513896 _w(DLC) 2019030437 |
| 856 | 4 | 0 |
_uhttps://doi.org/10.1002/9781119513957 _zWiley Online Library |
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| 994 |
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| 999 |
_c69354 _d69354 |
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