Kenett R.S., Swarz R.S., Zonnenshain A. (eds.) Systems Engineering in the Fourth Industrial Revolution: Big Data, Novel Technologies, and Modern Systems Engineering

Hoboken: Wiley, 2019. — 656 p. — ISBN: 978-1-119-51389-6.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.List of Contributors
Systems Engineering, Data Analytics, and Systems Thinking. Ron S. Kenett, Robert S. Swarz, and Avigdor ZonnenshainThe Fourth Industrial Revolution
Integrating Reliability Engineering with Systems Engineering
Software Cybernetics
Using Modeling and Simulations
Risk Management
An Integrated Approach to Safety and Security Based on Systems Theory
Applied Systems ThinkingApplied Systems Thinking. Robert Edson
Systems Thinking: An Overview
The System in Systems Thinking
Applied Systems Thinking
Applied Systems Thinking Approach
Problem Definition: Entry Point to Applied Systems Thinking
The System Attribute Framework: The Conceptagon
Soft Systems Methodology
Systemigram
Causal Loop Diagrams
Intervention Points
Approach, Tools, and Methods – Final Thoughts3 The Importance of Context in Advanced Systems Engineering. Adam D. Williams
Introduction to Context for Advanced Systems Engineering
Traditional View(s) of Context in Systems Engineering
Challenges to Traditional View(s) of Context in the Fourth Industrial Revolution
Nontraditional Approaches to Context in Advanced Systems Engineering
Context of Use in Advanced Systems Engineering
An Example of the Context of Use: High Consequence Facility SecurityArchitectural Technical Debt in Embedded Systems. Antonio Martini and Jan Bosch
Technical Debt and Architectural Technical Debt
Methodology
Case Study Companies
Findings: Causes of ATD
Problem Definition: Entry Point to Applied Systems Thinking
Findings: Long-Term Implications of ATD Accumulation
Solutions for ATD Management
Solution: A Systematic Technical Debt Map
Solution: Using Automated Architectural Smells Tools for the Architectural Technical Debt Map
Solution: Can We Calculate if it is Convenient to Refactor Architectural Technical Debt?Relay Race: The Shared Challenge of Systems and Software Engineering. Amir TomerSoftware-Intensive Systems
Engineering of Software-Intensive Systems
Role Allocation and the Relay Race Principles
The Life Cycle of Software-Intensive Systems
Software-Intensive System Decomposition
Functional Analysis: Building a Shared Software-Intensive ArchitectureAppendix
Data-Centric Process Systems Engineering for the Chemical Industry 4.0. Marco S. Reis and Pedro M. Saraiva
The Past 50 Years of Process Systems Engineering
Data-Centric Process Systems Engineering
Challenges in Data-Centric Process Systems EngineeringVirtualization of the Human in the Digital Factory. Daniele Regazzoni and Caterina RizziThe Problem
Enabling Technologies
Digital Human Models
Exemplary ApplicationsThe Dark Side of Using Augmented Reality (AR) Training Systems in Industry. Nirit Gavish
The Variety of Options of AR Systems in Industry
Look Out! The Threats in Using AR Systems for Training Purposes
Threat #1: Physical Fidelity vs. Cognitive Fidelity
Threat #2: The Effect of Feedback
Threat #3: Enhanced Information ChannelsCondition-Based Maintenance via a Targeted Bayesian Network Meta-Model. Aviv Gruber, Shai Yanovski, and Irad Ben-GalBackground to Condition-Based Maintenance and Bayesian Networks
The Targeted Bayesian Network Learning Framework
A Demonstration Case Study 2Reliability-Based Hazard Analysis and Risk Assessment: A Mining Engineering Case Study. H. Sebnem DuzgunData Collection
Hazard AssessmentOPCloud: An OPM Integrated Conceptual-Executable Modeling Environment for Industry 4.0. Dov Dori, Hanan Kohen, Ahmad Jbara, Niva Wengrowicz, Rea Lavi, Natali Levi Soskin, Kfir Bernstein, and Uri Shani
Background and Motivation
What Does MBSE Need to be Agile and Ready for Industry 4.0?
OPCloud:The Industry 4.0-Ready OPM Modeling Framework
Main OPCloud Features
Software Architecture Data Structure
Development Methodology and Software Testing
Model Integrity
Model Complexity Metric and Comprehension 2
Educational Perspectives of OP Cloud Through edXRecent Advances Toward the Industrialization of Metal Additive Manufacturing. Federico Mazzucato, Oliver Avram, Anna Valente, and Emanuele Carpanzano
State of the Art
Metal Additive Manufacturing
Industrialization of Metal AM: Roadmap Setup at the ARM Laboratory
Future WorkAnalytics as an Enabler of Advanced Manufacturing. Ron S. Kenett, Inbal Yahav, and Avigdor ZonnenshainA Literature Review
Analytic Tools in Advanced Manufacturing
Challenges of Big Data and Analytic Tools in Advanced Manufacturing
An Information Quality (InfoQ) Framework for Assessing Advanced ManufacturingAppendix
Hybrid Semiparametric Modeling: A Modular Process Systems Engineering Approach for the Integration of Available Knowledge Sources. Cristiana Rodrigues de Azevedo, Victor Grisales Díaz, Oscar Andrés Prado-Rubio, Mark J.Willis, Véronique Préat, Rui Oliveira, and Moritz von StoschA Hybrid Semiparametric Modeling Framework
ApplicationsSystem Thinking Begins with Human Factors: Challenges for the 4th Industrial Revolution. Avi HarelSystems
Human Factors
Human Factor Challenges Typical of the 3rd Industrial Revolution 387Building More Resilient Cybersecurity Solutions for Infrastructure Systems. Daniel Wagner
1A Heightened State of Vulnerability
The Threat is Real
A Particularly Menacing Piece of Malware
Anatomy of An Attack
The Evolving Landscape
The Growing Threat Posed by Nuclear Facilities
Not Even Close to Ready
Focusing on Cyber Resiliency
Enter DARPA
The Frightening Prospect of “Smart” Cities
Lessons from Petya
Best Practices
A Process Rather than a Product
Building a Better MousetrapClosed-Loop Mission Assurance Based on Flexible Contracts: A Fourth Industrial Revolution Imperative. Azad M. Madni and Michael SieversCurrent MA Approach
Flexible Contract Construct
Closed-Loop MA Approach
POMDP Concept of Operations for Exemplar Problem
An Illustrative ExampleFlexTech: From Rigid to Flexible Human–Systems Integration. Guy A. Boy
Industry 4.0 and Human–Systems Integration 4
HSI Evolution: From Interface to Interaction to Organizational Integration
What Does the Term “System” Mean?
HSI as Function Allocation
The Tangibility Issue in Human-Centered Design
Automation as Function Transfer
From Rigid Automation to Flexible Autonomy
Concluding RemarksTransdisciplinary Engineering Systems. Nel Wognum, John Mo, and Josip StjepandićTransdisciplinary Engineering Projects
Introduction to Transdisciplinary Systems
Transdisciplinary System
Example 1: Online Hearing Aid Service and Service Development
Example 2: License Approach for 3D PrintingEntrepreneurship as a Multidisciplinary Project. Arnon Katz
Introduction to Entrepreneurship
Entrepreneurship as a Project
Approaching Change, Risk, and Uncertainty Systematically
The Need for a Systemic Transdisciplinary Concept – Conclusions of Case Studies and Experience
Assimilating System Concepts in Entrepreneurship Management
Overview of Entrepreneurship ElementsDeveloping and Validating an Industry Competence and Maturity for Advanced Manufacturing Scale. Eitan Adres, Ron S. Kenett, and Avigdor Zonnenshain
Introduction to Industry Competence and Maturity for Advanced Manufacturing
Maturity Levels Toward the Fourth Industrial Revolution
The Dimensions of Industry Maturity for Advanced Manufacturing
Validating the Construct of the Scale
Analysis of Assessments from Companies in Northern Israel
Identifying Strengths and WeaknessesA A Literature Review on Models for Maturity Assessment of Companies and Manufacturing Plants.
A.1General
A.2 CMMI – Capability Maturity Mode Integration
A.3 Models for Assessing Readiness Levels
A.4 Models for Assessing the Digital Maturity of Organizations
A.5 National Models and Standards for Assessing the Readiness of Industry
B The IMAM Questionnaire
Modeling the Evolution of Technologies. Yair Shai
Introduction to Reliability of Technologies
Definitions of Technology
The Birth of New Technologies
Adoption and Dispersion of Technologies
Aging and Obsolescence of Technologies
Reliability of Technologies: A New Field of Research
Quantitative Holistic ModelsAcronyms
Biographical Sketches of Editors