The work is a context-oriented analysis and synthesis of complex engineered systems to ensure continuous and safe operations under conditions of uncertainty. The book is divided in four parts, the first one comprises an overview of the development of systems engineering: starting with basics of Systems Science and Single Systems Engineering, through System of Systems Engineering to Cognitive Systems Engineering. The Cognitive Systems Engineering model was based on the concept of imperfect knowledge acquisition and management. The second part shows the evolutionary character of the dependability concept over the last fifty years. Beginning from simple models based on the classical probability theory, through the concepts of tolerating faults, as well as resilience engineering, we come to the assumptions of Cognitive Dependability Engineering (CDE), based on the concept of continuous smart operation, both under normal and abnormal conditions. The subject of the next part is analysis and synthesis of Cyber-Physical-Social (CPS) Systems. The methodology consists of the following steps: modeling CPS systems' structure, simulating their behavior in changing conditions and in situations of disruptions, and finally assessing the dependability of the entire system based on CDE. The last part of the work answers the question of how to deal with risks in CPS systems in situations of high level of uncertainty. The concept of a Cognitive Digital Twin was introduced to support the process of solving complex problems by experts, and on this basis a framework for cognitive dependability based problemsolving in CPS Systems operating under deep uncertainty was developed. The possibilities and purposefulness of using this framework have been demonstrated with three practical examples of disasters that have happened in the past and have been thoroughly analyzed.
Author(s): Lech Bukowski
Publisher: CRC Press/Science Publishers
Year: 2023
Language: English
Pages: 324
City: Boca Raton
Cover
Title Page
Copyright Page
Dedication
Acknowledgements
Preface
Table of Contents
List of Acronyms and Abbreviations
Glossary
1. Introduction
Part I. Development of Systems Engineering Concepts: From Single Systems Engineering to Cognitive Systems Engineering
2. Basics of Systems Science
2.1 Main Principles of Systems Science – The Systems Approach
2.2 Defining System and its Attributes – The Concept of Cyber-physical Systems
2.3 Concept of Living Systems – The Viable System Model
2.4 References
3. Systems Engineering
3.1 Fundamentals of System Engineering
3.2 The System Engineering Process – The Lifecycle Concept
3.3 References
4. System of Systems Engineering
4.1 Main Principles of Complex Systems Engineering
4.2 System of Systems and Network Organization
4.3 Architecting Engineered System of Systems
4.4 References
5. Cognitive Systems Engineering
5.1 Basics of Cognitive Science and Cognitive Systems
5.2 Cognitive Processes of Knowledge Acquiring in Living Systems
5.3 Processes of Knowledge Acquiring in Engineered Systems
5.4 Defining Cognitive Systems Engineering – Imperfect Knowledge Acquisition and Management Concept
5.5 References
Part II. Concepts of Attribute-oriented Systems Engineering: From Reliability Engineering to Cognitive Dependability Engineering
6. Reliability Engineering: The Concept of Failure-free Operation
6.1 The Emergence and Development of Reliability Engineering
6.2 Mathematical Foundations of Reliability Engineering
6.3 Mathematical Models in Reliability Engineering
6.4 System Reliability Modelling – The Structural Reliability
6.5 References
7. Safety Engineering: The Concept of Effective Protection
7.1 The Origins and Development of the Safety Science – Accident Models
7.2 Safety Engineering Methods and Tools
7.3 References
8. Security Engineering: The Concept of Cyber-security
8.1 The Principles and Concepts of the Security Engineering
8.2 Cyber Security – Principles, Concepts, and Practices
8.3 References
9. Resilience Engineering: The Concept of Process Continuity
9.1 The Emergence and Development of Resilience Science
9.2 Resilience Engineering – Principles, Concepts, and Models
9.3 References
10. Dependability Engineering: The Concept of Fault-tolerant Functioning
10.1 Basic Concepts of Dependable Computing
10.2 Fundamentals of Dependability Engineering
10.3 References
11. Cognitive Dependability Engineering: The Concept of Trustworthy Performance
11.1 Defining Theoretical Assumptions of Scientific Theories
11.2 Specifying Fundamentals of Cognitive Dependability Engineering
11.3 Formalization of the Concept of Cognitive Dependability Engineering
11.4 References
Part III. Modelling and Simulation the Operation of Cyber-Physical-Social Systems in a Risky Environment
12. Methodology of Modelling and Simulation Used for Complex Systems
12.1 Modelling and Simulation of Complex Engineered Systems
12.2 Development and Application of the Modelling and Simulation Process
12.3 References
13. Modelling of Cyber-Physical-Social Systems
13.1 Modelling of Complex Structures
13.2 Process Modelling within Complex Systems
13.3 Modelling Process Continuity Disruptions in Complex Systems
13.4 References
14. Simulation of Cyber-Physical-Social Systems Behaviour in a Risky Environment
14.1 Basic Principles of Complex Systems Simulation
14.2 A Practical Example of Simulating a Complex System Behaviour Under Uncertainty
14.3 References
Part IV. Managing Risks in Cyber-Physical-Social Systems Under Deep Uncertainty
15. Uncertainty-oriented Concepts of Decision-making
15.1 Imperfect Knowledge-based Concept of Risk
15.2 Main Principles of Risk-informed Decision-making Based on Imperfect Knowledge
15.3 Dependability-related Concept of Decision-making
15.4 References
16. Cognitive Dependability Based Problem-solving in Cyber-Physical-Social Systems Operating Under Deep Uncertainty
16.1 Decision-making Under Uncertainty
16.2 Problem-solving Under Uncertainty
16.3 Complex Problem-solving Under Deep Uncertainty – The Concept of Cognitive Digital Twin
16.4 A Framework for Cognitive Dependability Based Problem-solving in Cyber-Physical-Social Systems Operating Under Deep Uncertainty
16.5 References
17. Application Examples: Lesson Learned from the Case Studies
17.1 Case Study I: Collapse of I-35W Highway Bridge Minneapolis, Minnesota, 1 August 2007
17.2 Case Study II: The Three Mile Island Nuclear Accident, 28 March 1979
17.3 Case Study III: Damage from the Great East Japan Earthquake and Tsunami, 11 March 2011
17.4 References
18. Summary and Concluding Considerations
Index
