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E-grāmata: Decision-Making in High Risk Organizations Under Stress Conditions

(City University of London, UK), (Independent Consultant, San Diegeo, California, USA)
  • Formāts: 190 pages
  • Izdošanas datums: 19-Aug-2016
  • Izdevniecība: CRC Press Inc
  • Valoda: eng
  • ISBN-13: 9781315353753
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Decision-Making in High Risk Organizations Under Stress ConditionsPalielināt
  • Formāts: 190 pages
  • Izdošanas datums: 19-Aug-2016
  • Izdevniecība: CRC Press Inc
  • Valoda: eng
  • ISBN-13: 9781315353753
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This book discusses management decision-making under accident conditions as a vehicle to confirm the importance of clear decision-making guided by a systems approach on how an organization functions related to the role of managers, operators, and the operation of the plant. The book shows how to effectively assess the reliability of an organization particularly those organizations responsible for critical infrastructure. The authors have used Stafford Beers cybernetic model as a basis to model the behavior and reliability of such organizations. A series of case studies are used to draw conclusions not only how training, experience, and education can improve the strategy and response of management to reduce the probability of an economic or social disaster, but also draw attention to the fact that managers need to be made aware of the consequences of their decisions.

Poor management decisions made under stress conditions can lead to the collapse of an organization together with its underlying business, possibly linked to a social disaster with loss of life. Some technology-ignorant management decisions even under non-stress conditions can lead to dangerous situations, which can increase the economic burden placed on an organization. This book describes such situations in order to promote improvement in organizational preparedness by training, experience, and education to reduce safety and economic risks.

This book offers: Case studies of accidents that have affected different HROs (high-risk organizations) and others, due to poor decision-making by management Training methods (advocated by Admiral Hyman Rickover, adopted by military bodies and others) to prepare staff to make critical decisions under difficult conditions and examine their applicability to training managers of high-risk facilities Documentation on how making decisions in difficult situations have psychological constraints related to the degree of preparedness and the tools available to aid the decision maker(s) Studies on the key actions taken before, during, and after accidents and how these management decisions can affect accident propagation, and how one could improve management decision-making by the use of training in decision-making and an understanding of Ross Ashbys Law of Requisite Variety. Simulation techniques to improve training of front-line operators and management Consideration of cost and investment evaluations and how they can distort the selection of tactics and measures that ensure successful operations and avoidance of accidents
Preface xiii
Acknowledgments xvii
Authors xix
Chapter 1 Introduction 1(6)
1.1 Purpose of the Book
1(2)
1.2 Potential Use of the Book
3(1)
1.3 Philosophy of the Authors
4(3)
Chapter 2 Background 7(4)
2.1 Introduction
7(1)
2.2 Applications of Technology
7(3)
2.2.1 Submarines
7(1)
2.2.2 Aircraft Development
8(1)
2.2.3 Computers
9(1)
2.2.4 Instruments
9(1)
2.3 Comments
10(1)
Chapter 3 Cybernetic Organizational Model 11(18)
3.1 Overview
11(1)
3.2 Controller Design and Operation
12(1)
3.3 Controller Response
13(1)
3.4 VSM System
13(1)
3.5 Use of Feedback in VSM
14(1)
3.6 Complexity of Operations
15(1)
3.7 Enhanced VSM Representation
16(2)
3.8 VSM Application to Aircraft Traffic Control Study
18(1)
3.9 ATC in Saudi Air Space
19(1)
3.10 Analysis of the ATM Operation
20(3)
3.11 Human Reliability Assessment
23(1)
3.12 Linking VSM and CAHR
23(3)
3.13 Comments
26(1)
3.14 Summary
27(2)
Chapter 4 Ashby's Law of Requisite Variety and Its Application 29(12)
4.1 Introduction
29(1)
4.2 General Approach to Control of Systems
29(5)
4.3 Impact of Ashby's Law
34(1)
4.4 Examples: Application of Ashby's Law
34(5)
4.4.1 Fermi's Chicago Pile (CP1) Nuclear Experiment and Xenon
35(1)
4.4.2 Effect of Management Decisions on the Fukushima Accident Progression
36(1)
4.4.3 Failure of San Onofre NPP Steam Generators
37(2)
4.5 Methods to Enhance the Probability of Good Decision-Making
39(1)
4.6 Conclusions
39(2)
Chapter 5 Probability Risk Assessment 41(6)
5.1 Introduction to PRA
41(2)
5.2 PRA Structure
43(1)
5.3 Applications of PRA
43(1)
5.4 Summary
44(3)
Chapter 6 Rasmussen's Human Behavior Groups 47(4)
6.1 Introduction to Skill-, Rule-, and Knowledge-Based Behavior
47(2)
6.2 Application of Skill, Rule, Knowledge Behavior Rules
49(1)
6.3 Comments
50(1)
Chapter 7 Case Studies of Accidents for Different Industries 51(52)
7.1 Scope: Analysis of Accidents
51(1)
7.2 Accidents: Analysis Approach
51(2)
7.3 List of Accidents
53(3)
7.4 Nuclear Industry Accidents
56(18)
7.4.1 Three Mile Island Unit #2
56(6)
7.4.1.1 Accident Analysis
57(1)
7.4.1.2 Organizational Analysis
58(1)
7.4.1.3 Review of a VSM Model following TMI Organizational Analysis
59(3)
7.4.2 Chernobyl
62(4)
7.4.2.1 Description of Plant
63(1)
7.4.2.2 Accident Description
63(1)
7.4.2.3 Accident and Organizational Analysis
64(1)
7.4.2.4 Comments on Chernobyl Organization
65(1)
7.4.3 Fukushima Daiichi Accident
66(8)
7.4.3.1 TEPCO and Fukushima Plant Organizations
66(1)
7.4.3.2 Comments on the Preaccident Status
67(1)
7.4.3.3 Accident Description
68(4)
7.4.3.4 TEPCO Daiichi Organization—Prior to Accident
72(1)
7.4.3.5 Reorganized Daiichi during Response to Emergency
73(1)
7.5 Chemical Industries
74(4)
7.5.1 Union Carbide Sevin (Pesticide) Plant, Bhopal, India, 1984
74(4)
7.5.1.1 Introduction
74(1)
7.5.1.2 Accident Analysis
75(2)
7.5.1.3 Organizational Analysis
77(1)
7.6 Oil and Gas Industries
78(7)
7.6.1 Deepwater Horizon/Macondo Blowout Gulf of Mexico Oil Accident
78(7)
7.6.1.1 Introduction
78(1)
7.6.1.2 Accident Description
78(1)
7.6.1.3 Accident Analysis
79(2)
7.6.1.4 Organizational Analysis
81(1)
7.6.1.5 Conclusions
81(3)
7.6.1.6 Organization (VSM) Comments
84(1)
7.6.1.7 Postscript on the Macondo Well Accident
84(1)
7.7 Railways
85(2)
7.7.1 Introduction
85(2)
7.7.1.1 Kings Cross Underground Fire, November 18, 1987
86(1)
7.7.1.2 Organization Analysis
86(1)
7.7.1.3 Comments on Railway Accidents
87(1)
7.8 NASA and Air Transport
87(7)
7.8.1 NASA Challenger Accident, January 28, 1986
87(4)
7.8.1.1 Background
87(1)
7.8.1.2 Description of the Shuttle
88(1)
7.8.1.3 Analysis
88(1)
7,8.1.4 Description of Accident
88(1)
7.8.1.5 Accident Analysis
89(1)
7.8.1.6 Comments
90(1)
7.8.2 Tenerife, Canary Islands Runway Accident, March 1977
91(3)
7.8.2.1 Background
91(1)
7.8.2.2 Accident Location
92(1)
7.8.2.3 Accident: Sequence of Events
92(1)
7.8.2.4 Analysis
93(1)
7.8.2.5 Comments
94(1)
7.9 Ancillary Safety-Related Incidents
94(9)
7.9.1 NPP Containment Sump Blockage
95(1)
7.9.2 Hungarian VVER Fuel Cleaning Accident
96(1)
7.9.3 San Onofre NPP: Replacement Steam Generators
97(2)
7.9.4 Northeast Utilities: Impact of Management Change
99(4)
Chapter 8 Lessons Learned from a Series of Accidents 103(8)
8.1 Introduction
103(1)
8.2 Listing of the Lessons Learned for Each Accident
104(5)
8.2.1 Three Mile Island Unit #2 Accident
104(1)
8.2.2 Chernobyl Accident
104(1)
8.2.3 Fukushima Accident
105(1)
8.2.4 Bhopal Accident
105(1)
8.2.5 BP Oil Refinery Accident
106(1)
8.2.6 Deepwater Horizon/Macondo Oil Release Accident
106(1)
8.2.7 Railways Accidents, Including Subsurface Railways
106(1)
8.2.8 NASA Challenger Accident
107(1)
8.2.9 Tenerife Accident
107(1)
8.2.10 NPP Containment Sump Blockage
108(1)
8.2.11 Fuel Cleaning Accident
108(1)
8.2.12 Replacement of Steam Generators
108(1)
8.2.13 Impact of Management, NU Operations
109(1)
8.3 Summary
109(2)
Chapter 9 Role of Regulation in Industrial Operations 111(8)
9.1 Introduction
111(1)
9.2 Regulation Process
112(1)
9.3 Lessons from Review of NRC Reports
113(4)
9.3.1 Comment on Report
117(1)
9.4 Comments
117(2)
Chapter 10 Integration of Tools Related to Decision-Making 119(12)
10.1 Introduction
119(2)
10.2 Integration and Roles of Each Element
121(10)
10.2.1 Beer's Cybernetic Model
121(1)
10.2.2 Ashby's Law of Requisite Variety
122(1)
10.2.3 Probabilistic Risk Assessment Studies
122(2)
10.2.4 Rasmussen's Human Behavior Types
124(1)
10.2.5 Case Studies of Accident for Different Industries
124(1)
10.2.6 Training Methods and Role of Advisors
125(1)
10.2.6.1 Use of Advisors
125(1)
10.2.7 Simulation of Processes and Its Value
126(1)
10.2.8 Summary
126(18)
10.2.8.1 Organizational Dynamic Model
126(1)
10.2.8.2 Ashby's Law
127(1)
10.2.8.3 Probabilistic Risk Assessment
127(1)
10.2.8.4 Rasmussen's Human Behavioral Models
127(1)
10.2.8.5 Accident Case Studies
128(1)
10.2.8.6 Training Methods
128(1)
10.2.8.7 Simulation Processes
129(2)
Chapter 11 Use of Simulation for Different Operations 131(6)
11.1 Introduction
131(1)
11.2 Simulators
131(2)
11.3 Simulations
133(1)
11.4 Future Uses: Decision-Making
134(1)
11.5 Summary
135(2)
Chapter 12 Training Approaches for Management 137(4)
12.1 Introduction
137(1)
12.2 Education
137(1)
12.3 Technical Tools for Managers
138(1)
12.4 Conclusions
139(2)
Chapter 13 Investment in Safety 141(14)
13.1 Introduction
141(1)
13.2 Managing for Shareholder Value
141(1)
13.3 Brief Overview of the Principles of MSV
142(2)
13.4 Using the J-Value to Estimate the Level of Investment Needed for Safety
144(9)
13.4.1 Formulation of the J-Value
145(3)
13.4.2 Limiting Risk Multiplier
148(2)
13.4.3 Application of the J-Value
150(3)
13.4.3.1 J-Value Analysis
151(2)
13.5 Conclusion
153(2)
Chapter 14 Conclusions and Comments 155(4)
14.1 Introduction
155(1)
14.2 Analytical Elements
156(1)
14.3 Conclusion
156(3)
Appendix: Admiral Rickover's Management Principles 159(4)
References 163(4)
Index 167
Dr. Anthony Spurgin is an independent consultant in the fields of risk assessment, human reliability, and control system design. Dr. David W. Stupples is a Professor in the Department of Mathematics and Engineering at City University, UK.
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