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Forensic Systems Engineering

Evaluating Operations by Discovery

Stimson, William A.

Wiley Series in Systems Engineering and Management

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1. Auflage März 2018
368 Seiten, Hardcover
Wiley & Sons Ltd

ISBN: 978-1-119-42275-4
John Wiley & Sons

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A systems-level approach to reducing liability through process improvement

Forensic Systems Analysis: Evaluating Operations by Discovery presents a systematic framework for uncovering and resolving problematic process failures. Carefully building the causal relationship from process to product, the discussion lays out in significant detail the appropriate and tactical approaches necessary to the pursuit of litigation with respect to corporate operations.

Systemic process failures are addressed by flipping process improvement models to study both improvement and failure, resulting in arguments and methodologies relevant to any product or service industry. Guidance on risk analysis of operations combines evaluation of process control, stability, capability, verification, validation, specification, product reliability, serial dependence, and more, providing a robust framework with which to target large-scale nonconforming products and services.

Relevant to anyone involved in business, manufacturing, service, and control, this book:
* Covers process liability and operations management from both engineering and legal perspectives
* Offers analyses that present novel uses of traditional engineering methods concerning risk and product quality and reliability
* Takes a rigorous approach to system tactics and constraints related to product and service operations and identifies dysfunctional processes
* Offers both prescriptive and descriptive solutions to both the plaintiff and the defendant

The global economy has created an environment in which huge production volume, complex data bases, and multiple dispersed suppliers greatly challenge industrial operations. This informative guide provides a practical blueprint for uncovering problematic process failures.

Preface xix

1 What Is Forensic Systems Engineering? 1

1.1 Systems and Systems Engineering 1

1.2 Forensic Systems Engineering 2

References 4

2 Contracts, Specifications, and Standards 7

2.1 General 7

2.2 The Contract 9

2.2.1 Considerations 9

2.2.2 Contract Review 10

2.3 Specifications 12

2.4 Standards 14

Credits 16

References 16

3 Management Systems 17

3.1 Management Standards 18

3.1.1 Operations and Good Business Practices 18

3.1.2 Attributes of Management Standards 18

3.2 Effective Management Systems 19

3.2.1 Malcolm Baldrige 19

3.2.2 Total Quality Management 20

3.2.3 Six Sigma 20

3.2.4 Lean 21

3.2.5 Production Part Approval Process 22

3.3 Performance and Performance 23

3.4 Addendum 23

Credits 24

References 24

4 Performance Management: ISO 9001 25

4.1 Background of ISO 9000 26

4.1.1 ISO 9001 in the United States 27

4.1.2 Structure of ISO 9000: 2005 27

4.1.3 The Process Approach 28

4.2 Form and Substance 32

4.2.1 Reference Performance Standards 33

4.2.2 Forensics and the Paper Trail 34

Credits 35

References 35

5 The Materiality of Operations 37

5.1 Rationale for Financial Metrics 38

5.1.1 Sarbanes-Oxley 38

5.1.1.1 Title III: Corporate Responsibility 38

5.1.1.2 Title IV: Enhanced Financial Disclosures 39

5.1.2 Internal Control 39

5.1.3 The Materiality of Quality 41

5.2 Mapping Operations to Finance 41

5.2.1 The Liability of Quality 43

5.2.2 The Forensic View 44

Credits 44

References 44

6 Process Liability 47

6.1 Theory of Process Liability 48

6.1.1 Operations and Process Liability 50

6.1.2 Process Liability and Misfeasance 51

6.2 Process Liability and the Law 52

Credits 52

References 52

7 Forensic Analysis of Process Liability 55

7.1 Improper Manufacturing Operations 57

7.1.1 Verification and Validation 57

7.1.1.1 Nonstandard Design Procedures 57

7.1.1.2 Unverified or Unvalidated Design 58

7.1.1.3 Tests Waived by Management 58

7.1.1.4 Altered Test Procedures and Results 58

7.1.2 Resource Management 59

7.1.2.1 Unmonitored Outsourcing 59

7.1.2.2 Substandard Purchased Parts 60

7.1.2.3 Ghost Inventory 60

7.1.2.4 Ineffective Flow Down 61

7.1.3 Process Management 61

7.1.3.1 Forced Production 61

7.1.3.2 Abuse and Threats by Management 62

7.2 Management Responsibility 62

7.2.1 Effective Internal Controls 62

7.2.2 Business Standards of Care 63

7.2.3 Liability Risk Management 64

7.2.4 Employee Empowerment 65

7.2.5 Effective Management Review 65

7.2.6 Closed?]Loop Processes 66

References 67

8 Legal Trends to Process Liability 71

8.1 An Idea Whose Time Has Come 71

8.2 Some Court Actions Thus Far 72

8.2.1 QMS Certified Organizations 73

8.2.2 QMS Noncertified Organizations 74

References 75

9 Process Stability and Capability 77

9.1 Process Stability 77

9.1.1 Stability and Stationarity 78

9.1.2 Stability Conditions 79

9.1.3 Stable Processes 80

9.1.4 Measuring Process Stability 82

9.2 Process Capability 83

9.2.1 Measuring Capability 83

9.2.2 A Limit of Process Capability 85

9.3 The Rare Event 85

9.3.1 Instability and the Rare Event 85

9.3.2 Identifying the Rare Event 86

9.4 Attribute Testing 87

References 88

10 Forensic Issues in Product Reliability 91

10.1 Background in Product Reliability 91

10.2 Legal Issues in the Design of Reliability 94

10.2.1 Good Design Practices 95

10.2.2 Design Is Intrinsic to Manufacturing and Service 95

10.2.3 Intended Use 95

10.2.4 Paper Trail of Evidence 96

10.2.5 Reliability Is an Implied Design Requirement 97

10.3 Legal Issues in Measuring Reliability 97

10.3.1 Failure Modes 97

10.3.2 Estimation of MTTF 98

10.3.3 The More Failure Data the Better 99

10.3.4 The Paper Trail of Reliability Measurement 99

10.4 Legal Issues in Testing for Reliability 100

10.4.1 Defined and Documented Life Test Procedures 100

10.4.2 Life Test Records and Reports 101

10.4.3 Test Procedures 101

10.5 When Product Reliability Is not in the Contract 102

10.5.1 Product Liability 102

10.5.2 ISO 9001 and FAR 103

10.6 Warranty and Reliability 104

References 105

11 Forensic View of Internal Control 107

11.1 Internal Controls 108

11.1.1 Purpose of Control 108

11.1.2 Control Defined 109

11.1.3 Control Elements in Operations 109

11.2 Control Stability 110

11.2.1 Model of a Continuous System 111

11.2.2 Transfer Functions 112

11.3 Implementing Controls 115

11.4 Control of Operations 117

11.4.1 Proportional (Gain) Control 118

11.4.2 Controlling the Effect of Change 119

11.4.2.1 Integral Control 120

11.4.2.2 Derivative (Rate) Control 121

11.4.3 Responsibility, Authority, and Accountability 121

References 123

12 Case Study: Madelena Airframes Corporation 125

12.1 Background of the Case 126

12.2 Problem Description 127

12.2.1 MAC Policies and Procedures (Missile Production) 127

12.2.2 Missile Test 127

12.3 Examining the Evidence 128

12.3.1 Evidence: The Players 129

12.3.2 Evidence: E?]mails 129

12.4 Depositions 132

12.4.1 Deposition of the General Manager 132

12.4.2 Deposition of the Senior Test Engineer 132

12.4.3 Deposition of the Production Manager 132

12.4.4 Deposition of the Chief Design Engineer 133

12.4.5 Deposition of the Test Programs Manager 133

12.5 Problem Analysis 133

12.5.1 Review of the Evidence 133

12.5.2 Nonconformities 134

12.5.2.1 Clause 7.3.1(b) Design and Development Planning 134

12.5.2.2 Clause 7.3.5 Design and Development Verification 135

12.5.2.3 Clause 7.3.6 Design and Development Validation 135

12.5.2.4 Clause 8.1 General Test Requirements 135

12.5.2.5 Clause 8.2.4 Monitoring and Measurement of Product 135

12.5.2.6 Clause 4.1 General QMS Requirements 135

12.5.2.7 Clause 5.6.1 General Management Review

Requirements 135

12.6 Arriving at the Truth 136

12.7 Damages 137

12.7.1 Synthesis of Damages 137

12.7.2 Costs of Correction 137

References 138

13 Examining Serially Dependent Processes 139

13.1 Serial Dependence: Causal Correlation 140

13.2 Properties of Serial Dependence 142

13.2.1 Work Station Definition 142

13.2.2 Assumptions 142

13.2.2.1 Assumption 1 143

13.2.2.2 Assumption 2 143

13.2.2.3 Assumption 3 143

13.2.3 Development of the Conditional Distribution 144

13.2.4 Process Stability 145

13.3 Serial Dependence: Noncausal Correlation 147

13.4 Forensic Systems Analysis 147

Credits 148

References 148

14 Measuring Operations 149

14.1 ISO 9000 as Internal Controls 151

14.2 QMS Characteristics 152

14.3 The QMS Forensic Model 154

14.3.1 Estimating Control Risk 155

14.3.2 Cost of Liability 156

14.4 The Forensic Lab and Operations 157

14.5 Conclusions 158

Credits 159

References 159

15 Stability Analysis of Dysfunctional Processes 161

15.1 Special Terms 162

15.1.1 Dysfunction 162

15.1.2 Common and Special Causes 163

15.1.3 Disturbances and Interventions 163

15.1.4 Cause and Effect 163

15.2 Literature Review 165

15.3 Question Before the Law 168

15.4 Process Stability 169

15.4.1 Internal Control 170

15.4.2 Mathematical Model for Correlation 170

15.5 Conclusions 173

Credits 174

References 174

16 Verification and Validation 179

16.1 Cause and Effect 180

16.1.1 An Historical View 180

16.1.2 Productivity versus Quality 182

16.2 What Is in a Name? 185

16.2.1 Verification and Validation Defined 186

16.2.2 Inspection and Test 187

16.2.3 Monitor and Measure 188

16.2.4 Subtle Transitions 189

16.3 The Forensic View of Measurement 190

16.3.1 Machine Tools and Tooling 190

16.3.2 Measurement 191

16.3.3 Control Charting 192

16.3.4 First Pass Yield 192

16.3.5 First Article Inspection 193

16.3.6 Tool Try 194

References 194

17 Forensic Sampling of Internal Controls 197

17.1 Populations 198

17.1.1 Sample Population 199

17.1.2 Homogeneity 199

17.1.3 Population Size 200

17.1.4 One Hundred Percent Inspection 201

17.2 Sampling Plan 201

17.2.1 Objectives 201

17.2.2 Statistical and Nonstatistical Sampling 202

17.2.3 Fixed Size and Stop?]or?]Go 203

17.2.4 Sample Selection and Size 204

17.3 Attribute Sampling 204

17.3.1 Internal Control Sampling 204

17.3.2 Deviation Rates 206

17.3.2.1 Acceptable Deviation Rate 206

17.3.2.2 System Deviation Rate 207

17.3.3 Sampling Risks 207

17.3.3.1 Control Risk 207

17.3.3.2 Alpha and Beta Risks 208

17.3.4 Confidence Level 208

17.3.5 Evaluation 209

17.4 Forensic System Caveats 209

References 210

18 Forensic Analysis of Supplier Control 211

18.1 Outsourcing 213

18.2 Supply Chain Management 215

18.3 Forensic Analysis of Supply Systems 216

18.3.1 Basic Principles of Supplier Control 216

18.3.2 The Forensic Challenge 216

18.3.2.1 Ensure that Purchased Units Conform

to Contracted Specifications 217

18.3.2.2 Assessment of the Supplier Process 218

18.3.2.3 Tracking 218

18.3.2.4 Customer Relations 219

18.3.2.5 Verification and Storage of Supplies 221

18.3.2.6 Identification and Traceability 222

18.4 Supplier Verification: A Case Study 223

18.4.1 Manufacture 224

18.4.2 V50 Testing 224

18.4.3 V50 Test Results 226

18.5 Malfeasant Supply Systems 226

References 227

19 Discovering System Nonconformity 229

19.1 Identifying Nonconformities 231

19.1.1 Reporting Nonconformities 232

19.1.2 Disputes 233

19.2 The Elements of Assessment 234

19.2.1 Measures of Performance 234

19.2.2 Considerations in Forensic Analysis of Systems 235

19.3 Forming Decisions 236

19.4 Describing Nonconformities 238

19.5 A Forensic View of Documented Information 240

19.5.1 Requirements in Documented Information 241

19.5.2 The Quality Manual 241

19.5.3 Documented Information Control 243

19.5.4 Records 244

Acknowledgment 246

References 246

Appendix A The Engineering Design Process: A Descriptive View 247

A.1 Design and Development 248

A.1.1 The Design Process 248

A.1.2 Customer Requirements 249

A.1.3 Interactive Design 249

A.1.4 Intermediate Testing 249

A.1.5 Final Iteration 251

A.2 Forensic Analysis of the Design Process 252

References 253

Appendix B Introduction to Product Reliability 255

B.1 Reliability Characteristics 256

B.1.1 Reliability Metrics 256

B.1.2 Visual Life Cycle 257

B.2 Weibull Analysis 259

B.2.1 Distributions 259

B.2.2 Shape and Scale 260

B.2.2.1 Shape 260

B.2.2.2 Scale 262

B.2.3 The B?]Percentile 262

B.3 Design for Reliability 263

B.4 Measuring Reliability 265

B.4.1 On Reliability Metrics 265

B.4.2 Graphing Failure Data 266

B.5 Testing for Reliability 269

References 271

Appendix C Brief Review of Probability and Statistics 273

C.1 Measures of Location 274

C.1.1 Average: The Mean Value 274

C.1.2 Average: The Median 275

C.1.3 Average: The Mode 275

C.2 Measures of Dispersion 276

C.2.1 Variance 276

C.2.2 Range 276

C.3 Distributions 277

C.3.1 Continuous Distributions 277

C.3.2 Discrete Distributions 279

C.4 Tests of Hypotheses 281

C.4.1 Estimating Parametric Change 281

C.4.2 Confidence Level 284

C.5 Ordered Statistics 284

References 285

Appendix D Sampling of Internal Control Systems 287

D.1 Populations 288

D.1.1 Sample Populations 289

D.1.2 Population Size 290

D.1.3 Homogeneity 290

D.2 Attribute Sampling 291

D.2.1 Acceptable Deviation Rate 292

D.2.2 System Deviation Rate 293

D.2.3 Controls 293

D.3 Sampling

Risks 294

D.3.1 Control Risk 294

D.3.2 Consumer and Producer Risks 294

D.3.3 Alpha and Beta Errors 295

D.4 Sampling Analysis 297

D.4.1 Statistical Inference 297

D.4.2 Sample Distributions 298

D.4.3 Sample Size 299

D.4.4 Estimating the SDR 299

D.4.5 Confidence Interval 300

References 302

Appendix E Statistical Sampling Plans 305

E.1 Fixed?]Size Attribute Sampling Plan 306

E.1.1 Determine the Objectives 306

E.1.2 Define Attribute and Deviation Conditions 306

E.1.2.1 Acceptable Deviation Rate 306

E.1.2.2 System Deviation Rate 307

E.1.3 Define the Population 307

E.1.4 Determine the Method of Sample Selection 307

E.1.5 Determine the Sample Size 308

E.1.6 Perform the Sampling Plan 312

E.1.7 Evaluate Sample Results 312

E.2 Stop?]or?]Go Sampling 313

E.2.1 Acceptable Deviation Rate 313

E.2.2 Sample Size 314

E.2.3 Evaluation 316

E.3 One Hundred Percent Inspection 316

E.4 Application: An Attribute Sampling Plan 317

References 318

Appendix F Nonstatistical Sampling Plans 321

F.1 Sampling Format 322

F.1.1 Frame of the Sampling Plan 322

F.1.2 Attribute and Deviation Conditions 323

F.1.3 The Population 323

F.1.4 Nonstatistical Sample Selection 324

F.1.5 Sample Size 325

F.1.6 The Effect of Sample Size on Beta Error 326

F.1.7 Evaluating Sample Results 327

F.2 Nonstatistical

Estimations 327

References 328

Index
William A. Stimson, PhD, is an independent consultant in systems engineering, and an expert witness for the Department of Justice and private law firms in evaluation of contractor performance. He has taken an active role in developing legal strategy for the evaluation of performance of operations in litigation, presented on the topic of forensic evaluation, and published peer-reviewed papers on dysfunctional processes.