Cover Page

Wiley Series in Systems Engineering and Management

William Rouse, Editor

Andrew P. Sage, Founding Editor

ANDREW P. SAGE and JAMES D. PALMER
Software Systems Engineering

WILLIAM B. ROUSE
Design for Success: A Human‐Centered Approach to Designing Successful Products and Systems

LEONARD ADELMAN
Evaluating Decision Support and Expert System Technology

ANDREW P. SAGE
Decision Support Systems Engineering

YEFIM FASSER and DONALD BRETINER
Process Improvement in the Electronics Industry, Second Edition

WILLIAM B. ROUSE
Strategies for Innovation

ANDREW P. SAGE
Systems Engineering

HORST TEMPELMEIER and HEINRICH KUHN
Flexible Manufacturing Systems: Decision Support for Design and Operation

WILLIAM B. ROUSE
Catalysts for Change: Concepts and Principles for Enabling Innovation

UPING FANG, KEITH W. HIPEL, and D. MARC KILGOUR
Interactive Decision Making: The Graph Model for Conflict Resolution

DAVID A. SCHUM
Evidential Foundations of Probabilistic Reasoning

JENS RASMUSSEN, ANNELISE MARK PEJTERSEN, and LEONARD P. GOODSTEIN
Cognitive Systems Engineering

ANDREW P. SAGE
Systems Management for Information Technology and Software Engineering

ALPHONSE CHAPANIS
Human Factors in Systems Engineering

YACOV Y. HAIMES
Risk Modeling, Assessment, and Management, Third Edition

DENNIS M. SUEDE
The Engineering Design of Systems: Models and Methods, Second Edition

ANDREW P. SAGE and JAMES E. ARMSTRONG, Jr.
Introduction to Systems Engineering

WILLIAM B. ROUSE
Essential Challenges of Strategic Management

YEFIM FASSER and DONALD BRETTNER
Management for Quality in High‐Technology Enterprises

THOMAS B. SHERIDAN
Humans and Automation: System Design and Research Issues

ALEXANDER KOSSIAKOFF and WILLIAM N. SWEET
Systems Engineering Principles and Practice

HAROLD R. BOOHER
Handbook of Human Systems Integration

JEFFREY T. POLLOCK and RALPH HODGSON
Adaptive Information: Improving Business Through Semantic Interoperability, Grid Computing, and Enterprise Integration

ALAN L. PORTER and SCOTT W. CUNNINGHAM
Tech Mining: Exploiting New Technologies for Competitive Advantage

REX BROWN
Rational Choice and Judgment: Decision Analysis for the Decider

WILLIAM B. ROUSE and KENNETH R. BOFF (Editors)
Organizational Simulation

HOWARD EISNER
Managing Complex Systems: Thinking Outside the Box

STEVE BELL
Lean Enterprise Systems: Using IT for Continuous Improvement

J. JERRY KAUFMAN and ROY WOODHEAD
Stimulating Innovation in Products and Services: With Function Analysis and Mapping

WILLIAM B. ROUSE
Enterprise Transformation: Understanding and Enabling Fundamental Change

JOHN E. GIBSON, WILLIAM T. SCHERER, and WILLAM F. GIBSON
How to Do Systems Analysis

WILLIAM F. CHRISTOPHER
Holistic Management: Managing What Matters for Company Success

WILLIAM B. ROUSE
People and Organizations: Explorations of Human‐Centered Design

MOJAMSHIDI
System of Systems Engineering: Innovations for the Twenty‐First Century

ANDREW P. SAGE and WILLIAM B. ROUSE
Handbook of Systems Engineering and Management, Second Edition

JOHN R. CLYMER
Simulation‐Based Engineering of Complex Systems, Second Edition

KRAG BROTBY
Information Security Governance: A Practical Development and Implementation Approach

JULIAN TALBOT and MILES JAKEMAN
Security Risk Management Body of Knowledge

SCOTT JACKSON
Architecting Resilient Systems: Accident Avoidance and Survival and Recovery from Disruptions

JAMES A. GEORGE and JAMES A. RODGER
Smart Data: Enterprise Performance Optimization Strategy

YORAM KOREN
The Global Manufacturing Revolution: Product‐Process‐Business Integration and Reconfigurable Systems

AVNER ENGEL
Verification, Validation, and Testing of Engineered Systems

WILLIAM B. ROUSE (Editor)
The Economics of Human Systems Integration: Valuation of Investments in People’s Training and Education, Safety and Health, and Work Productivity

ALEXANDER KOSSIAKOFF, WILLIAM N. SWEET, SAM SEYMOUR, and STEVEN M. BIEMER
Systems Engineering Principles and Practice, Second Edition

GREGORY S. PARNELL, PATRICK J. DRISCOLL, and DALE L. HENDERSON (Editors)
Decision Making in Systems Engineering and Management, Second Edition

ANDREW P. SAGE and WILLIAM B. ROUSE
Economic Systems Analysis and Assessment: Intensive Systems, Organizations, and Enterprises

BOHDAN W. OPPENHEIM
Lean for Systems Engineering with Lean Enablers for Systems Engineering

LEV M. KLYATIS
Accelerated Reliability and Durability Testing Technology

BJOERN BARTELS, ULRICH ERMEL, MICHAEL PECHT, and PETER SANDBORN
Strategies to the Prediction, Mitigation, and Management of Product Obsolescence

LEVANT YILMAS and TUNCER OREN
Agent‐Directed Simulation and Systems Engineering

ELSAYED A. ELSAYED
Reliability Engineering, Second Edition

BEHNAM MALAKOOTI
Operations and Production Systems with Multipme Objectives

MENG‐LI SHIU, JUI‐CHIN JIANG, and MAO‐HSIUNG TU
Quality Strategy for Systems Engineering and Management

ANDREAS OPELT, BORIS GLOGER, WOLFGANG PFARL, and RALF MITTERMAYR
Agile Contracts: Creating and Managing Successful Projects with Scrum

KINJI MORI
Concept‐Oriented Research and Development in Information Technology

KAILASH C. KAPUR and MICHAEL PECHT
Reliability Engineering

MICHAEL TORTORELLA
Reliability, Maintainability, and Supportability: Best Practices for Systems Engineers

DENNIS M. BUEDE and WILLIAM D. MILLER
The Engineering Design of Systems: Models and Methods, Third Edition

JOHN E. GIBSON, WILLIAM T. SCHERER, WILLIAM F. GIBSON, and MICHAEL C. SMITH
How to Do Systems Analysis: Primer and Casebook

GREGORY S. PARNELL
Trade‐off Analytics: Creating and Exploring the System Tradespace

CHARLES S. WASSON
Systems Engineering Analysis, Design and Development

Forensic Systems Engineering

Evaluating Operations by Discovery


William A. Stimson




















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To Josette,

my love,

my wife,

my friend,

my life.

Preface

Scientific theories deal with concepts, never with reality. All theoretical results are derived from certain axioms by deductive logic. The theories are so formulated as to correspond in some useful sense to the real world whatever that may mean. However, this correspondence is approximate, and the physical justification of all theoretical conclusions is based on some form of inductive reasoning

(Papoulis, 1965).

The profession of law is several thousand years old, at least. Given this history, it is quite natural that tradition would have an important role. This is especially true in English Common Law, in which precedence has a major influence on judicial decisions. During the past 100 years or so, product liability has developed as the basis of tort law when there is a question of harm caused by a product or service, and thus enjoys the influence of tradition. During much of this time, production volume was relatively low, claims were low in proportion, and over the years, litigation involving product liability became relatively straightforward.

Today, production volume can be massive—hundreds of thousands of units produced and sold annually, with claims increasing in proportion. The result has been class action suits and large volume manufacturing suits, all continuing to be prosecuted by product liability, one claim per unit. From an engineering point of view, this process is inefficient and even ineffective. As seen by engineers, a far more effective mechanism for litigation would be process liability.

The concept of process liability was first defined by attorney Leonard Miller (5 New Eng. L. Rev. 163, 1970) in his article, “Air pollution control: An introduction to process liability and other private actions.” Being unschooled in law, I do not know the present status of this idea in legal circles, but it is certainly helpful in forensic analysis and in systems engineering. In this book, process liability is shown to be a direct result of systems engineering procedures and methodologies applied to business operations.

Engineers have long recognized the strong correlation of process to product and many mathematical models are commonly used that can validate this cause and effect relationship. Process liability provides a needed legal basis in forensic application. Forensic Systems Engineering offers a complete approach to the investigation of large volume operations by uniting the concept of process liability to systems engineering.

Organization of the Book

The purpose of forensic systems engineering is to identify dysfunctional processes and to determine root causes of process failure, and further, to assist the court in determining whether harm or a breach of contract has occurred. Chapters 1 through 6 describe the role of management in operations. Chapters 7 through 11 unite liability to the essential characteristics of processes used in these operations. Chapter 12 is a fictional case study of a manufacturer, albeit based on actual events. The narration of the study is similar to the narrative technique used in many graduate schools of business.

Chapters 13 through 15 offer formal mathematical models, widely accepted in systems engineering, to demonstrate the correlation of process to product in terms of the risk of liability. Chapter 16 delves into the most troubling area found in my years as a consultant and expert witness in the litigation of business operations—the verification and validation of processes. Chapter 17 discusses the difficulty of supplier control in the age of offshore outsourcing and supply chain management. Chapter 18 addresses an unavoidable aspect of process evaluation via discovery, the effect of sampling. Finally, Chapter 19 discusses the process of identifying nonconformities in discovery and how to assess them.

Appendices A through F provide certain basic information to the reader in those subjects that are essential to forensic systems engineering and analysis. Appendices A and B are detailed accounts of engineering issues that occur more frequently in contract litigation than others. Appendix A concerns design and development; Appendix B concerns product reliability and should be considered by the reader as a prerequisite for Chapter 10.

Appendices C through F address the statistical nature of production and service processes and the fact that a forensic audit of discovery is effectively a sampling process. Therefore, the procedures of sampling and of statistics apply. These appendices, too, should be perused before Chapter 18, and they would be helpful in understanding Chapters 13 through 16. These latter chapters introduce the subject of risk, which is a probability, and employ various mathematical models of random variables.

Definitions and Terms of Art

One of the things that I admire about the profession of law is that when a specific idea requires a unique definition, it is expressed in Latin. Examples abound: nolo contendere, habeas corpus, qui tam, and so on. The terminology is effective because it is constant over time and does not compete with the common language. Unfortunately, engineering lacks this insight. When engineers want to express a specific idea, they borrow terms from the common language even though the engineering definition may have little to do with common understanding. One example will suffice. A system is called controllable if it can be taken from an initial state to any other state in finite time. I have witnessed a meeting at NASA aborted because someone used the word “controllable” in its general meaning, thereby confusing the conversation.

In addition, even terms within engineering context vary in their meaning, depending upon the audience. The meaning of terms such as production, operations, process, and system may differ from one group to another in the business and technical community. Therefore, to prevent confusion I have provided the definition of certain technical terms as they are intended in this book.

Discovery

Discovery is a pretrial procedure in a lawsuit in which each party in litigation, by court order, may obtain evidence from the other party by means of discovery devices such as documents, interrogatories, admissions, and depositions. The term “discovery” hence refers to the body of evidence available to each party in their pursuit of justice.

Production, Service, and Operations

For brevity, in this book the phrase “production or service” is called “operations.” On occasion, I may use “production” in lieu of “operations,” but only if the context is manufacturing. Or I may use the term “product” when speaking of operations in accordance with common usage. For example, I may speak of product quality or product reliability even though I implicitly include service, and ask the reader to bear in mind that service also has the traits of quality and reliability that apply to production. From a systems viewpoint, there is little or no difference between production and service. For this reason, for additional brevity I may use the term “unit” in place of the phrase “product or service.” For example, I might say 10 units proved to be nonconforming to requirements. These units could be 10 jet engine fan blades or they could be 10 billing accounts, depending on the context of the discussion.

Management System

The classical role of management is described in five functions: plans, organization, coordination, decision, and control (Laudon & Laudon, 1991). It is reasonable to assume that a systematic approach to these activities will optimize the effectiveness and efficiency of their results. Such an approach is called a management system. The overall system includes structures for self‐correction and for improving performance. The functions become subsystems of the management system, whose role is to achieve a synergistic direction to corporate goals.

With a system of management, operations can be conducted in an orderly fashion such that responsibility, authority, and accountability may be assigned with documented procedures and traceable results. The documentation and traceability do more than provide a basis from which risk assessment and methods of improvement can be made. They also provide forensic evidence if litigation arises. The evidence may support the defense or the plaintiff, depending on its nature.

The effectiveness of management will be a result of this system. Critics claim that too strict an adherence to formal procedures will stifle innovation. On the other hand, no system at all invites fire drill modes and chaos. Forensic systems engineering will measure the effectiveness of a management system in litigation by its conformity to contract requirements. The justification for this strategy is developed throughout this book.

Performance Standard

A management system has both form and substance. The form might derive from a standard of management. In this book, frequent reference is made to standards of management whose objective is the effective performance of operations in assuring the quality of the product or service rendered. Systematic operation is essential to effectiveness and can be enhanced by management standards. Such a standard is often called a quality management system (QMS) because its purpose is to improve the quality of whatever is being produced or served. For example, ISO 9001 is such a standard.

It is not unusual that in describing a document, the words management, performance, standard, and quality all occur in the same paragraph. To minimize this repetition, I may refer to such a document according to the characteristic being discussed and call it a standard of quality management, a standard of performance, or a standard of operations. In all cases, I am talking about the same thing—the effective management of business operations.

In short, I equate a standard of performance to a standard of quality management. This convention may be controversial because “quality” has, in industry, a nebulous definition. Many a company sharply distinguishes between its operations function and its quality function. Yet, assuming that a process is causal, then quality either refers to the goodness of operations or it has little meaning. (Some might argue whether a process is causal, but engineers do not and this book goes to great lengths to demonstrate the causal relation between process and product.) I regard ISO 9001 has a parsimonious set of good business practices and therefore an excellent performance standard, recognizable as such in a court of law.

A system and a standard for that system have a straightforward relationship—that of form and substance. We might say that form is a model of something; substance is the reality of it. Philosophically, the entity may or may not have physical substance. A violin can be substantive, but the music played on it may also be substantive. Relative to standard and system, the former provides the form and the system provides the substance. Both are deemed necessary to effective performance and the forensic evidence of nonconformity in either can lead to product or process liability.

A forensic investigation is akin to an audit in that it compares the descriptive system to the normative—what it is to what it should be. An effective examination of evidence will reveal what the system is doing; what it should be doing requires a relevant standard. In forensic analysis of operational systems, any recognized performance management standard can serve this role. By “recognized,” I mean a standard that is recognized within the appropriate industry and by the law. Chapter 2 provides a list of several well‐recognized performance standards that would carry weight in a court of law. All of them are very good in enhancing the effectiveness of operations, but not all of them are general enough to cover both strategic and tactical activities. A standard is needed for the purpose of explaining forensic systems engineering and ISO 9001 (2015) is selected as the model standard of this book because of its international authority.

I must admit that the selection of ISO 9001 as the standard of performance for this book is taken with some unease. This standard is rewritten every few years, not in its fundamentals but in its format. A good practice in, say, Clause 3 of one year may appear in Clause 5 in another year and perhaps even under another name or with a slightly different description. I beg the reader to understand that in this book, a reference to an ISO 9001 control or to its information refers to an accepted universal principle or action and not to a particular clause, paragraph, or annual version. For forensic purposes, any reference to ISO 9001 can be defended in court, although tracking down the itemized source may take some ingenuity.

Process Liability

The notion of process liability as it applies to operations is discussed in considerable detail in Chapter 6, but the subject is crucial to forensic systems engineering and appears often in various chapters of this book as it is applied to different situations. At this point, I shall not present the argument for process liability but simply introduce its genesis.

In his paper cited earlier, attorney Leonard A. Miller introduced the concept of process liability and traced legal precedents that justified its use. With permission of Mr. Miller and of the New England Law Review, several paragraphs are extracted from his paper and inserted in this book because of their pertinence to forensic investigation. Although referring to pollution control, his arguments for process liability are logically and clearly applicable to nonconforming or dysfunctional processes, as explained in Chapter 6.

Controllability, Reachability, and Observability

Formally, a system is controllable if it can be taken from any initial state in its state space to its zero state in finite time. A system is reachable if it can be taken from the zero state to any other state in finite time (Siljak, 1969). Over the years, the need to distinguish between system controllability and reachability has lessened and the latter has largely disappeared, simply by making a minor change in the definition of controllability to include the property of reachability. This explains the earlier definition I used in talking about the engineering use of common words: Engineers today say that a system is controllable if it can be taken from any initial state to any other state in finite time.

A system is completely observable if all its dynamic modes of motion can be ascertained from measurements of the available outputs (Siljak). Observability is no small issue in forensics because of its relation to verification and validation, which obviously require the property of observability. From an engineering point of view, inadequate processes of verification and validation render a system unobservable and are major nonconformities in management.

Process and System

The terms system and its kin, process, have no standard meaning in business and industry. Historically, they have carried different connotations and still do. For example, the international management standard, ISO 9000 (2005), distinguishes between them, defining a process as a set of interrelated or interacting activities which transforms inputs into outputs, and defining a system somewhat differently, omitting the dynamic sense assigned to a process.

In systems theory, they are regarded as the same thing. R.E. Kalman et al. (1969) defined a system as a mathematical abstraction—a dynamical process consisting of a set of admissible inputs, a set of single‐valued outputs, all possible states, and a state transition function. Since a system is a dynamical process in systems theory and a process is dynamical by definition of ISO 9000, the terms are considered equivalent in this book. I may use “process” and “system” where they are traditionally used, but I ask the reader to bear in mind that they behave the same way. The elements that compose a process or system may be called a subprocess or subsystem.

Product and Process Quality

Over the years there have been many definitions of “quality” when referring to a product, but the international definition used in this book is provided by ISO 9000 (2005): quality is the degree to which a set of inherent characteristics of a product or service fulfils requirements. Conformity is the fulfillment of a requirement; nonconformity is the nonfulfillment of a requirement. The requirements may denote those of a unit, customer, or the QMS. These definitions are also used in this book because they are good ones, implying how one might measure quality.

However, from a systems view, the definition of quality is necessary but not sufficient, as it infers nothing about the system that provides the product or service. One of the major objectives of this book is to demonstrate a causal relation between the conformance of a process and the conformance of its output. Any definition of quality should accommodate this relationship. Therefore, in Chapter 5, I offer an additional measure of “quality”: it refers to the effectiveness of productive and service processes in assuring that products and services meet customer requirements.

Acceptable Quality and Acceptable Performance

In the context of product and process, manufacturing uses two similar terms. Recognizing that no process is perfect, industry employs the metric, acceptable performance level (APL), defined as the lowest acceptable performance level of a function being audited (Mills, 1989). However, the term is not used in reference to a performance objective, but it is used simply to determine a sample size.

Similarly, recognizing that no sampling plan is perfect, industry employs the metric, acceptable quality level (AQL), defined as the largest percent defective acceptable in a given lot (Grant & Leavenworth, 1988). From the standpoint of auditing controls, the two criteria are essentially identical. Therefore, in this book the term, acceptable performance level, is preferred when referring to either concept because it has a greater sense of systems activity, suggesting both a dynamism and a broad perspective, in keeping with systems thinking.

Effectiveness and Efficiency

In litigation, it is critical that the meaning of a term be clear and unambiguous. I generally follow the definitions of ISO 9000 (2005). Effectiveness is the extent to which planned activities are realized and planned results are achieved. Efficiency is the relationship between the results achieved and the resources used. Briefly, then, effectiveness is a measure of how good the process is; efficiency is a measure of the cost to obtain that goodness.

Compliance and Conformance

Because financial auditing is subject to legal review, its procedures are well developed and formal. They are acknowledged and respected in courts of law. Forensic systems engineering is fundamentally an audit of evidence in discovery and as such the analysis should be conducted in a manner acceptable in court. Therefore, I often refer to the techniques of financial auditing in this book and use some of its terms, although they may differ somewhat from their meaning in business operations. Compliance is one such term.

A financial auditor audits financial reports for compliance to legal requirements. This corresponds closely with the definition of compliance used in manufacturing or service operations: Compliance is the affirmative indication or judgment that the performer of a product or service has met the requirements of the relevant contract, specifications, or regulation (Russell, 1997). In contrast, the same source defines conformance as the affirmative indication or judgment that a product or service has met the requirements of the relevant contract, specifications, or regulation.

Because of the kinship of process and product in liability, I continue with this kinship in performance and usually speak of the conformance of a control rather than of its compliance. This assignment can get complicated if the control is nonconforming because of misfeasance, which suggests that the control is noncompliant also. At the end of the day, the wording to be used in litigation will be determined by attorneys and not by forensic analysts or engineers.

Framework and Model

The word framework has several meanings but the one used quite often in business is that of a basic structure underlying a system, concept, or text. You see the word several times in Table 2.1, used in the titles of recognized performance standards. Engineers, however, tend to use the word model possibly because any concept is modeled mathematically before it is physically constructed. Although the two words come from different spheres, they meet in this book and are used interchangeably. Both refer to an organization or structure of elements assembled to affect a purpose. In short, they depict systems.

Sidestepped Definitions

There are several subjects of common occurrence in most civil litigation whose use cannot be avoided, but whose definitions I choose to leave unsaid. Strict liability and due diligence are used in this book in the sense that I understand them. However, I am unschooled in law and prefer that readers look up the meaning of the terms on their own.

Another such term is standard of care. This issue is critical to any critique of management performance and I use it often. Standard of care refers to the watchfulness, attention, caution, and prudence that a reasonable person in the circumstances would exercise. Failure to meet the standard is negligence, and any damages resulting there from may be claimed in a lawsuit by the injured party. The problem is that the “standard” is often a subjective issue upon which reasonable people can differ. I believe that in any specific litigation, standard of care will be decided by the court, so the very general description just given will do for this book.

Redundancy

The reader will find a certain amount of repetition of information in this book, and deliberately so. First, I believe that redundancy is a good teaching tool. Secondly, some important properties, understood in one context, may also be applicable in other contexts. For example, ISO 9001 is regarded internationally as a set of good business practices and this role is important from a number of points of view, each view expressed in a different chapter: Chapter 4, Chapter 5, and Chapter 8. Also, internal controls are defined redundantly: Chapter 5, Chapter 11, Chapter 14, and Chapter 15. As an additional example, a comparison of the terms durability and reliability is made both in Chapter 2 and in Appendix B because the difference is very important and not all readers will read the appendix.

References

  1. ANSI/ISO/ASQ (2005). ANSI/ISO/ASQ Q9000‐2005: Quality Management Systems—Fundamentals and Vocabulary. Milwaukee, WI: American National Standards Institute and the American Society for Quality.
  2. ANSI/ISO/ASQ (2015). ANSI/ISO/ASQ Q9001‐2015: American National Standard: Quality Management System Requirements. Milwaukee, WI: American National Standards Institute and the American Society for Quality.
  3. Grant, E. L. and Leavenworth, R. S. (1988). Statistical Quality Control. New York: McGraw‐Hill, p. 452.
  4. Kalman, R. E., Falb, P. L., and Arbib, M. A. (1969). Topics in Mathematical System Theory. New York: McGraw‐Hill, p.74.
  5. Laudon, K. C. and Laudon, J. P. (1991). Management Information Systems: A Contemporary Perspective. New York: Macmillan, p. 145
  6. Miller, L. A. (1970). “Air Pollution Control: An Introduction to Process Liability and other Private Actions.” New England Law Review, vol. 5, pp. 163–172.
  7. Mills, C. A. (1989). The Quality Audit. New York: McGraw‐Hill, p. 172.
  8. Papoulis, A., (1965). Probability, Random Variables and Stochastic Properties. New York: McGraw‐Hill.
  9. Russell, J. P., ed. (1997). The Quality Audit Handbook. Milwaukee, WI: ASQ Quality Press, p. 12.
  10. Siljak, D. D. (1969). Nonlinear Systems: Parameter Analysis and Design. New York: John Wiley & Sons, Inc., pp. 445–446.