Search for: All records

Abstract The modeling and simulation community has devoted considerable attention to the question of model validity. Their work has focused on the concept of “accuracy,” loosely defined as the difference between a model-computed result and a real-world result. This paper makes use of an example case that results in a paradox to illustrate weaknesses in an accuracy-focused approach, and proposes in its stead a value-focused approach based on classical decision theory. Instead of advocating the use of a model based on its accuracy, this work advocates using a model if it adds value to the overall application thus relating validation directly to system performance. The approach fills significant gaps in the current theory, notably providing a clearly defined validity metric and a fundamental rationale for the use of this metric. 

Abstract Tolerancing began with the notion of limits imposed on the dimensions of realized parts both to maintain functional geometric dimensionality and to enable cost-effective part fabrication and inspection. Increasingly, however, component fabrication depends on more than part geometry as many parts are fabricated as a result of a “recipe” rather than dimensional instructions for material addition or removal. Referred to as process tolerancing, this is the case, for example, with IC chips. In the case of tolerance optimization, a typical objective is cost minimization while achieving required functionality or “quality.” This article takes a different look at tolerances, suggesting that rather than ensuring merely that parts achieve a desired functionality at minimum cost, a typical underlying goal of the product design is to make money, more is better, and tolerances comprise additional design variables amenable to optimization in a decision theoretic framework. We further recognize that tolerances introduce additional product attributes that relate to product characteristics such as consistency, quality, reliability, and durability. These important attributes complicate the computation of the expected utility of candidate designs, requiring additional computational steps for their determination. The resulting theory of tolerancing illuminates the assumptions and limitations inherent to Taguchi’s loss function. We illustrate the theory using the example of tolerancing for an apple pie, which conveniently demands consideration of tolerances on both quantities and processes, and the interaction among these tolerances. 

Abstract The derivation of a theory of systems engineering has long been complicated by the fact that there is little consensus within the systems engineering community regarding precisely what systems engineering is, what systems engineers do, and what might constitute reasonable systems engineering practices. To date, attempts at theories fail to accommodate even a sizable fraction of the current systems engineering community, and they fail to present a test of validity of systems theories, analytical methods, procedures, or practices. This article presents a more theoretical and more abstract approach to the derivation of a theory of systems engineering that has the potential to accommodate a broad segment of the systems engineering community and present a validity test. It is based on a simple preference statement: “I want the best system I can get.” From this statement, it is argued that a very rich theory can be obtained. However, most engineering disciplines are framed around a core set of widely accepted physical laws; to the authors’ knowledge, this is the first attempt to frame an engineering discipline around a preference. 

Abstract System design is commonly thought of as a process of maximizing a design objective subject to constraints, among which are the system requirements. Given system-level requirements, a convenient management approach is to disaggregate the system into subsystems and to “flowdown” the system-level requirements to the subsystem or lower levels. We note, however, that requirements truly are constraints, and they typically impose a penalty on system performance. Furthermore, disaggregation of the system-level requirements into the flowdown requirements creates added sets of constraints, all of which have the potential to impose further penalties on overall system performance. This is a highly undesirable effect of an otherwise beneficial system design management process. This article derives conditions that may be imposed on the flowdown requirements to assure that they do not penalize overall system performance beyond the system-level requirement.