Measuring Value in Product Development

“What is value in product development?” is the key question of this paper. The answer is critical to the creation of lean in product development. By knowing how much value is added by product development (PD) activities, decisions can be more rationally made about how to allocate resources, such as time and money. In order to apply the principles of Lean Thinking and remove waste from the product development system, value must be precisely defined. Unfortunately, value is a complex entity that is composed of many dimensions and has thus far eluded definition on a local level. For this reason, research has been initiated on “Measuring Value in Product Development.” This paper serves as an introduction to this research. It presents the current understanding of value in PD, the critical questions involved, and a specific research design to guide the development of a methodology for measuring value. Work in PD value currently focuses on either high-level perspectives on value, or detailed looks at the attributes that value might have locally in the PD process. Models that attempt to capture value in PD are reviewed. These methods, however, do not capture the depth necessary to allow for application. A methodology is needed to evaluate activities on a local level to determine the amount of value they add and their sensitivity with respect to performance, cost, time, and risk. Two conceptual tools are proposed. The first is a conceptual framework for value creation in PD, referred to here as the Value Creation Model. The second tool is the Value-Activity Map, which shows the relationships between specific activities and value attributes. These maps will allow a better understanding of the development of value in PD, will facilitate comparison of value development between separate projects, and will provide the information necessary to adapt process analysis tools (such as DSM) to consider value. The key questions that this research entails are: · What are the primary attributes of lifecycle value within PD? · How can one model the creation of value in a specific PD process? · Can a useful methodology be developed to quantify value in PD processes? · What are the tools necessary for application? · What PD metrics will be integrated with the necessary tools? The research milestones are: · Collection of value attributes and activities (September, 200) · Development of methodology of value-activity association (October, 2000) · Testing and refinement of the methodology (January, 2001) · Tool Development (March, 2001) · Present findings at July INCOSE conference (April, 2001) · Deliver thesis that captures a formalized methodology for defining value in PD (including LEM data sheets) (June, 2001) The research design aims for the development of two primary deliverables: a methodology to guide the incorporation of value, and a product development tool that will allow direct application.

Type-omega DPLs

Type-omega DPLs (Denotational Proof Languages) are languages for proof presentation and search that offer strong soundness guarantees. LCF-type systems such as HOL offer similar guarantees, but their soundness relies heavily on static type systems. By contrast, DPLs ensure soundness dynamically, through their evaluation semantics; no type system is necessary. This is possible owing to a novel two-tier syntax that separates deductions from computations, and to the abstraction of assumption bases, which is factored into the semantics of the language and allows for sound evaluation. Every type-omega DPL properly contains a type-alpha DPL, which can be used to present proofs in a lucid and detailed form, exclusively in terms of primitive inference rules. Derived inference rules are expressed as user-defined methods, which are "proof recipes" that take arguments and dynamically perform appropriate deductions. Methods arise naturally via parametric abstraction over type-alpha proofs. In that light, the evaluation of a method call can be viewed as a computation that carries out a type-alpha deduction. The type-alpha proof "unwound" by such a method call is called the "certificate" of the call. Certificates can be checked by exceptionally simple type-alpha interpreters, and thus they are useful whenever we wish to minimize our trusted base. Methods are statically closed over lexical environments, but dynamically scoped over assumption bases. They can take other methods as arguments, they can iterate, and they can branch conditionally. These capabilities, in tandem with the bifurcated syntax of type-omega DPLs and their dynamic assumption-base semantics, allow the user to define methods in a style that is disciplined enough to ensure soundness yet fluid enough to permit succinct and perspicuous expression of arbitrarily sophisticated derived inference rules. We demonstrate every major feature of type-omega DPLs by defining and studying NDL-omega, a higher-order, lexically scoped, call-by-value type-omega DPL for classical zero-order natural deduction---a simple choice that allows us to focus on type-omega syntax and semantics rather than on the subtleties of the underlying logic. We start by illustrating how type-alpha DPLs naturally lead to type-omega DPLs by way of abstraction; present the formal syntax and semantics of NDL-omega; prove several results about it, including soundness; give numerous examples of methods; point out connections to the lambda-phi calculus, a very general framework for type-omega DPLs; introduce a notion of computational and deductive cost; define several instrumented interpreters for computing such costs and for generating certificates; explore the use of type-omega DPLs as general programming languages; show that DPLs do not have to be type-less by formulating a static Hindley-Milner polymorphic type system for NDL-omega; discuss some idiosyncrasies of type-omega DPLs such as the potential divergence of proof checking; and compare type-omega DPLs to other approaches to proof presentation and discovery. Finally, a complete implementation of NDL-omega in SML-NJ is given for users who want to run the examples and experiment with the language.

Probabilistic Analysis of Multistage Interconnection Network Performance

We present methods of calculating the value of two performance parameters for multipath, multistage interconnection networks: the normalized throughput and the probability of successful message transmission. We develop a set of exact equations for the loading probability mass functions of network channels and a program for solving them exactly. We also develop a Monte Carlo method for approxmiate solution of the equations, and show that the resulting approximation method will always calculate the values of the performance parameters more quickly than direct simulation.