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In this paper, we present the importance of using a singlecriterion approach to Decision-Based Design (DBD) by examining the flaws and limitations of multicriteria approaches. We propose in this paper an approach to DBD as an enhancement to Hazelrigg's DBD framework that utilizes the economic benefit to the producer as the single criterion in alternative selection. The technique of Discrete Choice Analysis (DCA) is introduced for constructing a product demand model, which is crucial for the evaluations of both profit and production cost. An academic universal motor design problem illustrates the proposed DBD approach. It appears that DBD, when applied correcfiy, is capable of unambiguously selecting the preferred alternative in a rigorous manner. Open research issues related to implementing the DBD approach are raised. The focus of our study is on demonstrating the approach rather than the design results per se.

The challenge of designing next-generation systems that meet goals for system effectiveness, environmental compatibility, and cost has grown to the point that traditional design methodologies are becoming ineffective. Increases in the analysis complexity required, the number of objectives and constraints to be evaluated, and the multitude of uncertainties in today's design problems are primary drivers of this situation. A new environment for design has been formulated to treat this situation. It is viewed as a testbed, in which new techniques in such areas as design-oriented/physics-based analysis, uncertainty modeling, technology forecasting, system synthesis, and decision-making can be posed as hypotheses. Several recent advances in elements of this multidisciplinary environment, termed the Virtual Stochastic Life Cycle Design Environment, are summarized in this paper.

A platform is the set of elements and interfaces that are common to a family of products. We have previously presented a method for designing product families based on platforms that quantifies performance and cost metrics. That approach allows a team of engineers to design and evaluate candidate platforms, given perfect understanding of the designs and requirements. In this paper we present a model to account for uncertainty present during the development of those product families. Real options concepts are introduced to model the risks and delayed decision benefits present under uncertainty in technologies, funding, etc. We develop a quantitative measure of the value to the company for different family designs, and apply it to select the most appropriate design from the possible alternatives. An application to the design of platform-based families of spacecraft is shown. Results from the models indicated the platforms that were most valuable to the company under different scenarios, ...

In recent years, considerable research has been directed towards the development of methods for designing families of products. In this paper, we present a Variation-Based Platform Design Methodology (VBPDM), which aims to satisfy a range of performance requirements using the smallest variation of the product designs in the family. In the first stage of the VBPDM, the common product platform around which the product family is to be developed is identified. A ranged set of solutions is found, represented by the mean and standard deviation of the input design variables, to meet a range of the different performance requirements for the product family. During this first stage, a compromise Decision Support Problem (DSP) is used to optimize the commonality goal that seeks to minimize the deviation of the input design variables, while satisfying the range of performance requirements. Those design variables that show small deviations are held constant to form the product platform. In the seco...

Center for there assistance and guidance in completing this thesis and dissertation. Each provided a unique point of reference that helped me to improve the presentation of material and general readability. Additionally, I would like to thank Dr. Bryce Roth, Dani Soban, and Elena Garcia for there assistance over the course of this project, and Mr. Brian German for his assistance in assuring that the some of the more esoteric concepts contained within this thesis are understandable.

Product variants with similar architecture but different functional requirements may have common parts. We define a product family to be a set of such products, and refer to the set of common parts as the product platform. Product platforms enable rapid adjustment to changing market needs while keeping development costs and time-cycles low. In many cases, however, the individual product requirements are conflicting when designing a product family. The designer must balance the tradeoff between maximizing commonality and minimizing individual product performance deviations. The design challenge is to select the product platform that will generate family designs with minimum deviation from individual optima. We propose a methodology that combines two previous approaches developed for making commonality decisions. In the first approach optimal values and sensitivity information from the individually optimized variants are used to indicate components that are probable candidates for sharing. In the second approach a relaxed combinatorial problem is formulated to maximize sharing among variants subject to bounds on performance reduction for the individually optimized values. In the combined methodology the first approach is used to identify an initial set of shared components and define the candidate platform to be considered by the second approach. The computational load is reduced significantly and the platform-selection problem is solved in a more robust manner. The proposed methodology is demonstrated on the design of an automotive engine family.

Product/service family engineering, which encourages the development of a common product platform, plays a key role in facilitating large-scale and planned reuse in the development of customized products. In product family designs, managing points of variability is critical to achieve product variety. Variation points are points at which one among the several possible variations of a feature of a system can be selected to achieve different configurations of a product. We are developing an ontology that catalogues the different concepts associated with variability. This ontology is used to define the elements characterizing the knowledge elements necessary for managing variability in product/service families. We have also developed a knowledge management system integrated with an ontology development tool to facilitate knowledge capture and retrieval for variability management.

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This paper presents a knowledge-intensive support paradigm for platform-based product family design and development. The fundamental issues underlying the product family design and development, including product platform and product family modeling, product family generation and evolution, and product family evaluation for customization, are discussed. A module-based integrated design scheme is proposed with knowledge support for product family architecture modeling, product platform establishment, product family generation, and product variant assessment. A systematic methodology and the relevant technologies are investigated and developed for knowledge supported product family design process. The developed information and knowledge-modeling framework and prototype system can be used for platform product design knowledge capture, representation and management and offer on-line support for designers in the design process. The issues and requirements related to developing a knowledge-intensive support system for modular platform based product family design are also addressed.