"Demand-based configuration of modular product architecture" by Benoit George Gauthier Jr.

Date of Award

2002

Degree Type

Dissertation

First Advisor

Manbir Sodhi

Second Advisor

Peter Dewhurst

Abstract

A framework is presented for development of appropriately partitioned modular product architectures tailored both to market variance and to production economics. Beginning with a market assessment, product attribute requirements are arrayed to illustrate and derive priority ratings based on commonality and diversity in demand, and potential revenue from the respective clients. Market attribute information is converted to product specifications using existing methods in quality function deployment, with restrictions in areas of concern with this method, including the need for improved fidelity of product representation, and the validity of additive contribution of design parameters to satisfy design requirements. Candidate product architecture is then developed using existing methods in function-structure networks, with the function structure be developed first for the simplest complete product involving common high priority design parameters. Following this, features may be added to the network for variant products beginning with the externalities of the network that correspond to variant design attributes. Compatibility criteria are presented to merge the variant nodes and flows to the existing function structure network. This network construction technique is proposed as a more efficient alternative to current methods, which create a union network from complete networks of individual products. The product family architecture partitioning decision is conducted using existing heuristics for initial candidate module identification, aided by a new selection tool that considers the economics of production. This tool is used iteratively to groom the product family function-structure network architecture and aid selection decisions on module partitioning with the objective of profitably serving the greatest range of customers. The method concludes by transferring the component, interface, and partition data from the QFD and Function-structure formats into a detailed interface optimization problem, in a collaborative optimization construct. Examples are presented both for the optimization tool development and to illustrate the flow and translation of design information using this framework.

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