Multivariate tolerance design using quality loss

Multivariate tolerance design using quality loss

0.00 Avg rating0 Votes
Article ID: iaor20022245
Country: United States
Volume: 33
Issue: 6
Start Page Number: 437
End Page Number: 448
Publication Date: Jun 2001
Journal: IIE Transactions
Authors: , ,
Keywords: design
Abstract:

The determination of tolerance allocations among design parameters is an integral phase of product/process design. Such allocations are often necessary to achieve desired levels of product performance. We extend our prior research on tolerance allocation by developing both parametric and nonparametric methods for a multivariate set of performance measures that are functions of a common set of design parameters. The parametric method is novel and assumes full information about the probability distribution of design parameter processes. The proposed nonparametric method assumes that only partial information is available and significantly extends prior research by considering a more contemporary and realistic model for manufacturer costs. For both methods we derive economically based models that represent the costs, both internal (supplier) and external (manufacturer), of tolerance allocation under several different process scenarios. These scenarios are based on the manner of disposition of non-conforming product. For the parametric methods we derive tolerance allocation solutions that jointly minimize expected total cost of the supplier and manufacturer. For the nonparametric methods we derive solutions for tolerance allocation that jointly minimizes the maximum expected total cost. An example in the fabrication of a rubber tread compound is used to: (i) demonstrate the implementation of our proposed methodologies for tolerance allocation: (ii) illustrate and compare the nonparametric and parametric methods; and (iii) assess the sensitivity of optimal tolerance allocations to changes in process model types, cost coefficient estimates, and manner of disposition of nonconforming products.

Reviews

Required fields are marked *. Your email address will not be published.