Affiliation:
1. Department of Intelligent Production Engineering, National Taichung University of Science and Technology, Taichung
Abstract
Amidst fierce competition and diversifying customer needs in today’s markets, product development and design have shifted toward a more user-oriented model. This makes it common for products to have multiple quality characteristics. However, simply meeting customer needs is no longer sufficient; quality is also a key factor of a consumer’s willingness to buy a product. To this end, process capability indices have been used to measure the relationship between manufacturing specifications and processing performance, as well as serve as a bridge of communication between manufacturers and clients. In view of this, the loss-based capability index [Formula: see text] that fully reflects process loss and yield is employed in this study to analyze the process performance of each quality characteristic. However, [Formula: see text] must be estimated based on collected samples, in which the measured values of all sample data are expressed with precise values. Uncertainty and imprecision in collected data increase the risk of misjudgment. To reduce this risk, the [Formula: see text] confidence interval of [Formula: see text] is first derived to define fuzzy estimations of both the critical value and index, and develop a fuzzy process capability analysis model for a machined product with multiple quality characteristics of symmetric tolerance. Finally, an industrial example involving a five-way pipe product is presented to illustrate the applicability of the proposed approach. The results show that the proposed fuzzy analysis model makes determination of the process capability of each quality characteristic more reliable and rigorous to ensure that manufactured products meet requirements.
Subject
Industrial and Manufacturing Engineering,Mechanical Engineering
Cited by
4 articles.
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