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A dual‐response surface modeling approach for gamma robust design
Author(s) -
Zeybek Melis,
Köksoy Onur,
Robinson Timothy J.
Publication year - 2020
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.2575
Subject(s) - dual (grammatical number) , computer science , process (computing) , design of experiments , quality (philosophy) , gamma distribution , reliability engineering , mathematical optimization , engineering , mathematics , statistics , art , philosophy , literature , epistemology , operating system
Robust parameter design is a methodology that involves experimental design and strategic modeling for the purpose of simultaneously reducing system variability while achieving a target specification for the system mean. Modeling results obtained under unrealistic assumptions about the underlying data distribution may mislead practitioners when it comes to improving system quality. Using classical normal theory modeling techniques for right‐skewed experimental data in dual‐response modeling has some drawbacks, such as obtaining a misleading fit and estimated optimal operating conditions that are potentially far from the true optimal values. Moreover, using inappropriate modeling methods can create a chain of degradation in the production phase and subsequently result in poor system performance. This paper proposes a new dual‐response surface modeling approach when the quality characteristic of a system follows a gamma distribution. The procedure and its advantages are illustrated using the well‐known printing process experiment.