A Fuzzy Modelling Approach to Robust Design via Loss Functions

Yıl 2017, Cilt: 01 Sayı: 2, 40 - 45, 29.12.2017

Melis Zeybek , Onur Köksoy

Öz

Especially in a world where
industrial development is reinforced by globalization tendencies, competitive
companies know that satisfying customers' needs and running a successful
operation requires a process that is reliable, predictable and robust.
Therefore, many of quality improvement techniques focus on reducing process
variation in line with the “loss to society” concept. The upside-down normal
loss function is a weighted loss function that has the ability to evaluate
losses with a more reasonable risk assessment. In this study, we introduce a
fuzzy modelling approach based on expected upside-down normal loss function
where the mean and standard deviation responses are fitted by response surface
models. The proposed method aims to identify a set of operating conditions to
maximize the degree of satisfaction with respect to the expected loss.
Additionally, the proposed approach provides a more informative and realistic
approach for comparing competing sets of conditions depending upon how much
better or worse a process is. We demonstrate the proposed approach in a
well-known design of experiment by comparing it with existing methods.

Anahtar Kelimeler

fuzzy modeling, response surface methodology, robust parameter design, upside-down normal loss function

Kaynakça

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