AN APPROACH FOR DETERMINING THE COST MATRIX OF MULTIVARIATE QUALITY LOSS FUNCTION

Date

2020-11-01

Author

Dolgun, Leman Esra
Erişkin, Levent
Özkan, Gökçe
Köksal, Gülser

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

161
views

0
downloads

Multivariate quality loss functions are commonly used in product and process design parameter optimization, which involves simultaneous consideration of multiple responses in determination of the levels of design parameters that provide high quality performance. These functions are also used in statistical tolerancing and quality improvement decision making. This study investigates the bivariate loss function in terms of its ability to represent different values or preferences a decision maker may attribute to different settings of responses. Then, an interactive and evolutionary method for estimating parameters of the multivariate quality loss function is proposed. This method can be used for such functions regardless of the number of quality characteristics under consideration. It is shown that the method converges to the true underlying loss function after a few iterations even when the information provided by the decision maker contains certain degrees of errors.

URI

https://journals.sfu.ca/ijietap/index.php/ijie/article/view/6265
https://hdl.handle.net/11511/93948

Journal

International Journal Of Industrial Engineering-Theory Applications And Practice

Collections

Department of Industrial Engineering, Article

Suggestions

OpenMETU
Core

An Experimental comparison of linear regression methods used in multi-response design parameter optimization for their estimation and prediction errors Gökayaz, Gülten; Köksal, Gülser; Department of Industrial Engineering (2016) Product and process designers need to find most preferable settings of design parameters to simultaneously achieve multiple quality objectives based on some performance measures such as means and variances of quality characteristics. In these optimization studies, typically empirical models of such performance measures are utilized. These models are usually developed based on data collected through statistically designed experiments using linear regression methods such as Ordinary Least Squares (OLS), Weigh...
Multivariate quality loss function cost parameter estimation Köksal, Gülser; Dolgun, Leman Esra (2021-08-23) In this study, we consider estimating the cost matrix parameters of the multivariate quality loss function which is commonly used in product and process design parameter optimization. Multivariate quality loss functions consider multiple responses simultaneously for determining the optimal levels of design parameters that yield a high-quality performance. They are also used in quality improvement decision making and statistical tolerancing. To that end, we propose an interactive and evolutionary method for ...
A reformulation of the ant colony optimization algorithm for large scale structural optimization Hasançebi, Oğuzhan; Saka, M.p. (2011-01-01) This study intends to improve performance of ant colony optimization (ACO) method for structural optimization problems particularly with many design variables or when design variables are chosen from large discrete sets. The algorithm developed with ACO method employs the so-called pheromone scaling approach to overcome entrapment of the search in a poor local optimum and thus to recover efficiency of the method for large-scale optimization problems. Besides, a new formulation is proposed for the local upda...
An Interactive approach to two-response product and process design optimization with statistical inferences Özateş, Melis; Köksal, Gülser; Köksalan, Murat; Department of Industrial Engineering (2015) In this study, an interactive approach has been developed for two-response product and process design optimization problems treating the single response problems as a special case. This approach considers preferences of the decision maker explicitly and the correlation between the responses. It uses a predefined set of objectives that are commonly encountered in the literature and industrial applications. However, instead of presenting all objective values at each iteration, a set of performance measures ar...
An Interactive Approach To Design Parameter Optimization Considering Response Surface Prediction Errors Özateş, Melis; Köksal, Gülser; Köksalan, Mustafa Murat (null; 2016-11-15) An interactive approach is presented for finding parameter settings of a product or process design that allows achieving targets for two responses as well as robustness. The approach utilizes response surface models and it allows the decision maker to consider magnitude of prediction errors in choosing the design solution.

Citation Formats

L. E. Dolgun, L. Erişkin, G. Özkan, and G. Köksal, “AN APPROACH FOR DETERMINING THE COST MATRIX OF MULTIVARIATE QUALITY LOSS FUNCTION,” International Journal Of Industrial Engineering-Theory Applications And Practice, vol. 27, no. 6, pp. 879–905, 2020, Accessed: 00, 2021. [Online]. Available: https://journals.sfu.ca/ijietap/index.php/ijie/article/view/6265.