Using analytic hierarchy process to determine process economics in multivariate loss functions

Performance of a product usually depends on several responses (quality characteristics) which must meet all of the specifications simultaneously. This could be achieved by applying of (the) robust design methodology to problems with multiple characteristics. In the literature, several works have been published concerning multi-response optimization methods, which aim to achieve the best possible robustness. One of the approaches for multi-response optimization is Loss Function Approach which allows the practitioner to include variance–covariance structure of the responses, prediction quality and the economic importance of the responses relevant to the product or process. In this paper, we propose utilizing Analytic Hierarchy Process, a multi-criteria decision making tool, to determine the economic importance matrix in the multivariate loss function.