QFD-Based Product Design for Multisegment Markets: A Fuzzy Chance-Constrained Programming Approach

Abstract

Modern companies are moving rapidly toward more customer-oriented approaches for new product design and development. In real-world applications, customer requirements are more diverse and rather heterogeneous in practice, which requires the targeted market to be multisegmented. In this article, employing the quality function deployment (QFD) and assuming that parameter uncertainty exists, we propose a new fuzzy QFD model for use in multisegment markets, to search for optimal engineering characteristics by maximizing the overall customer satisfaction score. Under that framework, and when the credibility measure is employed, we adopt a fuzzy chance-constrained programming setting to convert the fuzzy model into its crisp counterpart. Afterwards, an analytical method based on fuzzy operational law is proposed to further transform the chance-constrained programming into an equivalent explicit model that can be solved directly by a standard commercial software. For a targeted group of customers, a new yoghurt design is presented to illustrate the effectiveness and superiority of our treatment. We report that our methodology not only permits the selection of the preferred solution based on an acceptable level of risk, which is very important in practice, but also guarantees higher customer satisfaction scores. This fact extends the fuzzy QFD methodology to a wider range of applications.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 23 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.