Technical decomposition approach of critical to quality characteristics for Product Design for Six Sigma

Abstract

Product Design for Six Sigma (DFSS) approach is a structural and disciplined methodology driven by critical to quality characteristics (CTQs). How to identify and decompose the CTQs is the kernel part in the DFSS process. Traditional method only depends on the quality function deployment (QFD) matrix to flow down CTQs roughly. The paper puts forward a novel technical approach for CTQs decomposition from customer requirements into critical technical parameters based on the relational tree. Specifically, this approach emphasizes the systematic process and quantitative computation on quality relation weight. In order to specify the object of product DFSS, the connotation and evolution model of CTQs are created first. Then along the product development process, a decomposition measure for relational tree of CTQs is studied based on the functional and physical trees in Axiomatic Design (AD). And the quality relation weight computation of its nodes by means of Rough Set and fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is explored. Finally, an application on a car body noise vibration harshness (NVH) improvement, as an example, is given, and the decomposition process of NVH related with the functional and physical trees as well as its node weights computation algorithm are expounded in detail.

A Decision Support System for Solving Multi‐Objective Redundancy Allocation Problems

“…The TOPSIS method has been widely used for failure mode and effects analysis, [35][36][37] crisis management, 38,39 and quality control. [40][41][42]…”

Práticas para a melhoria contínua do Processo de Desenvolvimento de Produtos: análise comparativa de múltiplos casos

“…Both approaches emphasize creating value for customers, in order to reduce waste, process vulnerabilities, development time and increase the quality of the final product (Fouquet, 2007;Gremyr & Fouquet, 2012). The DFSS proposes a model based on standardized PDP stages and gates, focusing on the critical features for quality and use statistical tools for analysis and measurement of product and process to meet the specifications and tolerances (Fouquet, 2007;He et al, 2010;Gremyr & Fouquet, 2012).…”

Identification of CTQs for Complex Products Based on Mutual Information and Improved Gravitational Search Algorithm

“…For CTQs of design, the design team identifies the voice of the customer (VOC) and determines the CTQs from engineering characteristics based on the relationship of VOCs and engineering characteristics. The typical method of CTQs identification is quality function deployment (QFD) [5,6]. QFD provides a means of translating customer requirements into the appropriate technical requirements for each stage of product development and production [7].…”

“…For example, Zhang et al established a multiple CTQs optimization model by using QFD technology and successfully extracted various influencing factors for multiple quality characteristics [8]. He et al put forward an approach to CTQs decomposition from customer requirements into critical technical parameters based on the relational tree [6]. Thornton distinguishes importance degree of obtained characteristics through adding process data [4,9].…”