New Framework for Quality Function Deployment Using Linguistic Z-Numbers

Abstract

Quality function deployment (QFD) is a useful design quality control tool in service enterprises and manufacturing enterprises. However, there are several issues in extant QFD frameworks, that is, in three aspects: description of evaluation information, weight determination of expert team members (TMs), and weight identification of customer requirements (CRs). In order to address these issues, a novel QFD framework is first proposed utilizing linguistic Z-numbers (LZNs) with integrated subjective and objective weights of TMs and CRs. The LZNs can represent uncertain information and the reliability of information in a specific way while the fuzzy numbers cannot. Moreover, the order relation analysis (G1) method and improved maximum consensus (MC) method are developed to get the subjective and objective weights of TMs, respectively. Further, the step-wise weight assessment ratio analysis (SWARA) method and statistical distance (SD) method are studied to acquire combined weights of CRs. Next, the proposed QFD framework is applied to a case of logistics service provider, which illustrates the availability and utility of the framework. Then, a sensitivity analysis is conducted to prove the reliability of the framework. Finally, two comparative analyses are performed to declare the advantages of the framework. Results indicate the proposed QFD framework is better than existing models.

A Multi-Criteria Decision Support Framework for Inland Nuclear Power Plant Site Selection under Z-Information: A Case Study in Hunan Province of China

“…Several studies have shown that information is not completely reliable in many MCDM processes [10][11][12]. Especially in the problem with complex information source and subjective evaluation information, a large amount of incomplete reliable information exists [13]. Z-number is a new concept integrating both cognitive information and the reliability of information, produced by Zadeh in 2011 [14].…”

Supplier Selection in the Nuclear Power Industry with an Integrated ANP-TODIM Method under Z-Number Circumstances

“…In order to address this problem, Zadeh [21] proposed the Z-number to describe the reliability of information, and it can better capture the expression nature of experts. Owing to its superiority and availability, the Z-number has been widely used in logistics service provider selection [22], economy development program selection [23], hospital performance management [24], and so on, but its application in supplier selection is not common yet. In this work, the Z-number is introduced to handle the uncertainty of decision-making, in order to determine the optimal nuclear power equipment supplier.…”

A Distinctive Symmetric Analyzation of Improving Air Quality Using Multi-Criteria Decision Making Method under Uncertainty Conditions

“…Casanovas-Rubio et al [27] developed a method for assessing the sustainability of trenches based on the MIVES decision-making method. Chao Song et al [28] explore the structure of Quality Function Deployment (QFD) using linguistic Z-numbers (LZNs) and integrate the weights of expert team members and customer needs. Here, Step Wise Weight Assessment Ratio Analysis (SWARA) and Standard Deviation (SD) methods are presented to get the subjective and objective weights of customer needs.…”