New customer-oriented design concept evaluation by using improved Z-number-based multi-criteria decision-making method. (August 2022)

• Record Type: Journal Article
• Authors: Qi, Jin; Hu, Jie; Huang, Haiqing; Peng, Yinghong
• Is Part Of: Advanced engineering informatics. Volume 53(2022)
• Publication Date: 2022-08
• Subjects: Design concept evaluation -- Customer preference -- Z-number -- Ideal solution selection -- Multi-criteria decision-making; Computer-aided engineering -- Periodicals; Engineering -- Data processing -- Periodicals; 620.00285
• DOI: 10.1016/j.aei.2022.101683
• Languages: English
• ISSNs: 1474-0346

Abstract

Highlights: Presenting Z-opinion to express customer's uncertain opinion. Proposing new ideal solution selection way integrating with multi-information. More reasonable concept is selected by considering PV, PR and DAI information. This method supports different MCDM-based evaluation models. This method's superiority is validated by application and empirical comparisons. Abstract: The customer-oriented design concept evaluation (CDCE) enables companies to select the best design concept from the perspective of customer to win the customer-centered market. However, previous CDCE studies only focus on the customer's preference value (PV), but neglect the customer's confidence attitude on this preference, i.e., the preference reliability (PR), and some design specifications, e.g., the design attribute's importance (DAI). To address such drawbacks, we propose a new CDCE by using improved Z-number-based multi-criteria decision-making (IZ-MCDM) method to better express and utilize customer's uncertain opinion. In IZ-MCDM, the Z-number is used to express the customer's opinion (Z-opinion) that includes PV and its affiliated PR information. Z-opinion is translated into an interval Z-number to form a new type of evaluation value and decision matrix. Based on the evaluation value, a new ideal solution selection (ISS) strategy integrating with PV, PR and DAI information is employed in IZ-MCDM. By comparing with the re-defined ideal solution, the alternative that attracts certain high-preferences for its importance attribute values and uncertain low-preferences for its less importance attribute values is more likely to be recommended as the best one. Hence, IZ-MCDM can get more reasonable design concept than classical PV-only CDCE method. Two empirical experiments from existing CDCE examples have been carried out in this study, and the comparison experimental results further validate the significance of IZ-MCDM, which show that 1) besides PV factor, PR and DAI factors could also significantly impact the evaluation result; 2) these two factors should be acted together to select the ideal solution; 3) IZ-MCDM has suitability as it supports different MCDM models with different deviation measurement metrics to evaluate the alternatives.