A concept evaluation approach based on incomplete information: Considering large-scale criteria and risk attitudes

Dou, Yubo; Jing, Liting; Cai, Xionghui; Lu, Chunfu; Lv, Ting; Jiang, Shaofei

doi:10.1016/j.aei.2023.102234

Cited by 4 publications

(1 citation statement)

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“…These factors can generate a negative impact on the evaluation process and the results of design concept. Therefore, how to eliminate information ambiguity is an important issue in product concept design evaluation 3 .…”

Section: Introductionmentioning

confidence: 99%

An integrated design concept evaluation model based on interval valued picture fuzzy set and improved GRP method

Ma,

Chen,

Tan

et al. 2024

Sci Rep

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The objective of this research is to enhance the precision and efficiency of design concept assessments during the initial stages of new product creation. Design concept evaluation, which occurs at the end of the conceptual design phase, is a critical step in product development. The outcome of this evaluation significantly impacts the product's eventual success, as flawed design concepts are difficult to remedy in later stages. However, the evaluation of new product concepts is a procedure that encompasses elements of subjectivity and ambiguity. In order to deal with the problem, a novel decision-making method for choosing more logical new product concepts is introduced. Basically, the evaluation process is outlined in three main phases: the construction of evaluation index system for design concept alternatives, the calculation of weights for evaluation criteria and decision-makers, the selection of the best design concept alternatives. These stages are composed of a hybrid method based on kano model, multiplicative analytic hierarchy process (AHP) method, the entropy of IVPFS and improved grey relational projection (GRP) under interval-valued picture fuzzy set (IVPFS). The novel approach integrates the strength of interval-valued picture fuzzy number in handling vagueness, the advantage of multiplicative AHP and the merit of improved GRP method in modelling multi-criteria decision-making. In final, the effectiveness of the proposed model is validated through comparisons with other models. The potential applications of this study include but are not limited to product development, industrial design, and innovation management, providing decision-makers with a more accurate and comprehensive design concept evaluation tool.

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Section: Introductionmentioning

confidence: 99%