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Issue title: Meta-Heuristic Techniques for Solving Computational Engineering Problems: Challenges and New Research Directions
Guest editors: Suresh Chandra Satapathy, Rashmi Agrawal and Vicente García Díaz
Article type: Research Article
Authors: Cheng, Yuan | Wang, Kunqian; *
Affiliations: Faculty of Art and Communication, Kun Ming University of Science and Technology, Kunming Yunnan, China
Correspondence: [*] Corresponding author. Kunqian Wang, Faculty of Art and Communication, Kun Ming University of Science and Technology, Kunming Yunnan, 650093, China. E-mail: 11303087@kust.edu.cn.
Abstract: Small and medium-sized manufacturing enterprises have the characteristics of large numbers and small scales. Problems such as backward manufacturing technology, lack of talents, small amount of information resources, and insufficient product research and development capabilities have severely restricted the development of enterprises. The backward manufacturing design model cannot adapt to the development trend of modern manufacturing informatization. This paper proposes and designs a fuzzy inference model and fuzzy inference engine algorithm with threshold. In order to describe the numerical multiple input and multiple output variables in the industrial manufacturing design industry, the relevant experience is used to make numerical reasoning decisions. Applying fuzzy sets and fuzzy theory to the expert system, a fuzzy rule model containing the membership function information and thresholds of the corresponding fuzzy sets is proposed and established, and a fuzzy reasoning system suitable for numerical and uncertain reasoning decisions is constructed. The improved grey relational analysis method is used to decompose and evaluate the exponential mathematical quantitative process of manufacturing enterprises. Based on the fuzzy Decision Analytic Network Process (DANP) method to calculate the relative weight of the influencing factors in the evaluation system, the evaluation index of the enterprise is obtained. Starting from the industrial manufacturing design process, this article constructs a relatively comprehensive and reasonable enterprise exponential mathematical quantitative process decomposition evaluation system. Considering that there are complex interactions between the various influencing factors in the system, the fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) method is selected to process the direct impact matrix of the evaluation system, and the causal relationship between the indicators is obtained. The fuzzy exponential gray correlation method is used to evaluate the quantitative process of industrial manufacturing design, avoiding the shortcomings of traditional methods that only consider ideal values.
Keywords: Industrial manufacturing design, quantitative process decomposition, DANP, fuzzy reasoning
DOI: 10.3233/JIFS-189445
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6059-6068, 2021
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