Open accessJournal Article

# A Multidimensional Information Fusion-Based Matching Decision Method for Manufacturing Service Resource

02 Mar 2021-IEEE Access (IEEE)-Vol. 9, pp 39839-39851
Abstract: With the development of specialization, coordination and intelligence in the manufacturing service process, the issue of how to quickly extract potential resources or capabilities for distributed manufacturing service requirements, and how to carry out resource matching for manufacturing service requirements with correlated mapping characteristics, have become the critical issues to be addressed in the cloud manufacturing environment. Through the combination of the characteristics of relevance, synergy and diversity of manufacturing service tasks on the intelligent cloud platform, a matching decision method for manufacturing service resources is proposed in this paper based on multidimensional information fusion. On the basis of integrating multidimensional information data in cloud manufacturing resource, the information entropy and rough set theory are applied to classify the importance of manufacturing service tasks, while the matching capability are analyzed by using a hybrid collaborative filtering (HCF) algorithm. Then, the information of function attribute, reliability and preference is employed to match and push manufacturing service resources or capabilities actively, so as to realize the matching decision of manufacturing service resources with precise quality, stable service and maximum efficiency. At last, a case study of resources matching decision for body & chassis manufacturing service in a new energy automobile enterprise is presented, in which the experimental results show that the proposed approach is more accuracy and effective compared with other different recommendation algorithms.

Topics: Cloud manufacturing (74%), ,  ... read more
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Sankar Kumar Roy1, Jishu Jana1Institutions (1)
Abstract: The hesitant fuzzy set (HFS) is a very fruitful mathematical approach to deal with uncertain or imprecise information. In this work, we consider a multi-objective linear production planning (MOLPP) problem in which multiple decision makers pool resources to make various products and analyze them with the help of cooperative game theory. It can be formulated as a mathematical programming problem with triangular hesitant fuzzy (THF) parameters. The main aim of this paper is to analyze the MOLPP problem in THF environment. In view of realistic sense we choose the coefficients of multi-objective linear production planning game (MOLPPG) as triangular hesitant fuzzy numbers (THFNs), and hereby it is referred to as THF-MOLPPG. The THF-MOLPPG is converted to fuzzy MOLPPG by taking an average aggregation operator (AAO) of the THFNs. Thereafter we consider $$\alpha$$ -cut of a fuzzy number to obtain MOLPPG with interval parameters. Two approaches, namely weighted sum method (WSM) and extended technique for order preference by similarity to ideal solution (TOPSIS), are chosen to obtain the optimal strategy and payoff vectors of the players to the MOLPPG. For solving MOLPPG, we apply WSM and extended TOPSIS by considering the various values of $$\alpha$$ for finding the value of the game in such a way that the total income is maximized. A comparison is drawn among the payoff vectors, which are determined from the approaches. Finally, the applicability and feasibility of the proposed methods are illustrated by a numerical example. WSM and extended TOPSIS provide better results at the values $$\alpha = 0.3$$ and $$\alpha =0.9$$ , respectively, for the proposed problem. From the results, we infer that TOPSIS is far better than WSM of the proposed problem. Also, the conclusions and outlooks of the paper are delineated.

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