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.
Highlights
With the development of cloud computing, big data, "Internet +", Internet of things, artificial intelligence and other emerging technologies, the manufacturing industry has changed from the previous single production model to a service-oriented, collaborative and intelligent cloud manufacturing model [1]
CASE STUDY AND RESULTS ANALYSIS a matching decision of manufacturing service resource in a new energy automobile was toke as a case
According to the specific manufacturing service tasks proposed by new energy automobile enterprises, the order of task importance was obtained using rough set theory, which could accelerate manufacturing service activities in the cloud environment
Summary
With the development of cloud computing, big data, "Internet +", Internet of things, artificial intelligence and other emerging technologies, the manufacturing industry has changed from the previous single production model to a service-oriented, collaborative and intelligent cloud manufacturing model [1]. Cloud manufacturing will improve production efficiency, and generate new product and service models in addition to traditional products, open up new growth space, and redefine the operation mode and competitiveness of manufacturing industry [2]. For manufacturing applications and business operations on the virtual cloud manufacturing systems, the resources and capabilities required by customers come from the large scale manufacturing cloud pool. The manufacturing resources and capability are integrated by cloud manufacturing, and virtualized to customers in the VOLUME XX, 2017.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
