Research On Manufacturing Resource Service Optimization Considering Tripartite Benefit Under Cloud Manufacturing

As a new way of intelligent manufacturing,cloud manufacturing can realize the sharing of mass manufacturing resources and services across fields and regions.While improving the utilization of resources,it also urges enterprises to pay more attention to the development of core competitiveness,so as to improve the production quality of the industry.The optimization of manufacturing resources under cloud manufacturing is the process of selecting the optimal task solution for enterprises after the manufacturing resources are virtualized into manufacturing services.The optimization result will directly affect the implementation effect of cloud manufacturing.Most of the existing studies do not fully consider the interests of all participants,so that the established evaluation index system is not perfect,and the built model is unable to ensure the effect of the overall optimization process due to the lack of consideration of the dynamic characteristics of cloud manufacturing.Aiming at the above shortcomings,this paper studies the optimization method of manufacturing resource services,and mainly carries out the following research work:Firstly,the relevant theories of cloud manufacturing are deeply studied,the manufacturing tasks under cloud manufacturing are divided into simple tasks and complex tasks,and the optimization process of single manufacturing resource and manufacturing resource service combination is analyzed in detail.Secondly,according to the direct task resource matching characteristics of simple tasks,based on the interests of the demand side,the service side and the platform side,a manufacturing resource evaluation index system including the interests of the three parties is established.The cloud model theory is introduced to quantify the qualitative indexes in the evaluation process.After obtaining the weight of each index by using F-AHP,a simple task manufacturing resource service optimization model based on cloud model is established to rank the candidate manufacturing resource sets.Then,according to the characteristics of task decomposition and resource service combination of complex tasks,fully consider the impact of demand change and resource change on task completion,establish the optimization index system of complex task manufacturing resource service combination including service quality index of both supply and demand sides and cloud platform flexibility index,and construct a bilevel programming mathematical model.Based on the introduction of time decay function to determine the satisfaction of both supply and demand,the optimization of cloud manufacturing resource service combination for complex tasks is realized.Finally,the model built in this paper is verified by a specific example.The results show that the cloud manufacturing resource evaluation model based on cloud model can sort the candidate manufacturing resource sets of simple tasks according to their advantages and disadvantages,and complete the optimization of cloud manufacturing resource services on the basis of reducing the impact of the fuzziness of qualitative indicators on the evaluation results.On the premise of satisfying the satisfaction of both the supplier and the demander,the optimization of manufacturing resource service combination for complex tasks can reduce the rejection rate of the recommended combination of the platform by both the supplier and the demander and improve the efficiency of resource matching.The bilevel programming model not only has an effect on the dynamic characteristics of cloud manufacturing,but also improves the speed and quality of optimization.Therefore,the optimization of manufacturing resource services considering the interests of three parties under cloud manufacturing can ensure the efficient completion of tasks on the basis of meeting the interests of all participants,and provide a theoretical reference for the development and promotion of cloud manufacturing system.