Resource Allocation And Scheduling Optimization Of Processing Capability Sharing On Cloud Manufacturing Platform

With the rapid development of Cyber Physical Systems(CPS)and Industrial Internet of Things(IIoT)technologies,the basic industrial Internet connecting enterprises,machines,materials,people,and information systems have been established.Evolving a resource allocation model based on the sharing economy,a large number of application services,such as Manufacturing as a service(MaaS)/Data as a service(DaaS)used on cloud manufacturing platform(Cloud Manufacturing Platform,CMP)and the corresponding innovative business based on "Platform as a service(PaaS)".Innovative practice and related operational mechanism study of cloud manufacturing mode has been widely investigated in the fields of supply chain management and manufacturing management for a few years.How to build a logical model of the enterprise-level manufacturing execution system unified by the cloud platform under the actual cloud manufacturing operation scenario becomes the key.In order to improve the utilization efficiency of enterprise resource who participated in the sharing of cloud manufacturing platform,an input and output model is introduced,and the I/O-BOM-WBS model for decomposing cloud manufacturing demand orders into processing sub-orders is given.with the minimum chemical period as the scheduling target.In order to study multi-structures of resource service composition invloved in complex manufacturing task allocating problem under cloud manufacturing mode,find a way to improve the efficiency of platform-based enterprise resource allocation,a bi-level programming decision-making model of resource allocation is built under multi-attribute evaluation which included quality of service and flexibility factors,and then we designed a heuristic resource allocation algorithm,which proved the supply chain of cloud manufacturing pareto optimality.A cloud processing capabilities scheduling model based on platform and sharing-oriented is constructed with the minimization duration as the scheduling target and the minimization cost as constraint target.An improved second order particle swarm optimization algorithm is designed to solve optimal scheduling sequence,and an update strategy of the share ability window is proposed.A sample application finally verified the feasibility and validity of the whole scheduling and resource allocation mechanism.