Research On Cross-organizational Resource Service Chain Monitoring And Scheduling

Cross-organizational collaborative manufacturing based on integration ofresources sharing and optimized configuration, make the enterprise in the face of theglobal economic competition, integration advantage resources, fast response to marketdemand changes, win the market competition for manufacturing enterprise has veryimportant strategic significance. The article combined with the national naturalscience fund project named "Research on construction and operation ofcross-organizational resources service chain of Timing constraints associatedcollaborative manufacturing’s task drive (71271192)" and zhejiang province naturalscience fund project "Research on construction and operation of cross-organizationalcollaborative manufacturing task chain drive resource service chain(LY12G01008)",the key technical problems in cross-organizational collaborative manufacturing formore in-depth research and analysis. In this paper, the main researches are shown asfollows:(1) Expound the research background of cross-organizational resource servicechain, and analyze the domestic and foreign of cross-organizational resource servicechain construction and operation of the current research status, and the basic theoryand algorithm of cross-organizational resource service chain has carried on the briefoverview.(2) It analyzed the process of the construction of the cross-organizationalresource service chain, put forward the evaluation indicator on time, cost, serviceability, and establish the corresponding mathematical model, through the improvedbinary particle swarm optimization algorithm(PSO) to solve, so as to select the bestcandidate resources constitute a global optimal cross-organizational resource servicechain.(3) Because of cross-organizational collaborative manufacturing resource tasksare loosely coupled, dynamic and changeful, may be some emergency resourceservice cannot normal execution. So the article research on the monitoring of cross-organizational resource service chain, based on the QoS parameters of thesemantic Web service chain across organizational resources monitoring methods,select the resource service QoS parameters in time, cost, availability and credibility asthe monitoring indicators. Data acquisition and preprocessing of each indicator, and toevaluate QoS parameters based on time series prediction, in order to realize themonitoring of cross-organizational resource service chain.(4) In cross-organizational resource service chain service, if a resource cannotnormal execution, it will be dealt with production scheduling. The paper proposes twoplans that alternative scheduling and collaborative scheduling, based on the optimalmathematical model of the time and cost, and use the improved binary particle swarmoptimization algorithm to solve and choose the optimal cross-organizational resourceservice chain scheduling scheme.(5) The article studies on cross-organizational resource service chain serviceconstruction, monitoring and scheduling simulation experiment and analysis, by theanalysis of experimental results, proved that the mathematical model built in thispaper and the solving algorithm is effective and feasible.