The Method Based On Ontology For The Servitization Of Manufacture Resource And The Banlancing Optimization Of Its Service Capability

As the informatization of manufacturing industry is developing rapidly, the problem,about how to improve the utilization of the manufacturing resources, has become to themost important one to be focus on and resolved. The CMfg (Cloud Manufacturing)provides a new way to resolve the two problems. This paper is focusing on theservitization of the manufacturing resources and the optimization method of the servicecapability in the CMfg.By studying the manufacturing process, a unified description of the classificationand properties characterization about the manufacturing resources is made. Based on thedescription, a model of the servitization of the manufacturing resources, composed ofthree steps known as the virtualizing, the clustering and the servitization, is established.And then, the manufacturing resources are abstracted as the manufacturing servicesexpressed by the ontology.This paper made a rigorous definition, the classification and the quantification of themanufacturing service capability. Based on the manufacturing service process, the NLWmodel of the manufacturing resource service is designed, and, a computational model ofthe service capability is also founded. Plus, combined the characteristics of MTO (Maketo Order) manufacturing service, the paper proposed a plan of the manufacturing servicecapability. Firstly, decompose the requirements of the manufacturing service, and then,combined the NLW model and the computational model, generate the manufacturingservice capability plan through the requirements.Get deep into the MTO manufacturing service, a balancing optimization model ofthe manufacturing service capability is established to solve the problem about themultiple orders’ production scheduling, this the purpose of improving the matching rateof the order and the utilization of the manufacturing service. To make the standard PSOalgorithm is usable for the model, the algorithm is redefined and redesigned to meet thetwo requirements, discrete solving and multi-objective solving.The experiments prove that the discretization method is feasible, and the balancingoptimization model of multi-objective problem can guarantee an optimized capabilityplan in a shorter time, at the same time, the utilization of the orders and the matching rateof the manufacturing services are higher. Finally, a small manufacturing resource servicecapability management system is designed and programmed by synthesizing all thetheories mentioned above.