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Research On Machining Service Modes And Service Optimal Scheduling In Cloud Manufacturing

Posted on:2017-09-09Degree:MasterType:Thesis
Country:ChinaCandidate:Y CaoFull Text:PDF
GTID:2348330503465645Subject:Mechanical and electrical engineering
Abstract/Summary:
Cloud manufacturing(CMfg) is a new networked manufacturing model that based on the idea of “Manufacturing as a Service” and inspired by the thought of cloud computing. In the CMfg system, manufacturing resources are inserted into the network, and virtualized and encapsulated into whole product life-cycle manufacturing services. CMfg is able to realize manufacturing resources sharing within larger area, and in a more convenient, higher efficiency and cheaper way. Under the background of significant adjustments in global industrial situations, CMfg enlightens a new solution for the development of the manufacturing industry in China.Since the proposal of CMfg, domestic and foreign scholars have conducted comprehensive and in-depth research about its definitions and theoretical structures. However, with respect to the machining field, it lacks a feasible CMfg service mode. This paper proposes a “PMS+WPMS” prime machining collaboration mode based on the analysis of the current situations of the manufacturing industry, researches related manufacturing resources integration methods and the ontology information description model of manufacturing services, and expands the prime collaboration mode to a complete CMfg service system.Service optimal scheduling is a key problem in the CMfg system, which directly affects the performance of the CMfg platform. Although the research of resources selection and production scheduling in traditional manufacturing systems is much mature, the constructed models generally do not apply to the CMfg system. This paper constructs a CMfg service optimal scheduling model based on the analysis of the new characteristics of CMfg service optimal scheduling, builds the optimization function by considering criteria time, quality, cost and service, and then designs a novel ACOS algorithm to solve the model. Simulation experiment results have validated the feasibility of the proposed model and the effectiveness of the algorithm.Lastly, based on the previous theoretical work, the author developed a CMfg prototype service platform using ASP.NET and Microsoft SQL Server. The platform’s business logic, function modules and development tools are introduced, and the database design solution is provided and some business pages are displayed.
Keywords/Search Tags:Cloud manufacturing(CMfg), Machining, Service mode, Service optimal scheduling, CMfg service platform
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