Optimization Technologies Of Manufacturing Execution System In Cloudy Manufacturing And Applications In Machine Production Enterprise

With the rapid development of manufacturing industry, manufacturing execution system has become one of the most important keys of using manufacturing resources and improving the ability of rapid response to market. In the cloudy manufacturing environment, part case retrieval method, manufacturing resources management and allocation, production planning and scheudling are studied. Part case retrieval method based on CBR, flexible manufacturing cell formation approach based on PSO algorithm, integrated method of machining and assembly planning and scheduling based on JIT and multi-objective optimization method of flexible job-shop lot-splitting scheduling based on SPEA are put forward and applied in the machine equipment production, and good effects are obtained.The main works are as follows:The first chapter reviews the hierarchy, fuctions and research status of manufacturing execution system, expounds the status, development trend and technology of manufacturing industry and the characteristic of cloudy manufacturing. By analyzing the shortage of existing manufacturing execution system in cloudy manufacturing environment, the research contents and technical route are presented.The chapter 2 puts forwards part case retrieval method based on CBR and expounds the research status of part case retrieval, the classifying principle of part features, recognition method and technology of part features. By analyzing the comparability and similarity of parts form features, the methond of similarity calculation of parts form and geometry in mulriple feature layer, basic characteristic layer and simple feature layer is put forward. A multi-level part case retrieval method is proposed based on CBR. The similarity is calculated with three stages analysis between a new part and old parts in the case library.The chapter 3 puts forward flexible manufacturing cell formation approach based on PSO algorithm. Manufacturing resource formation methods in different manufacturing environment are analyzed. Flexible manufacturing cell model integrating with the advantages of physical manufacturing cell (PMC) and logical manufacturing cell (LMC) in the open shops in cloudy manufacturing with changeable resources layout is set up. Mainly considsing three factors: machine layout, routing and production lot sizing, based on PSO algorithm, manufacturing cell formation algorithm is proposed to minimize total manufacturing cost.The chapter 4 puts forward integrated method of machining and assembly planning and scheduling based on JIT. The research status of production planning and scheduling is analyzed, the restriction, characteristic, key problem and method of production planning and scheduling are expounded. An integrated model of machining and assembly planning and scheduling is constructed in order to deal with manufacturing in a JIT production system of MTO enterprise for delivery just-in-time. Function objective of the proposed model is to guarantee the due dates of production. Restraint functions include machining capacity, assembly capacity, machining and assembly procedures restraints. Feasible planning can be set down considering these restraints. To build up two level mixed programming model, a hybrid heuristic algorithm based on genetic algorithm and heuristics rules is put forward. Integrated model is used in a shop of a MTO company. By decomposing manufacturing planning, due dates of each parts can be achieved by assembly planning and machining sequence of parts can be ascertained according to due dates of each parts.The chapter 5 puts forward multi-objective optimization method of flexible job-shop lot-splitting scheduling. The research status of job shop scheduling is analyzed and the multi-objective FJSP optimization model is set up, concerned with makespan, tardiness penalty, manufacturing cost, count of batch and total workload. The optimal solutions are obtained by using improved strength Pareto evolutionary algorithm (SPEA). The jobs are splitted into flexible size batch, and the batch routing and sequencing are simultaneously optimized by the method.The chapter 6 develops the manufacturing execution system of machine equipment ("ME-MES") in cloudy manufacturing with the project requirement and research results, which shows the validity and feasibility of the new theory and method proposed in the dissertation.The chapter 7 summarizes the key research contents and achievements, and presents conclusions along with recommendations for future research.