Research On Production Planning And Optimization For Manual Operation System

Based on the external environment and development status, the realistic operational needs, and the research of modeling theory of organization and optimization to small and medium-sized make-to-order (MTO) manufacturing enterprise, this article mainly studies the operation characteristics and optimization of the production system under random uncertain conditions, the completion time estimation and delivery time decision, production planning and orders scheduling, along the idea:"to summarize the modeling and simulation elements of small and medium-sized make-to-order (MTO) manufacturing enterprise production system-to establish simulation model with regular realistic production structure-to get large amount of experimental data-to summarize the main factors affecting the production output-to model and validate-to propose management strategy based modeling and simulating". The specific studies are as belows:(1) Research on the operation characteristics and modeling and simulating for production structure under random uncertain conditions. Current research status, the running mode and running characteristicsis of manual operation system (MOS) are summarized. Based the management model of a small and medium-sized manufacturing enterprises in the Pearl River Delta, this article establishes a Timed-colored-Petri net for manual operation system under random uncertain conditions. Then, the essey simulates production data and evaluates the production results in different situations.(2) Research on the order completion time estimation and delivery time decision. The essey analyzes the factors which are affected the completion time by quantity and quality. Taking the lead time as the objective function, we compare the three operation modes, calculate the lead time of different operating modes based on certain worker’s learning rate, and analyze the sensitivity of relationship between different operating modes and the factors such as the workers’learning rate, the production batch and the process time difference, etc. Then, BP neural network is established to completion time estimation within ten factors. Sensitivity of some factors is analysized in Matlab, such as the load on the production line and the number of orders. This model can help small and medium-sized manufacturing enterprises to make a effectively delivery time decision under eight situations.(3) Research on production planning and orders scheduling. First, considering of the effects of the learning effect, the essey establish a model of decision-making of planning quantity put into production, which takes the minimum expense expected value. Second, the essey establishes the order scheduling profit model between two situation-manufactures who determine the delivery time and customer or both customer and manufactures that determine the delivery time. Finally, grey relational analysis is introduced to optimize the mixed order scheduling moder considering the order fulfillment time, inventory costs and delayed delivery cost.Eventually, this essay displays the outlook of the future research. And this study is sponsored by The National Nature Science Foundation(70971026).