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Research On Production Scheduling Problem Based On Order Disturbance

Posted on:2013-08-11Degree:MasterType:Thesis
Country:ChinaCandidate:L N YueFull Text:PDF
GTID:2268330398498789Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
In the increasingly fierce market competition, the manufacturing management of enterprise has been turned "sale by production" to "production by sale". Especially since the diversification and individuation of customers requirements, which makes Made To Order (MTO) is one of important means for production in manufacturing industry. According to the customer’s needs, ensure orders on-time delivery is the crucial standard of the customer service level in the manufacturing enterprise. Rational production scheduling is crucial in improving the customer service level in make-to-order manufacturing environment. Orders scheduling is making reasonable orders production plan under finite resource constraints, the aim is to keep on-time orders’ delivery.Firstly, the optimization objects of scheduling are presented, including delivery satisfaction, production efficiency and equipment utilization, and then the significance and measurement method of optimization objects are expatiated. Secondly, this paper researches on make-to-order production scheduling problem in two aspects:basic scheduling and scheduling based on order disturbance. According to the characteristics of genetic algorithms in solving problem, it is presented to figure out this basic scheduling issue; Since the orders disturbance occurred in manufacturing process, dynamic scheduling of event-driven and cycle-driven is put forward to apply the orders scheduling model, and a method combing rolling window technology and simple genetic algorithm is proposed to solve this dynamic scheduling. Finally, numerical examples modeled after a real-world make-to-order manufacturing system and computational results are provided in the end of this paper. Then, the feasibility of the method and model is verified.
Keywords/Search Tags:Make-to-Order, Dynamic Scheduling, Production Scheduling, Genetic Algorithms
PDF Full Text Request
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