A Study And Application Of APS Planning In Textile Enterprises

Production management system is one of the most complex information systems in manufacture, the key point of which is planning and scheduling. Due to the complexity and uncertainty in production process, most of the planning approaches are hardly able to reach a satisfactory goal. This thesis will focus on methods of planning as well as optimization, and then establish an effective Advanced Planning and Scheduling (APS) system framework in textile industry, armed with the prevalent information techniques and various algorithms.The significance of this thesis is stated in the first section, standing in the perspective of the evolution of production planning methods, and current research upon applications in textile industry is investigated. After analyzing the most comprehensive methods employed in the demand planning and master planning, effective measures are introduced in the second section, which are to ensure a more accurate plan. Also the performance of both the innovative and the original implementations is demonstrated and compared in this section. The essence of planning method is integrated as a whole, when people finish improving the process of ATP. In the last section, an APS framework, which contains the ideas presented hereinbefore, is constructed and illustrated.In order to eliminate the confusion between quantity of demand andthat of sales, the introduction of a forecasting model, say, Kalman Filter model, will benefit to enhance the veracity of prediction. However, most textile companies locate in the upstream of supply chains, inclining to be impacted tremendously by the famous bullwhip effect. The purpose of weakening the bullwhip effect constitutes the driver of building a Kalman Filter forecasting model in the supply chain environment, by being lent information sharing through the chain.Since multiple objectives programming is able to simulate the changeful situations in the production process by settling different fulfillments in its target function, it is proper for master production planning to balance material flow through supply chain. A better attainment of the model necessitates a more accurate setting of resource constraint data in the model. The thesis discusses specifically the classifications, sources and obtainment of differentiated resource constraint information. Additionally, the estimation of productivity, including of equipment and product line, is dependent on reliability theory and simulation;thus the corresponding steps of the productivity estimation of a textile company are delivered.Furthermore, depending on the new ideas of demand planning and master production planning, this thesis describes the reformative ATP process under the circumstance of supply chain management. Since the ameliorative ATP process connects with not only demand planning but also master production planning, the three planning processes are able to interact with each other and become a circulatory system. Thus, a core planning system of production management emerges.Consequently, on the grounding of "Object-Oriented analysis and design" as well as the basal principles of framework design, this thesis establishes a framework of APS to meet the ideas of planning discussed above. This framework describes the definition of data, algorithm, agent,integration and exchange in detail. Similarly, a simplified example of demand forecast in a textile firm is given to embody the utilization of this framework.The research hereby is to contribute mainly to the improvement and integration of the three planning processes and the establishment of an APS framework, which enable the production management more effective. Besides, the framework will help companies set up a new APS system and extend the existent system as a reference. As a result, the systems, which are based on this framework, can assist the decision makers to organize more reasonable, flexible and appropriate plans.