Research On Agile Inquiry Order Promising Method For Electronic Manufacturing Industry

Sponsored by the China's National High-tech R&D Program (No.2006AA04Z157) and the Key Sci.& Tech. Program of Zhejiang Province, China (No.2003C11010), based on in-depth analysis and discussion of inquiry order promising, advanced planning and scheduling (APS), and quick quote research, this dissertation focused on agile decision-making methodology for inquiry order in electronics manufacturing, advanced planning and scheduling method for rapid delivery, method of committing delivery-date of orders based on APS, method of fast quotation, and implement of agile decision-making system for inquiry order in electronics manufacturing. That provided a solid theoretical basis and guidance method for the successful implementation of agile manufacturing and rapid response to market demand and customer orders.Chapter I gave the background and significance of research paper, described research state at home and abroad related to inquiry order decision-making in theory, methods, techniques, etc, cleared the research objective, and presented the main research content and paper structure.Chapter II analyzed business processes and mixed production mode, and gave the process models of agile inquiry order performing, delivery-date decision-making and pricing decision-making according to electronic manufacturing characteristics and requirements. Agile inquiry order four-layer methodology architecture for electronic manufacturing was proposed.Chapter III aimed at the goal of agile response to customer demand, a master planning schedule based on storing materials and parts for ATO and storing products for MTS for fast delivery was brought forward. To build a fuzzy production planning model based on credibility programming under fuzzy environment. The fuzzy production planning model was transformed into the form of a clear equivalent through the clarity of fuzzy objectives and constraints. A modified PSO algorithm based on evaluated vector and non-stationary multi-stage mapping penalty function method was given for solving this model. According to typical features in electronics manufacturing and features of purchasing electronic components under multiple suppliers'environments, two allocation patterns considering cost or delivery date as top priority were proposed. Two models of purchasing tasks allocation considering the total cost of products were constructed and corresponding algorithms were constructed based on the two predetermined policy. Chapter IV aimed at quickly determining delivery-date of inquiry order, delivery-date decision of inquiry order for multiple assembly lines was studied. The sequence of scheduling orders was given by calculating order priority value based on evaluation orders priority indicators and hierarchical model. Two-way scheduling method for multiple assembly lines based on order priority rule was proposed, considering constraint of assembly resources and delivery date after ATP. The cost model of scheduling orders for electronic products with fuzzy capacity constraints was established. A new adaptive particle swarm optimization algorithm with dynamically changing inertia weight (DCWPSO) was brought forward to solve the problem.Chapter V aimed at the quick quotation for inquiry order, a model of cost estimation for electronic products was brought forward. Manufacturing cost estimation processes of standard products, standard configure products and custom products were established. After product cost estimation, to offer the quote to customers based on the expected profit. Both supply and demand sides obtained the best strategic choices after tow games under the condition of imperfect information.Chapter VI implemented agile decision-making system for inquiry order in electronics manufacturing sponsored by the Key Sci.& Tech. Program of Zhejiang Province, China (No.2003C11010). On this basis; to achieve the support for inquiry order delivery-date quickly identify, product cost estimation and fast quote.Chapter VII summarizes the research work of the full dissertation and prospects further research for the future.