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Parts Purchase Decision Support System

Posted on:2017-04-05Degree:MasterType:Thesis
Country:ChinaCandidate:R XuFull Text:PDF
GTID:2272330485977492Subject:Mechanical design and theory
Abstract/Summary:PDF Full Text Request
With the rapid development of China’s manufacturing technology, more and more car manufacturers, in particular, more and more small and medium automobile manufacturing companies added to the fierce competition in the automotive industry. Parts procurement not only directly relates to the manufacturer’s profit, it also affects the automobile production and manufacturing service activities. With parts commonality continuing to become stronger and stronger, and the proportion of automobile factory’s purchased parts increasing, manufacturers are increasingly relying on parts suppliers. Therefore, how to predict the number of parts and select the appropriate parts suppliers becomes manufacturers’s major problem in procurement plans. In this paper, the automobile industry chain collaboration platform to platform components business data as the foundation, to build parts procurement decision support system, the system uses forecasting methods and evaluation methods for the manufacturers to provide scientific support on purchasing decisions. Thesis has done the following work:For small and medium manufacturing enterprises in the major issues faced in parts procurement, explained the significance of this study, then analyzed the research status of procurement forecasting techniques, and understand the supplier evaluation index and evaluation methods from two aspects the research status at home and abroad; the automobile industry chain binding characteristics of parts procurement, clear user demand for parts procurement decision support systems combined with the automobile industry chain platform,asp.net proposed three-tier B/S mode system solution programs; the system overall business process analysis, a clear functional requirements of the system, performed functional use case modeling; analysis of the gray forecast model and neural network forecasting model, combining the characteristics of procurement is established based on multiple factors improvement Grey prediction model; Conducted from the perspective of the whole industry chain, a clear distribution of parts suppliers indicators, combined with scientific, comprehensive, qualitative and quantitative principles, the establishment of quality, price, ability to cooperate, service-oriented capabilities and external environment index system, and the significance of each index and a detailed description of the calculation and design; analysis of the current evaluation method, fuzzy theory is applied analytic hierarchy process, the establishment of evaluation model based on fuzzy analytic hierarchy process, and model is numerical example; with the user’s needs and functional modeling use cases, functional structure of the overall system is designed, and detailed design of functional modules; for frame system is designed, according to the business process and user needs, analysis of the systems business entities, establish a conceptual model of the database, and the establishment of a conceptual model based on the logical model of the database system; Finally, system development tool, the main function of the system implementation.
Keywords/Search Tags:Parts procurement, Procurement forecast, Supplier evaluation, gray forecasting model, Fuzzy Analytic Hierarchy Process
PDF Full Text Request
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