Equipment maintenance outsourcing is an important means by which enterprise can reduce business cost and risks, acquire competitive advantages and change manage model. Although the practice of equipment maintenance outsourcing is already carried out broadly in business circles, have a set of mature information system to provide support to it by now not yet. Enterprise may be confined to knowledge and individual background of managers to make some unwise decision out on every aspect of equipment maintenance outsourcing decision-making. That the outsourcing business is based only on individual hobby and experience of managers is to fail as soon as beginning. Building equipment maintenance outsourcing decision support system by which enterprise will standardize the decision-making process of equipment maintenance outsourcing by information technology, fully utilize the various information that enterprise has in hand, adopt the scientific decision-making implement to assist the decision-making, guarantee that decision process will be science and standard, avoid active jamming, besides realizing the transparency of the decision-making process.The article starts from studying background and concentrates on the analysis of the reasons of equipment maintenance outsourcing and equipment maintenance outsourcing decision support system development; Recalls the current documents situation of them; Then build the entire structure of equipment maintenance outsourcing decision support system based on fundamental IDSS theory, design the function structure of the system based on the process frame of the maintenance outsourcing, divide the system into five functions module and explain the function of each module; Analyze the operating principle and key technology of case-based reasoning and case-based reasoning IDSS model in detail, then take this as basis, discuss the concrete application of case-based reasoning on outsourcing partner choose, service business valuation and choose, outsourcing contract sign and outsourcing achievement effect estimate. |