Manufacturing Enterprise After-sales Service Decision-making Expert System Design And Implementation

Expert system is one of the most successful computer systems so far. By utilizingexperience from experts, it can resolve complex problems and free people from fussyworks. The expert system has been used in the manufacturing enterprises. But it isdifficult for traditional expert system to adapt the new conditions brought by thereformation of management thinking and changing in the internal operation mechanism. Itis exigent to analyze the shortage of traditional expert system and find out the new way todirect the design and development of the new expert system. The research of this subjectis critical to an enterprise in a competitive environment.This paper studies a production-rule-based fuzzy expert system and its application inthe decision of post sale support business of manufacture industry. Unlike some of theprevious fuzzy expert systems, which merely use a'confidence coefficient' to representthe uncertainty of rule, this paper designs a set of thoroughly fuzzy rules by introducingfuzzy set theory, fuzzy predication and human language into the system. This model willmore align with the real world business operations. This paper uses fuzzy recognitiontechnology to solve the problem of matching of the fuzzy rules and enable the fuzzyreasoning ability on the basis of weighted fuzzy reasoning system, thus make the expertsystem more reliable in solving complex practical problems. Through this system, we cansolve the uncertain and unpredictable problems which are very common in post salesoperations of manufacture industry.