A Dynamic Fuzzy Exper t System Based on Maintenance Indicators for Servic e Type Selection of achinry

Due to the multiplicity of standard s and compl ex rules, m aintenance, repair, and servicing o f machinery could be done only by the fully qualified and proficient experts. Since the knowledge of s uch experts is not accessible all tim es, using e xpert system s can help to improve the maintenance proces s. To address this need and the un certainty of the maintenance proce ss indicators, this rese rch proposed a Fuzzy Expert Systems (FES) for decision-making on the type of service. Since not a ll indicato rs identifie in the literature are important adequately, firstly, indicators that are more influential in the service type selecti n are chosen using inferential statistical ana lysis. Then, these selected indicato rs designed the fuzzy rules of the knowledge based. Fin ally, Inference engine has been designed based on Mamdani model to detect the service typ e of equipment. This research sel ected Shemsh Sazan Z anjan Comp any as a ca se study to implement the proposed expert system. Accord ing to our e xperiments, the proposed system increases the reliability by suggesti ng effective ideas that l ead to decr asing production line breakdowns . The main contribution of this pap er is provi ding a new approach t designing maintenance dynamic FES based on Maintenance Indicators for service-type selection th at can decrease produ ction line breakdowns.

Keywords:

Expert syst ems , Artificial i ntelligent , Fuzzy logi c , Preventive repair ndmaintenan e , Conveyors belt , Maintenance indicators