Development of Knowledge Management & Reasoning System for Condition BasedMaintenanceA Case Study Using Oil Analysis and Case-Based Reasoning

Knowledge management is an important key for manufacturing companies to stay competitive in a continuous growing global market. Improved performance can be achieved through increased availability. This has directed focus on gathering and manages expert knowledge in different maintenance types and maintenance strategies. Increased availability through efficient maintenance can be achieved through less corrective maintenance actions and more accurate preventive maintenance intervals. Condition Based Maintenance (CBM) is a technology that strives to identify incipient faults before they become critical which enables more accurate planning of the preventive maintenance. This paper will acknowledge this possible reason, although not trying to resolve it, but focusing on system technology with component strategy and an open approach to condition parameters as the objective is fulfilled. , this paper uses data mining techniques including association rules and neural network and classi?cation, to survey technical components of a complete CBM system approach and by a case study illustrate how a CBM system for truck BENZ2628 fault diagnosis and prognosis can be designed using the Artificial Intelligence method Case-Based Reasoning and oil analysis.

Keywords:

Knowledge Management (KM) , Condition Based Maintenance (CBM) , Data Mining , Diagnosis , Artificial Neural Network , Decision Tree , Case-Based Reasoning (CBR)