Intelligent approaches in Condition Based Maintenance System, A Case Study using Oil Analysis and Case-Based Reasoning

Intelligent approaches in Condition Based Maintenance System, A Case Study using Oil Analysis and Case-Based Reasoning

Productivity is a key weapon for manufacturing companies to stay competitive in a continuous growing global marketIncreased productivity can be achieved throughincreased availability. This has directed focus on different maintenance types and maintenance strategies. Increased availability through efficient maintenance can beachieved through less corrective maintenance actions and more accurate preventivemaintenance intervals. Condition Based Maintenance (CBM) is a technology that strives to identify incipient faults before they become critical which enables more accurateplanning of the preventive maintenance. CBM can be achieved by utilizing complextechnical systems or by humans manually monitoring the condition by using theirexperience, normally a mixture of both is used. Although CBM holds a lot of benefitscompared to other maintenance types it is not yet commonly utilized in industry. Onereason for this might be that the maturity level in complex technical CBM system is toolow. 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 tocondition parameters as the objective is fulfilled. , this paper uses data mining techniquesincluding association rules and neural network and classification, to survey technical components of a complete CBM system approach and by a case study illustrate how aCBM system for truck BENZ2628 fault diagnosis and prognosis can be designed usingthe Artificial Intelligence method Case-Based Reasoning and oil analysis.