t Hajjari - Department of Mathematics, Islamic Azad University, Firuz-Kuh Branch Firuz-Kuh, Iran,
y Nejadbakhsh, - Department of Mathematics, Islamic Azad University, Firuz-Kuh Branch Firuz-Kuh, Iran
m Farahmand - Department of Mathematics, Islamic Azad University, Zahedan Branch, Zahedan, Iran

Maintenance, as a system plays a key role in reducing cost, minimizing equipment downtime, improving quality, increasing productivity, providing reliable equipment, and as a result achieving organizational goals and objective. Consequently, proper preventive maintenance of machinery is an important element in the control of quality, waste and production. Therefore, to achieve production targets through equipment reliability, industrial maintenance strategies need to be reviewed periodically. Often Predictive Maintenance data and qualitative expert domain knowledge are ignored while dealing with reliability metrics such asMTBF, MTTR etc., which may result in obscure decisions. To overcome this lacuna and to lead to a logical scientific conclusion on equipment health, this paper proposes a generic method based on Information Fusion, which is arrived from failure history, predictive maintenance data and domain expert's knowledge. The proposed method uses the failure history to compute indices to evaluate the validity of the existing maintenance and to assign Degree of Certainty using fuzzy rules

Failure History, Maintenance Strategy, Predictive Maintenance, Preventive Maintenance