Abstract
Unexpected failure causes tremendous losses in economy and production, and may cause hazard of staff and equipment in manufacturing plant. A Condition-Based Maintenance (CBM) strategy can reduce these losses and guarantee the safety of personnel and machines by maintaining or repairing equipment just before failure. This paper presents a condition-based predictive maintenance model in system level for manufacturing industries which finally calculating the whole profit. Bee Colony Algorithm (BCA) is applied to find the maximum whole profit based on this model, and meanwhile maximizing availability. The optimal dynamic condition-based predictive maintenance scheduling could be achieved with reducing maintenance productivity, avoiding catastrophic losses, and prolong equipment service life according to the condition of the machine. The case study shows its effectiveness and efficiency of the proposed methodology.
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