With the rapid growth of the number of elevators,the traditional regular maintenance method is difficult to meet the dual needs of ensuring the safe and stable operation and cost control of elevators,on-demand maintenance is the direction of current key exploration,and intelligent diagnosis,prediction and maintenance decision-making of elevator faults are key technical issues.Starting from the technical principles and characteristics of predictive maintenance theory,this paper analyzes the feasibility of market demand,technical conditions and costs in the field of elevator on-demand maintenance,establishes an on-demand maintenance process framework based on predictive maintenance theory,points out fault complexity and data sparsity as the main bottlenecks in practice,and provides a reference for elevator on-demand maintenance research.
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