A decision-making approach to field service delivery under mixed maintenance policy
Maintenance service delivery for large-scale equipment has been studied for decades and is becoming a crucial way for equipment manufacturers to obtain profit and competitiveness. To delivery maintenance service, equipment manufacturers need to optimal delivery plans with considering of various constraints (e.g. maintenance policy, service capacities, service costs) as well as maintenance type. This study proposed a mathematical model and algorithm-based approach to solving a maintenance service decision-making problem in the mixed maintenance policy context and to assess its performance. The mathematical model was constructed with the constraints of technician number, skill level, maintenance time windows, and maintenance policy. A hybrid algorithm of simulated annealing algorithm (SA) and genetic algorithm (GA) is proposed to solve this practical maintenance service delivery problem. A case study of agricultural equipment maintenance demonstrated that the proposed methods are effective and the algorithms can provide reasonable solutions within an acceptable computational time. Our approach is effective and can be utilized to improve the performance of maintenance service decision-making for the mixed policy.