Joint Decision Of Optimal Maintenance And Spare Parts Ordering For Leased System With Lessees' Satisfaction

To acquire equiment with minimal initial expenditure,many large enterprises opt to lease equipment.In such cases,the lessor owns equipment and is responsible for maintenance while the lessee has the use right of equipment.A large market share and low maintenance cost are essential for the lessor to make profit.However,uncertainty of the leased equipment deterioration state leads to uncertainty of the maintenance requirements.To guarantee the reliable operation of leased equipment,the lessor needs to carry out regular inspection and maintenance services,and store a large number of spare parts to improve the maintenance efficiency,resulting in higher costs.It is a major challenge for the lessor to develop a reasonable maintenance and spare parts policy according to the deterioration characteristics of leased equipment,ensure their reliable operation,improve lessee's satisfaction and gain a larger market share while reducing maintenance costs.With the rapid development of internet of things and sensing technology,the deterioration data of leased equipment can provide a new decision basis for the implementation of condition-based maintenance and spare parts ordering.While considering lessee's satisfaction and market share,this paper studies the time-based and condition-based maintenance decisions,and condition-based maintenance and spare parts integrated modeling for single equipment and the multi-equipment leased system.The paper covers the following:(1)Condition-based maintenance decision for leased equipment.The sequential inspection plan and condition-based preventive maintenance with control limit are proposed for the inspectable leased equipment.The probability distribution of deterioration state of leased equipment is derived,so is the inspection probability.An analytic model is established to minimize the maintenance cost by optimizing preventive maintenance threshold and inspection interval.Finally,a numerical experiment is conducted using a leased crane as a case study.(2)Time-based maintenance decision for multi-equipment leased system with consideration of lessee's satisfaction.For the leased system with a known failure rate,time-based maintenance policy combining sequential preventive maintenance and minimal failure repair is adopted,and the maintenance quality evaluation and the lessee number prediction method are proposed based on actual maintenance effect and lessee's subjective expectation.On this basis,based on the expected profit of the leased system,the time-based maintenance decision model is established to determine the optimal preventive maintenance times and maintenance effectiveness.A numerical experiment is conducted using a leased crane as a case study.(3)Condition-based maintenance decision for multi-equipment leased system with consideration of lessee's satisfaction.The optimal maintenance decision considering lessee's satisfaction is studied for the leased system with inspectable deterioration state.The condition-based maintenance policy with control limits is proposed for the leased system.With equipment availability and performance as objective indicators,the paper defines lessee's satisfaction and market share on the basis of lessee's subjective expectations,deduces the probability distribution of deterioration state under maintenance intervention.Meanwhile,an analytical model maximizing lessor's profit is established to determine the optimal inspection cycle and preventive maintenance threshold while considering penalties for both failure and overtime halting.A numerical experiment is conducted using a leased crane as a case study.(4)Joint decision based on both condition-based maintenance and spare part ordering of leased equipment with consideration of lessee's satisfaction.The policy considering both preventive maintenance and spare parts ordering with control limits is developed for the leased equipment.The paper defines lessee's satisfaction according to both objective maintenance service and lessee's subjective expectation,and deduces the equipment inspection probability,and the joint probability distribution of deterioration state and spare part state as well as the probability of equipment leased out.Considering the overtime halting penalty caused by the shortage of spare parts,an analytical model maximizing profit is established to optimize the optimal inspection cycle,preventive maintenance threshold and spare part ordering threshold.A numerical experiment is conducted using a leased crane as a case study.(5)Joint decision based on both condition-based maintenance and spare parts inventory management of multi-equipment leased system with consideration of lessee's satisfaction.Firstly,the paper suggests a policy considering both condition-based maintenance and spare parts inventory management based on a stochastic dynamic leasing mode.Secondly,the priority sequencing rule of multiple maintenance requirements is developed under limited spare parts resource,together with a spare part allocation model.Thirdly,taking availability and equipment performance as the objective service performance,the paper suggests an evaluation model of lessees' satisfaction and the market share based on lessee's subjective expectation.On this basis,a simulation model maximizing lessor's profit is established,with optimal inspection cycle,preventive maintenance threshold,maximum spare parts inventory,and spare parts safety inventory of the decision-making system.An experiment is conducted using a leased crane for verification.