چکیده:
One of the most important activities in preventive maintenance is replacement of spare parts prior to failure. The aim of this paper is to propose an approach which determines jointly the preventive replacement interval and the spare parts inventory by considering different criteria and interacting with decision makers. In this approach, preventive replacement intervals, determined by experts of production and maintenance, are ranked by analytical hierarchy process (AHP). Criteria such as cost per unit of time, availability, remaining lifetime, and reliability are used. Then, a mixed integer nonlinear multi-objective model presented that it simultaneously specifies the period of preventive replacement and the required number of spare parts. This model considers the mentioned criteria and the inventory control costs of spare parts as different objective functions. Since, the solution of the problem depends on the decision maker’s strategy, it need interact with the decision-makers and consequently the proposed model could be solved using goal programming approach. The applicability of the proposed approach is illustrated by two numerical examples. The effect of key parameters on the optimal decisions is investigated for two examples.
خلاصه ماشینی:
The aim of this paper is to propose an approach which determines jointly the preventive replacement interval and the spare parts inventory by considering different criteria and interacting with decision makers.
Then, a multi-objective is developed that simultaneously determines the preventive replacement times and the quantity of spare parts over a planning horizon that is solved by goal programming approach.
Jiang and Ji (2002) developed a multi-criteria model along with a utility function in order to compute the optimal period of preventive replacement according to cost, reliability and life of parts.
(2016) proposed an optimization model of joint preventive maintenance and spare parts inventory which determines a cost-effective production plan and a maintenance policy.
In addition, Nosoohi and Hejazi (2011) developed a multi-objective model to simultaneously calculate the quantity of spare parts and preventive replacement times over a planning horizon; their proposed model has been solved by the ε-constraint method.
In most previous studies, reliability and anticipated cost per unit of time are used to identify the preventive replacement policies while other criteria including equipment accessibility and remaining life of spare parts are important in decisions making about preventive maintenance.
Therefore, this paper focuses on optimizing jointly preventive replacement times and ordering quantities of spare parts by considering various decision-making criteria as well as managerial goals.
Decision variables and parameters Once the weights (scores) of all preventive replacement time intervals are computed, they are applied and a multi-objective model is put forward to simultaneously determine preventive replacement policies and order quantity of spare parts.