Abstract
This paper proposes an integrated preventive maintenance and economic production quantity model. A condition-based maintenance policy is described by a random coefficient regression model, based on which the monitored condition is divided into two parts: the actual condition and random error. Products are produced in batches and the system is monitored at the end of each batch. If the observed system condition either reaches or exceeds the critical level, the system should be renewed by preventive maintenance. However, if the actual system condition reaches the failure level during the production process, the system fails and should be renewed immediately. Based on these two renewal situations, we construct a model of expected cost per unit time using the renewal reward theory. The critical level and production lot size are decision variables, which can be obtained by minimizing the cost model. We also develop a simulation process to obtain the optimal results in another way and validate our proposed cost model. Finally, a real case study is given to demonstrate the model and the simulation process.
Highlights
The joint optimization of maintenance and production has two main research streams
Two renewal scenarios were studied according to a pre-set failure level and the critical level, which is the decision variable of the system condition
Based on the distributions of the system condition and time to failure, we proposed an integrated economic production quantity (EPQ) and condition-based maintenance (CBM) cost model
Summary
The joint optimization of maintenance and production has two main research streams. The first research stream is the joint optimization of the capacitated lot-sizing and scheduling problem (CLSP) and maintenance. Cheng et al [31] proposed an integrated EPQ and CBM optimization model for an imperfect production system, where the quality control is studied and the degradation process is modeled by a gamma process They used the structural importance measure to make maintenance decisions, and they set the production lot size and PM threshold as the decision variables. Our integrated EPQ and CBM model provides innovation in the following areas: 1) for this type of model, we are the first study to use the RCRM to describe a system degradation process; 2) we consider the product quality problem in the model; and 3) we develop a simulation process to verify our model and provide a new method for finding the optimal results.
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