It is assumed that the production system responds to planned demand at the end of the expected life of each individual piece of equipment and unplanned demand triggered by equipment failures. The difficulty of controlling this type of production system resides in the variable nature of the remanufacturing process. In practice, remanufacturing operations for planned demand can be executed at different rates, referring to different component replacement and repair strategies. A sub‐optimal control policy in which inventory thresholds trigger the use of different execution modes has been formulated in previous research to address this problem when unplanned demands are processed under an exponential time distribution. The aim of this study is to extend this control policy to more realistic unplanned demand arrival and processing times distributions.
The proposed approach is based on a combination of analytical modeling, simulation experimentation and regression analysis. The model was validated by comparing the obtained simulation results with those obtained under an exponential processing time distribution.
The results demonstrate that the structure of optimal control can be approximated by the sub‐optimal multiple hedging point policy with non‐significant cost variations.
The simulation results demonstrate that hedging point control policies could be applicable to a wide variety of complex remanufacturing problems in which analytical solutions are not easily obtained.
The paper extends the concept of hedging point policy to the control of real‐word repair and remanufacturing operations. Once calculated, the sub‐optimal policy parameters can be simply implemented by practitioners through the definition of stock‐level parameters.
