An integrated approach for configuration optimization in a CBM system by considering fatigue effects

Abstract

This study presents a new approach based on Taguchi, computer simulation, and data envelopment analysis to determine the optimal number of redundant machines and operators in a condition-based maintenance (CBM) system. This is achieved by optimizing availability, processing time, and total number of failures. Due to the complex nature of various parameters, computer simulation is used as a powerful tool to mimic the real conditions of the system. The actual CBM and production activities as well as fatigue effects are simulated. Time to failure of machines is estimated by two condition monitoring parameters including oil level and vibration. Standard outputs which are reliability, queue length, availability, and cost are calculated by the simulation model. The efficiency of each scenario and its rank are calculated by data envelopment analysis (DEA). In order to improve the efficiency of the approach, the Taguchi method is applied, which reduces the number of scenarios. The Taguchi method is also used as a robust design to evaluate the robustness of different number of machines and operators. A real case study is applied to show the applicability and effectiveness of the proposed approach. In the case study, the preferred solution is obtained by investigating only 12.5 % of the scenarios. The proposed approach of this study would help the decision makers to select the preferred system configuration efficiently in a shorter time.