Optimal availability for determining choice and repair policy of system components

Purpose: The purpose of this paper is to establish the regression model by a simulation method that was obtained by using the system response at unit cost as the response value. The unit availability was maximized, while the unit cost was minimized. Design/methodology/approach: In this study, the Monte Carlo simulation method was used to simulate an operational system, and the regression model was obtained by using response surface methodology with the experimental matrix and different levels of experimental combinations. Findings: The optimal value of mean time between failure (MTBF) and mean time to repair (MTTR) of each component was then obtained by using the system response at unit cost as the response value. Practical implications: Due to the upgrading of industrial technology and the maturity of electronic technology, product development technology has become highly sophisticated with complex designs. Reliability engineering has become a key procedure of high-tech industry. Social implications: Based on the system availability of unit cost as the response value, it can maximize the availability to help decision makers to formulate the best selection strategy components and repair strategy. Originality/value: Previous works regarding the parameter settings of reliability values never mention the simulation methodology. However, this study aims to achieve the above goals in finding the relationship of MTBF and MTTR simultaneously.