The purpose of this study is to present a novel indicator for analyzing machine failure based on its idle time and productivity. Existing machine repair plan was limited to machine experts from its manufacturing industries. This study evaluates the repair status of machines and extracts machines that need improvement. In this study, F-RPN was calculated using the etching process data provided by the 2018 PHM Data Challenge. Each S(S: Severity), O(O: Occurence), D(D: Detection) is divided into the idle time of the machine, the number of fault data, and the failure rate, respectively. The repair status of machine is quantified through the F-RPN calculated by multiplying S, O, and D. This study conducts a case study of machine in a semiconductor etching process. The process capability index has the disadvantage of not being able to divide the values outside the range. The performance of this index declines when the manufacturing process is under control, hereby introducing F-RPN to evaluate machine status that are difficult to distinguish by process capability index.

Failure mode and effects analysis(FMEA) is popular approach applied to examine potential failures in equipment designs and maintenance of equipments. Risk Priority Number(RPN) is used as an index for the criticality of fault modes in FMEA and RCM(reliability centered maintenance). Traditional RPN approach does not have much credit as a index for the criticality because it does not reflect their experience and the governing logic is apart from their knowledge. Multiple Criteria Decision Method(MCDM) is a proven approach applied to evaluate multiple conflicting criteria in decision making. MCDM can be applied as a tool for RPN evaluation. This study was carried out to investigate application of Analytical Hierarchy Process(AHP) in evaluating RPN.