Measuring efficiency of total productive maintenance (TPM): a three-stage data envelopment analysis (DEA) approach

Abstract

Total productive maintenance (TPM) is a manufacturing strategy that has been successfully employed globally for the last three decades. A prerequisite for benefiting from TPM is to measure the performance of TPM activities. Although overall equipment effectiveness has widely been used as a performance measure of TPM activities, it is a measure for TPM effectiveness. It is also required to measure the performance of TPM implementation in terms of efficiency. This study intends to measure the efficiency of TPM implementation using data envelopment analysis (DEA) with consideration of the overall process of TPM implementation. Since more and more organisations are increasingly relying on self-directed work team (SDWT) to accomplish organisational tasks in TPM implementation, this study employs SDWT as a unit of analysis. The process of TPM implementation is captured in a three-stage model: stage 1 (from TPM input to TPM intermediate output), stage 2 (from TPM intermediate output to TPM final output), and stage 3 (from TPM input to TPM final output). Every SDWT in every team is evaluated together by DEA for each stage. The relationships between the efficiency scores of the three stages are analysed by correlation analysis. Also, cluster analysis is conducted to identify different types of SDWTs in terms of TPM implementation.