Total productive maintenance (TPM) implementation based on lean manufacturing tools

Abstract

This research was aimed to explore the implementation of Total Productive Maintenance (TPM) pillars and Lean Manufacturing (LM) tools as well as to investigate barriers and enablers in their implementations in Indonesian manufacturing industries. Another primary focus of this research was to develop reference models for both measurement and structural TPM pillars, LM tools and Manufacturing Performance (MP). A total of 132 questionnaires were sent to 132 manufacturing companies from 5 different industrial estates in Jakarta, Tangerang, Bekasi, Cilegon and Batam. A total of 108 questionnaires returned and only 91 were found suitable to be analysed. The findings indicate a reasonably good implementation of TPM and LM in Indonesian manufacturing industries. However, TPM performance in terms of Overall Equipment Effectiveness (OEE) value seems to be unsatisfactory, with the average value of 52.5 compared to the world class OEE with a value of 85%. There were 5 enablers and 7 barriers significantly influencing the success of TPM implementation, while 4 enablers and 5 barriers were found in the LM tools implementation. Six pillars of TPM were considered to be valid, reliable, and significant to represent the TPM implementation in Indonesia, while the other two were found to be nullified. All of the eight LM tools were also considered to be valid, reliable and significant. TPM was found to have a strong correlation with LM but has a weak correlation with MP. On the other hand, TPM has an indirect and moderate influence on MP through OEE and also LM tools. There was also evidence indicating that OEE has a strong direct influence towards MP. Lean manufacturing also has a moderate correlation with MP. The TPM pillars and LM tools have a significant and positive impact to MP simultanously. The influence of both on MP is 60.9% (R2 = 0.609) in proposed model but increased to 74.8% in the revised (final) model (R2 = 0.748). It also means that 74.8% variability of MP can be explained by TPM and LM, while 25.2% can be explained by the others. This model can be considered as a reference on the impact of TPM pillars and LM tools implementation over manufacturing performance in Indonesian manufacturing industries.