Evaluating 8 pillars of Total Productive Maintenance (TPM) implementation and their contribution to manufacturing performance - Adesta, Erry Yulian Triblas; Prabowo, Herry Agung; Agusman, Delvis (Institute of Physics Publishing, 2018)
TPM is one method to improve manufacturing performance through an emphasis on maintenance that involves everyone in the organization. Research on the application of TPM and its relevance to the manufacturing performance has been performed quite a lot. However, to the best of our knowledge, a study that deliberates how the application of 8 pillars TPM (especially in developing countries) is still hard to find. This paper attempts to evaluate in more detail about how the 8 pillars of TPM are applied in Indonesia and their impact on manufacturing performance. This research is a pilot study with a target of 50 companies. From the results of data collection, only 22 companies (44%) are eligible to process. Data processing was performed using SPSS and Smart PLS tools. From the validity and reliability tests, it can be seen that all items/indicators for TPM pillars are valid and reliable with correlation value (R) of 0.614 - 0.914 and with Cronbach's alpha equal to 0.753. As for the Manufacturing Performance construct, the Delivery indicator was not valid. In overall, the model is reliable with Cronbach's alpha of 0.710. From the results of Confirmatory Factors Analysis (CFA) for TPM, it can be seen that four indicators (pillars) are highly significant while four other indicators are less significant. For MP, three indicators are significant, and two are not significant. In general, the structural model of the relationship between TPM and MP is relatively strong and positive with values R = 0.791, and R squared = 0.626. This means that the TPM Pillars can explain 62.6% MP variability construct variable, while the other 37.4% can be explained by unrelated variables.