Evaluating 8 pillars of Total Productive Maintenance (TPM) implementation and their contribution to manufacturing performance

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 t...

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Main Authors: Adesta, Erry Yulian Triblas, Prabowo, Herry Agung, Agusman, Delvis
Format: Conference or Workshop Item
Language:English
English
English
Published: Institute of Physics Publishing 2018
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spelling my.iium.irep.644072018-10-18T01:47:22Z http://irep.iium.edu.my/64407/ Evaluating 8 pillars of Total Productive Maintenance (TPM) implementation and their contribution to manufacturing performance Adesta, Erry Yulian Triblas Prabowo, Herry Agung Agusman, Delvis HC79 Special topics. Including air pollution, consumer demands,famines, flow of fund etc TS155 Production management TS200 Metal manufactures. Metalworking 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. Institute of Physics Publishing 2018-01-30 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/64407/1/64407_Evaluating%208%20pillars%20of%20Total%20Productive%20Maintenance%20%28TPM%29_conference%20article.pdf application/pdf en http://irep.iium.edu.my/64407/2/64407_Evaluating%208%20pillars%20of%20Total%20Productive%20Maintenance%20%28TPM%29_scopus.pdf application/pdf en http://irep.iium.edu.my/64407/13/64407_Evaluating%208%20pillars%20of%20Total%20Productive%20Maintenance%20%28TPM%29%20_WoS.pdf Adesta, Erry Yulian Triblas and Prabowo, Herry Agung and Agusman, Delvis (2018) Evaluating 8 pillars of Total Productive Maintenance (TPM) implementation and their contribution to manufacturing performance. In: International Conference on Advances in Manufacturing and Materials Engineering 2017, ICAMME 2017, 8 - 9 August 2017, International Islamic University Malaysia (IIUM), Gombak Campus, Kuala Lumpur. http://iopscience.iop.org/article/10.1088/1757-899X/290/1/012024/meta 10.1088/1757-899X/290/1/012024
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
English
topic HC79 Special topics. Including air pollution, consumer demands,famines, flow of fund etc
TS155 Production management
TS200 Metal manufactures. Metalworking
spellingShingle HC79 Special topics. Including air pollution, consumer demands,famines, flow of fund etc
TS155 Production management
TS200 Metal manufactures. Metalworking
Adesta, Erry Yulian Triblas
Prabowo, Herry Agung
Agusman, Delvis
Evaluating 8 pillars of Total Productive Maintenance (TPM) implementation and their contribution to manufacturing performance
description 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.
format Conference or Workshop Item
author Adesta, Erry Yulian Triblas
Prabowo, Herry Agung
Agusman, Delvis
author_facet Adesta, Erry Yulian Triblas
Prabowo, Herry Agung
Agusman, Delvis
author_sort Adesta, Erry Yulian Triblas
title Evaluating 8 pillars of Total Productive Maintenance (TPM) implementation and their contribution to manufacturing performance
title_short Evaluating 8 pillars of Total Productive Maintenance (TPM) implementation and their contribution to manufacturing performance
title_full Evaluating 8 pillars of Total Productive Maintenance (TPM) implementation and their contribution to manufacturing performance
title_fullStr Evaluating 8 pillars of Total Productive Maintenance (TPM) implementation and their contribution to manufacturing performance
title_full_unstemmed Evaluating 8 pillars of Total Productive Maintenance (TPM) implementation and their contribution to manufacturing performance
title_sort evaluating 8 pillars of total productive maintenance (tpm) implementation and their contribution to manufacturing performance
publisher Institute of Physics Publishing
publishDate 2018
url http://irep.iium.edu.my/64407/1/64407_Evaluating%208%20pillars%20of%20Total%20Productive%20Maintenance%20%28TPM%29_conference%20article.pdf
http://irep.iium.edu.my/64407/2/64407_Evaluating%208%20pillars%20of%20Total%20Productive%20Maintenance%20%28TPM%29_scopus.pdf
http://irep.iium.edu.my/64407/13/64407_Evaluating%208%20pillars%20of%20Total%20Productive%20Maintenance%20%28TPM%29%20_WoS.pdf
http://irep.iium.edu.my/64407/
http://iopscience.iop.org/article/10.1088/1757-899X/290/1/012024/meta
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