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Autonomous maintenance decision model for lathe machine using fuzzy analytical hierarchy process (AHP) method

Deterioration on production machine may lead to high production costs. One of the preventive maintenance strategies to reduce deterioration of machine is Autonomous Maintenance (AM). The aim of autonomous maintenance is to achieve a high degree of cleanliness, excellent lubrication and proper fast...

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Bibliographic Details
Main Author: Ahmadi Hamdan, Musman
Other Authors: Dr. Rosmaini Ahmad
Format: Thesis
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2019
Subjects:
Lathes
Lathes > Numerical control
Deterioration
Autonomous Maintenance (AM)
Total Productive Maintenance (TPM)
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/61537
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spelling my.unimap-615372019-08-23T09:44:09Z Autonomous maintenance decision model for lathe machine using fuzzy analytical hierarchy process (AHP) method Ahmadi Hamdan, Musman Dr. Rosmaini Ahmad Lathes Lathes -- Numerical control Deterioration Autonomous Maintenance (AM) Total Productive Maintenance (TPM) Deterioration on production machine may lead to high production costs. One of the preventive maintenance strategies to reduce deterioration of machine is Autonomous Maintenance (AM). The aim of autonomous maintenance is to achieve a high degree of cleanliness, excellent lubrication and proper fastening on the machine. However, the conventional AM practice, the process of initial cleaning might increase the maintenance cost and the time required. Therefore, to make this process more effective and efficient, this study proposes an AM decision model using fuzzy Analytical Hierarchy Process (AHP) method to identify the critical components and to determine the right AM activities. A case study of a lathe machine is used to validate the model. The data were collected through personnel interview with technicians at machine shop laboratory in UniMAP. In this study, fuzzy AHP is carried out using pairwise comparison data to verify the critical components. Finding of the analysis reveals that there are eight critical components of the lathe machine that have been identified. By having this information, the model does help in minimizing the maintenance costs and time by identifying the right component for maintenance and so to determine the right maintenance activities to be carried out. Thus, this study has provide theoretical and practical inferences about the development of AM decision model. 2019-08-23T09:44:08Z 2019-08-23T09:44:08Z 2015 Thesis http://dspace.unimap.edu.my:80/xmlui/handle/123456789/61537 en Universiti Malaysia Perlis (UniMAP) School of Manufacturing Engineering
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Lathes
Lathes -- Numerical control
Deterioration
Autonomous Maintenance (AM)
Total Productive Maintenance (TPM)
spellingShingle Lathes
Lathes -- Numerical control
Deterioration
Autonomous Maintenance (AM)
Total Productive Maintenance (TPM)
Ahmadi Hamdan, Musman
Autonomous maintenance decision model for lathe machine using fuzzy analytical hierarchy process (AHP) method
description Deterioration on production machine may lead to high production costs. One of the preventive maintenance strategies to reduce deterioration of machine is Autonomous Maintenance (AM). The aim of autonomous maintenance is to achieve a high degree of cleanliness, excellent lubrication and proper fastening on the machine. However, the conventional AM practice, the process of initial cleaning might increase the maintenance cost and the time required. Therefore, to make this process more effective and efficient, this study proposes an AM decision model using fuzzy Analytical Hierarchy Process (AHP) method to identify the critical components and to determine the right AM activities. A case study of a lathe machine is used to validate the model. The data were collected through personnel interview with technicians at machine shop laboratory in UniMAP. In this study, fuzzy AHP is carried out using pairwise comparison data to verify the critical components. Finding of the analysis reveals that there are eight critical components of the lathe machine that have been identified. By having this information, the model does help in minimizing the maintenance costs and time by identifying the right component for maintenance and so to determine the right maintenance activities to be carried out. Thus, this study has provide theoretical and practical inferences about the development of AM decision model.
author2 Dr. Rosmaini Ahmad
author_facet Dr. Rosmaini Ahmad
Ahmadi Hamdan, Musman
format Thesis
author Ahmadi Hamdan, Musman
author_sort Ahmadi Hamdan, Musman
title Autonomous maintenance decision model for lathe machine using fuzzy analytical hierarchy process (AHP) method
title_short Autonomous maintenance decision model for lathe machine using fuzzy analytical hierarchy process (AHP) method
title_full Autonomous maintenance decision model for lathe machine using fuzzy analytical hierarchy process (AHP) method
title_fullStr Autonomous maintenance decision model for lathe machine using fuzzy analytical hierarchy process (AHP) method
title_full_unstemmed Autonomous maintenance decision model for lathe machine using fuzzy analytical hierarchy process (AHP) method
title_sort autonomous maintenance decision model for lathe machine using fuzzy analytical hierarchy process (ahp) method
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2019
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/61537
_version_ 1643806654781718528
score 13.211869

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