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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| Format: | Thesis |
| Language: | English |
| Published: |
Universiti Malaysia Perlis (UniMAP)
2019
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| Online Access: | http://dspace.unimap.edu.my:80/xmlui/handle/123456789/61537 |
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| Summary: | 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. |
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