An Application of Decision Making Grid to Improve Maintenance Strategies in Small and Medium Industries
Competitive disadvantages for small and medium industries (SMI), in comparison with the larger ones, essentially result from the restricted personnel possibilities in the administrative and production departments and also the decreasing lot sizes to be fabricated in the productions with referen...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | en |
| Published: |
IEEE
2007
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| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/11452/1/Burhan%282007%29_An_Application_of_Decision_Making_Grid_to_Improve_Maintenance_Strategies_in__Small_and_Medium_Industries.pdf http://eprints.utem.edu.my/id/eprint/11452/ |
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| Summary: | Competitive disadvantages for small and medium
industries (SMI), in comparison with the larger ones, essentially
result from the restricted personnel possibilities in the
administrative and production departments and also the
decreasing lot sizes to be fabricated in the productions with
reference to a growing product range. Also less number of
machines use in the SMI’s, in comparison to the larger ones,
which are always grouped together in serial lines. Therefore, it is
important to well organize their maintenance structure
individually to ensure the effectiveness of the entire production
lines. In order to increase the effectiveness of the units, we
studied some decision support systems (DSS) to maintain the
equipment. Choosing and optimizing maintenance strategies is of
formost importance in maintenance management. In this paper,
we identified maintenance strategies to the machines based on 2
factors: the downtime and the frequency of machines failures
with multiple criterions. We use decision making grid (DMG)
model introduced by [1]. Next, maintenance management
department can implement these strategies for their machines
respectively. The case study is taken from the SMI’s, one of the
food processing company in West Malaysia. We have collected a
dataset, conduct data analysis and provide few recommendations
to the maintenance management. |
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