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Maintenance Performance Indicators using Hybrid Models for Food Processing Industries

The performance and competitiveness of manufacturing companies are depending on the reliability and availability of their production equipment. To ensure the equipment always at desired performance, maintenance managers need a good track of the machines operation, maintenance activities and their...

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Main Authors: M.A., Burhanuddin, A.R., Ahmad, halawani, sami
Format: Article
Language:English
Published: International Journal of Advancements Computer Technology 2012
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.utem.edu.my/id/eprint/11588/1/Burhanuddin2012_Maintenance_Performance_Indicators_using_Hybrid_Models.pdf
http://eprints.utem.edu.my/id/eprint/11588/
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spelling my.utem.eprints.115882015-05-28T04:18:39Z http://eprints.utem.edu.my/id/eprint/11588/ Maintenance Performance Indicators using Hybrid Models for Food Processing Industries M.A., Burhanuddin A.R., Ahmad halawani, sami QA75 Electronic computers. Computer science The performance and competitiveness of manufacturing companies are depending on the reliability and availability of their production equipment. To ensure the equipment always at desired performance, maintenance managers need a good track of the machines operation, maintenance activities and their results. They should always attain all maintenance data, analyze them periodically, and subsequently transform it into useful strategies. Then act on the strategies to increase equipment productivities. In this research, we demonstrate on how to use Maintenance Decision Grid (MDG) and Fuzzy Inference System (FIS) to analyze maintenance performance in food processing industries. The MDG model is used to analyze top ten problematic machines in the production lines. Next, FIS is used to visualize output based on the given rules and input i.e. frequency of failures, downtime and cost. Based on MDG analysis, maintenance strategies are recommended i.e. operate to failure, service level upgrade, condition-based maintenance, design-out maintenance, total productive maintenance and reliability centered maintenance for one of the food processing industries. We collected maintenance data in 2008 and 2009 from the industry. Maintenance strategies given to the technical team and data are collected again in 2010 to observe any improvement. From the observation, we have verified that breakdowns reduced tremendously with the given strategies using MDG and FIS models. The objective of this paper is to use hybrid models i.e. MDG and FIS to analyze failure-based maintenance data. The MDG with FIS model give promising decision analysis where the performance indicators and strategies able to improve machine availabilities. International Journal of Advancements Computer Technology 2012-12-31 Article PeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/11588/1/Burhanuddin2012_Maintenance_Performance_Indicators_using_Hybrid_Models.pdf M.A., Burhanuddin and A.R., Ahmad and halawani, sami (2012) Maintenance Performance Indicators using Hybrid Models for Food Processing Industries. International Journal of Advancements Computer Technology, 4 (13). pp. 94-106. ISSN 100
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
M.A., Burhanuddin
A.R., Ahmad
halawani, sami
Maintenance Performance Indicators using Hybrid Models for Food Processing Industries
description The performance and competitiveness of manufacturing companies are depending on the reliability and availability of their production equipment. To ensure the equipment always at desired performance, maintenance managers need a good track of the machines operation, maintenance activities and their results. They should always attain all maintenance data, analyze them periodically, and subsequently transform it into useful strategies. Then act on the strategies to increase equipment productivities. In this research, we demonstrate on how to use Maintenance Decision Grid (MDG) and Fuzzy Inference System (FIS) to analyze maintenance performance in food processing industries. The MDG model is used to analyze top ten problematic machines in the production lines. Next, FIS is used to visualize output based on the given rules and input i.e. frequency of failures, downtime and cost. Based on MDG analysis, maintenance strategies are recommended i.e. operate to failure, service level upgrade, condition-based maintenance, design-out maintenance, total productive maintenance and reliability centered maintenance for one of the food processing industries. We collected maintenance data in 2008 and 2009 from the industry. Maintenance strategies given to the technical team and data are collected again in 2010 to observe any improvement. From the observation, we have verified that breakdowns reduced tremendously with the given strategies using MDG and FIS models. The objective of this paper is to use hybrid models i.e. MDG and FIS to analyze failure-based maintenance data. The MDG with FIS model give promising decision analysis where the performance indicators and strategies able to improve machine availabilities.
format Article
author M.A., Burhanuddin
A.R., Ahmad
halawani, sami
author_facet M.A., Burhanuddin
A.R., Ahmad
halawani, sami
author_sort M.A., Burhanuddin
title Maintenance Performance Indicators using Hybrid Models for Food Processing Industries
title_short Maintenance Performance Indicators using Hybrid Models for Food Processing Industries
title_full Maintenance Performance Indicators using Hybrid Models for Food Processing Industries
title_fullStr Maintenance Performance Indicators using Hybrid Models for Food Processing Industries
title_full_unstemmed Maintenance Performance Indicators using Hybrid Models for Food Processing Industries
title_sort maintenance performance indicators using hybrid models for food processing industries
publisher International Journal of Advancements Computer Technology
publishDate 2012
url http://eprints.utem.edu.my/id/eprint/11588/1/Burhanuddin2012_Maintenance_Performance_Indicators_using_Hybrid_Models.pdf
http://eprints.utem.edu.my/id/eprint/11588/
_version_ 1665905471397036032
score 13.211869

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