Troubleshooting using Cost Effective Algorithms and Bayesian Networks

As the heavy duty truck market becomes more competitive the importance of quick and cheap repairs increases. However, to find and repair the faulty component constitutes cumbersome and expensive work and it is not uncommon that the troubleshooting process results in unnecessary expenses. To repair t...

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Main Author: Gustavsson, Thomas
Format: Others
Language:English
Published: KTH, Reglerteknik 2007
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-106253
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spelling ndltd-UPSALLA1-oai-DiVA.org-kth-1062532013-01-08T13:45:42ZTroubleshooting using Cost Effective Algorithms and Bayesian NetworksengGustavsson, ThomasKTH, Reglerteknik2007As the heavy duty truck market becomes more competitive the importance of quick and cheap repairs increases. However, to find and repair the faulty component constitutes cumbersome and expensive work and it is not uncommon that the troubleshooting process results in unnecessary expenses. To repair the truck in a cost effective fashion a troubleshooting strategy that chooses actions according to cost minimizing conditions is desirable. This thesis proposes algorithms that uses Bayesian networks to formulate cost minimizing troubleshooting strategies. The algorithms consider the effectiveness of observing components, performing tests and repairs to decide the best current action. The algorithms are investigated using three different Bayesian networks, out of which one is a model of a real life system. The results from simulation cases illustrate the effectiveness and properties of the algorithms. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-106253application/pdfinfo:eu-repo/semantics/openAccess
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language English
format Others
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description As the heavy duty truck market becomes more competitive the importance of quick and cheap repairs increases. However, to find and repair the faulty component constitutes cumbersome and expensive work and it is not uncommon that the troubleshooting process results in unnecessary expenses. To repair the truck in a cost effective fashion a troubleshooting strategy that chooses actions according to cost minimizing conditions is desirable. This thesis proposes algorithms that uses Bayesian networks to formulate cost minimizing troubleshooting strategies. The algorithms consider the effectiveness of observing components, performing tests and repairs to decide the best current action. The algorithms are investigated using three different Bayesian networks, out of which one is a model of a real life system. The results from simulation cases illustrate the effectiveness and properties of the algorithms.
author Gustavsson, Thomas
spellingShingle Gustavsson, Thomas
Troubleshooting using Cost Effective Algorithms and Bayesian Networks
author_facet Gustavsson, Thomas
author_sort Gustavsson, Thomas
title Troubleshooting using Cost Effective Algorithms and Bayesian Networks
title_short Troubleshooting using Cost Effective Algorithms and Bayesian Networks
title_full Troubleshooting using Cost Effective Algorithms and Bayesian Networks
title_fullStr Troubleshooting using Cost Effective Algorithms and Bayesian Networks
title_full_unstemmed Troubleshooting using Cost Effective Algorithms and Bayesian Networks
title_sort troubleshooting using cost effective algorithms and bayesian networks
publisher KTH, Reglerteknik
publishDate 2007
url http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-106253
work_keys_str_mv AT gustavssonthomas troubleshootingusingcosteffectivealgorithmsandbayesiannetworks
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