A Knowledge-Based Framework for Cost Implication Modeling of Mechanically Repairable Systems with Imperfect Preventive Maintenance and Replacement Schedule
A knowledge-based framework that exploits fuzzy logic to generate precise cost implication decisions from an optimal maintenance and replacement schedule is proposed. Using data from a locally fabricated 8HP-PML Gold engine cassava grinding machine whose failure distribution follows the Weibull dist...
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Format: | Article |
Language: | English |
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Tamkang University Press
2022-05-01
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Series: | Journal of Applied Science and Engineering |
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Online Access: | http://jase.tku.edu.tw/articles/jase-202302-26-2-0008 |
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author | Nse Udoh Moses Ekpenyong |
author_facet | Nse Udoh Moses Ekpenyong |
author_sort | Nse Udoh |
collection | DOAJ |
description | A knowledge-based framework that exploits fuzzy logic to generate precise cost implication decisions from an optimal maintenance and replacement schedule is proposed. Using data from a locally fabricated 8HP-PML Gold engine cassava grinding machine whose failure distribution follows the Weibull distribution function with shape and scale parameters α=1.30 and β =1386, respectively; and cost input parameters namely, the cost of preventive maintenance (Cp), cost of replacement maintenance (Cr), and cost of minimal repair (Cm), an analytical model was constructed to generate the corresponding optimal cost ratios (Cr⁄Cp and Cm⁄Cp ), useful for deriving the required universe of discourse and membership functions for the respective linguistic variables or cost parameters ranges. Extensive simulation using MATLAB 2017a revealed three types of system performance demonstrating the effects of costs interaction on varying costs implication decisions. Results of simulation indicate that the machine functions optimally at all low costs (i.e., when Cp, Cr, and Cm are ‘low’) and maintains delayed replacement frequencies but the machine becomes expensive to maintain when Cp, and Cm increases above acceptable thresholds (i.e., are either ‘high’ or ‘v.high’). The scientific implication is that the proposed system efficiently models interaction between input parameters and can effectively guide operators/designers’ decisions on the choice to weigh varying cost implication decisions of PM and replacement schedules for mechanically repairable systems whose failure rate may be characterized by other failure distribution functions. |
first_indexed | 2024-12-12T04:21:05Z |
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institution | Directory Open Access Journal |
issn | 2708-9967 2708-9975 |
language | English |
last_indexed | 2024-12-12T04:21:05Z |
publishDate | 2022-05-01 |
publisher | Tamkang University Press |
record_format | Article |
series | Journal of Applied Science and Engineering |
spelling | doaj.art-4e8f4ec411084b478238c7d3e43be5d32022-12-22T00:38:19ZengTamkang University PressJournal of Applied Science and Engineering2708-99672708-99752022-05-01261221234 10.6180/jase.202302_26(2).0008A Knowledge-Based Framework for Cost Implication Modeling of Mechanically Repairable Systems with Imperfect Preventive Maintenance and Replacement ScheduleNse Udoh0Moses Ekpenyong1Department of Statistics, University of Uyo, NigeriaDepartment of Computer Science, University of Uyo, NigeriaA knowledge-based framework that exploits fuzzy logic to generate precise cost implication decisions from an optimal maintenance and replacement schedule is proposed. Using data from a locally fabricated 8HP-PML Gold engine cassava grinding machine whose failure distribution follows the Weibull distribution function with shape and scale parameters α=1.30 and β =1386, respectively; and cost input parameters namely, the cost of preventive maintenance (Cp), cost of replacement maintenance (Cr), and cost of minimal repair (Cm), an analytical model was constructed to generate the corresponding optimal cost ratios (Cr⁄Cp and Cm⁄Cp ), useful for deriving the required universe of discourse and membership functions for the respective linguistic variables or cost parameters ranges. Extensive simulation using MATLAB 2017a revealed three types of system performance demonstrating the effects of costs interaction on varying costs implication decisions. Results of simulation indicate that the machine functions optimally at all low costs (i.e., when Cp, Cr, and Cm are ‘low’) and maintains delayed replacement frequencies but the machine becomes expensive to maintain when Cp, and Cm increases above acceptable thresholds (i.e., are either ‘high’ or ‘v.high’). The scientific implication is that the proposed system efficiently models interaction between input parameters and can effectively guide operators/designers’ decisions on the choice to weigh varying cost implication decisions of PM and replacement schedules for mechanically repairable systems whose failure rate may be characterized by other failure distribution functions.http://jase.tku.edu.tw/articles/jase-202302-26-2-0008failure distributionfuzzy logicpreventive maintenancepredictive maintenancereplacement scheduleweibull distribution function |
spellingShingle | Nse Udoh Moses Ekpenyong A Knowledge-Based Framework for Cost Implication Modeling of Mechanically Repairable Systems with Imperfect Preventive Maintenance and Replacement Schedule Journal of Applied Science and Engineering failure distribution fuzzy logic preventive maintenance predictive maintenance replacement schedule weibull distribution function |
title | A Knowledge-Based Framework for Cost Implication Modeling of Mechanically Repairable Systems with Imperfect Preventive Maintenance and Replacement Schedule |
title_full | A Knowledge-Based Framework for Cost Implication Modeling of Mechanically Repairable Systems with Imperfect Preventive Maintenance and Replacement Schedule |
title_fullStr | A Knowledge-Based Framework for Cost Implication Modeling of Mechanically Repairable Systems with Imperfect Preventive Maintenance and Replacement Schedule |
title_full_unstemmed | A Knowledge-Based Framework for Cost Implication Modeling of Mechanically Repairable Systems with Imperfect Preventive Maintenance and Replacement Schedule |
title_short | A Knowledge-Based Framework for Cost Implication Modeling of Mechanically Repairable Systems with Imperfect Preventive Maintenance and Replacement Schedule |
title_sort | knowledge based framework for cost implication modeling of mechanically repairable systems with imperfect preventive maintenance and replacement schedule |
topic | failure distribution fuzzy logic preventive maintenance predictive maintenance replacement schedule weibull distribution function |
url | http://jase.tku.edu.tw/articles/jase-202302-26-2-0008 |
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