Optimization of preventive maintenance schedule and production lot size
In this research, a developed mathematical model is proposed to optimize the preventive maintenance age and lot size for a single-unit production system producing a single item. The system is assumed to start in an in-control state producing items of acceptable quality and then after a period of pro...
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Veröffentlicht in: | International journal of production economics 2012-05, Vol.137 (1), p.19-28 |
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description | In this research, a developed mathematical model is proposed to optimize the preventive maintenance age and lot size for a single-unit production system producing a single item. The system is assumed to start in an in-control state producing items of acceptable quality and then after a period of production time the system may shift to an out-of-control state producing non-conforming items. The time for the system to shift is a random variable that is assumed to follow a general probability distribution. It is assumed that failure may occur at any time after the system shift to the out-of-control state. The system failure time is also assumed to follow a general probability distribution. The proposed model considers average total values of the maintenance, inventory holding, non-conforming items, and shortage costs. The results found indicated that the introduction of failure possibility decreased the production lot size for a specific preventive maintenance age. Sensitivity analysis is carried out to assess the effect of four cost parameters on model performance. Furthermore, the model is extended to consider the effects of: combining inspection with preventive maintenance; and introducing non-negligible preventive maintenance duration. |
doi_str_mv | 10.1016/j.ijpe.2012.01.006 |
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The system is assumed to start in an in-control state producing items of acceptable quality and then after a period of production time the system may shift to an out-of-control state producing non-conforming items. The time for the system to shift is a random variable that is assumed to follow a general probability distribution. It is assumed that failure may occur at any time after the system shift to the out-of-control state. The system failure time is also assumed to follow a general probability distribution. The proposed model considers average total values of the maintenance, inventory holding, non-conforming items, and shortage costs. The results found indicated that the introduction of failure possibility decreased the production lot size for a specific preventive maintenance age. Sensitivity analysis is carried out to assess the effect of four cost parameters on model performance. Furthermore, the model is extended to consider the effects of: combining inspection with preventive maintenance; and introducing non-negligible preventive maintenance duration.</description><identifier>ISSN: 0925-5273</identifier><identifier>EISSN: 1873-7579</identifier><identifier>DOI: 10.1016/j.ijpe.2012.01.006</identifier><identifier>CODEN: IJPCEY</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Age ; Costs ; Failure ; Inspection ; Inventory ; Lot size ; Maintenance optimization models ; Mathematical models ; Operations research ; Preventive maintenance ; Probability distribution ; Production scheduling ; Random variables ; Sensitivity analysis ; Shortages ; Studies</subject><ispartof>International journal of production economics, 2012-05, Vol.137 (1), p.19-28</ispartof><rights>2012 Elsevier B.V.</rights><rights>Copyright Elsevier Sequoia S.A. 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Furthermore, the model is extended to consider the effects of: combining inspection with preventive maintenance; and introducing non-negligible preventive maintenance duration.</description><subject>Age</subject><subject>Costs</subject><subject>Failure</subject><subject>Inspection</subject><subject>Inventory</subject><subject>Lot size</subject><subject>Maintenance optimization models</subject><subject>Mathematical models</subject><subject>Operations research</subject><subject>Preventive maintenance</subject><subject>Probability distribution</subject><subject>Production scheduling</subject><subject>Random variables</subject><subject>Sensitivity analysis</subject><subject>Shortages</subject><subject>Studies</subject><issn>0925-5273</issn><issn>1873-7579</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><recordid>eNp9kD1PwzAQhi0EEqXwB5giJpaEs5PYjsSCKihIlbrAbBnnIhzlC9upRH89LmViQDfc8ryn9x5CrilkFCi_azPbTpgxoCwDmgHwE7KgUuSpKEV1ShZQsTItmcjPyYX3LQAIKuWCrLdTsL3d62DHIRmbZHK4wyHYHSa9tkPAQQ8GE28-sJ47TPRQR2asZ_OT6MaQeLvHS3LW6M7j1e9ekrenx9fVc7rZrl9WD5vUFKwIaV1ToRk1DHmJnHEJOWVQFQILygpo3gsZe7EGcyw5x7oAmQsTRwKLnMyX5PZ4N3b4nNEH1VtvsOv0gOPsFY2clHlJIaI3f9B2nN0Q26mKyaooac4jxI6QcaP3Dhs1Odtr9xUvqYNa1aqDWnVQq4CqqDaG7o8hjJ_uLDrljcWoqbYOTVD1aP-LfwMZGoCR</recordid><startdate>20120501</startdate><enddate>20120501</enddate><creator>Suliman, Saad M.A.</creator><creator>Jawad, Sayed Husain</creator><general>Elsevier B.V</general><general>Elsevier Sequoia S.A</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TA</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JG9</scope><scope>KR7</scope></search><sort><creationdate>20120501</creationdate><title>Optimization of preventive maintenance schedule and production lot size</title><author>Suliman, Saad M.A. ; Jawad, Sayed Husain</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c424t-dd17a21c2e65e626803120947e41240fb487182fe3e566ed40837c7c780220983</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Age</topic><topic>Costs</topic><topic>Failure</topic><topic>Inspection</topic><topic>Inventory</topic><topic>Lot size</topic><topic>Maintenance optimization models</topic><topic>Mathematical models</topic><topic>Operations research</topic><topic>Preventive maintenance</topic><topic>Probability distribution</topic><topic>Production scheduling</topic><topic>Random variables</topic><topic>Sensitivity analysis</topic><topic>Shortages</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Suliman, Saad M.A.</creatorcontrib><creatorcontrib>Jawad, Sayed Husain</creatorcontrib><collection>CrossRef</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Materials Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>International journal of production economics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Suliman, Saad M.A.</au><au>Jawad, Sayed Husain</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimization of preventive maintenance schedule and production lot size</atitle><jtitle>International journal of production economics</jtitle><date>2012-05-01</date><risdate>2012</risdate><volume>137</volume><issue>1</issue><spage>19</spage><epage>28</epage><pages>19-28</pages><issn>0925-5273</issn><eissn>1873-7579</eissn><coden>IJPCEY</coden><abstract>In this research, a developed mathematical model is proposed to optimize the preventive maintenance age and lot size for a single-unit production system producing a single item. The system is assumed to start in an in-control state producing items of acceptable quality and then after a period of production time the system may shift to an out-of-control state producing non-conforming items. The time for the system to shift is a random variable that is assumed to follow a general probability distribution. It is assumed that failure may occur at any time after the system shift to the out-of-control state. The system failure time is also assumed to follow a general probability distribution. The proposed model considers average total values of the maintenance, inventory holding, non-conforming items, and shortage costs. The results found indicated that the introduction of failure possibility decreased the production lot size for a specific preventive maintenance age. Sensitivity analysis is carried out to assess the effect of four cost parameters on model performance. 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source | ScienceDirect Journals (5 years ago - present) |
subjects | Age Costs Failure Inspection Inventory Lot size Maintenance optimization models Mathematical models Operations research Preventive maintenance Probability distribution Production scheduling Random variables Sensitivity analysis Shortages Studies |
title | Optimization of preventive maintenance schedule and production lot size |
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