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MRP-controlled batch-manufacturing environment under uncertainty
The overall aim of this research is to model the effects of uncertainty on delivery performance in an MRP-controlled batch-manufacturing environment with multi-product and multi-level dependent demand. To this end, MRP planning and batch-manufacturing system control architectures were modelled using...
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Published in: | The Journal of the Operational Research Society 2004-03, Vol.55 (3), p.219-232 |
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description | The overall aim of this research is to model the effects of uncertainty on delivery performance in an MRP-controlled batch-manufacturing environment with multi-product and multi-level dependent demand. To this end, MRP planning and batch-manufacturing system control architectures were modelled using simulation to implement the MRP release logic. Simulation and experimental design were carried out based on a real case enterprise. ANOVA showed that four uncertainty factors-namely late delivery from suppliers, machine breakdowns, process batch size increments and customer design changes-have significant effects on delivery performance. This ANOVA further showed that uncertainties create knock-on and compound effects; the latter are difficult to predict in practice. Significant two-way and three-way interactions among some uncertainty factors were also found, making it more difficult to characterise the precise factor effects. It was found that the more uncertain the environment is, the later the deliveries are. It can be concluded that MRP-controlled batch-manufacturing enterprises should diagnose uncertainties that are significantly affecting delivery performance, and tackle these uncertainties most urgently to prevent diffusion of knock-on and compound effects and improve delivery performance. This conclusion was validated through the case enterprise, for which significant delivery improvement has been achieved. |
doi_str_mv | 10.1057/palgrave.jors.2601710 |
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To this end, MRP planning and batch-manufacturing system control architectures were modelled using simulation to implement the MRP release logic. Simulation and experimental design were carried out based on a real case enterprise. ANOVA showed that four uncertainty factors-namely late delivery from suppliers, machine breakdowns, process batch size increments and customer design changes-have significant effects on delivery performance. This ANOVA further showed that uncertainties create knock-on and compound effects; the latter are difficult to predict in practice. Significant two-way and three-way interactions among some uncertainty factors were also found, making it more difficult to characterise the precise factor effects. It was found that the more uncertain the environment is, the later the deliveries are. It can be concluded that MRP-controlled batch-manufacturing enterprises should diagnose uncertainties that are significantly affecting delivery performance, and tackle these uncertainties most urgently to prevent diffusion of knock-on and compound effects and improve delivery performance. This conclusion was validated through the case enterprise, for which significant delivery improvement has been achieved.</description><identifier>ISSN: 0160-5682</identifier><identifier>EISSN: 1476-9360</identifier><identifier>DOI: 10.1057/palgrave.jors.2601710</identifier><identifier>CODEN: JORSDZ</identifier><language>eng</language><publisher>London: Taylor & Francis</publisher><subject>Applied sciences ; Architectural control ; Architecture ; Business and Management ; Case Oriented Papers ; Case-Oriented Paper ; Children ; control ; Customer relationship management ; Enterprise resource planning ; Exact sciences and technology ; Experiment design ; Inventory control, production control. Distribution ; Literature reviews ; Management ; Manufacturing ; Manufacturing resource planning ; Marginal revenue products ; Material requirements planning ; Model theory ; Modeling ; Multilevel models ; Operational research and scientific management ; Operational research. Management science ; Operations research ; Operations Research/Decision Theory ; planning ; Planning. Forecasting ; Production controls ; Production planning ; Release dates ; Simulation ; Simulations ; Studies ; Supply chain management ; Uncertainty</subject><ispartof>The Journal of the Operational Research Society, 2004-03, Vol.55 (3), p.219-232</ispartof><rights>Copyright © 2004, Palgrave Macmillan Ltd 2004</rights><rights>Copyright 2004 Operational Research Society Ltd</rights><rights>Palgrave Macmillan Ltd 2004</rights><rights>2004 INIST-CNRS</rights><rights>Copyright (c) 2004 Palgrave Macmillan Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c433t-84f8272f1d406dfcc078815cd1e570b0d946a9a63caa7f4704f353b5f1b05b4f3</citedby><cites>FETCH-LOGICAL-c433t-84f8272f1d406dfcc078815cd1e570b0d946a9a63caa7f4704f353b5f1b05b4f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/231261612/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/231261612?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,776,780,11667,27901,27902,36037,44339,58213,58446,74638</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=15623792$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Koh, S C L</creatorcontrib><title>MRP-controlled batch-manufacturing environment under uncertainty</title><title>The Journal of the Operational Research Society</title><addtitle>J Oper Res Soc</addtitle><description>The overall aim of this research is to model the effects of uncertainty on delivery performance in an MRP-controlled batch-manufacturing environment with multi-product and multi-level dependent demand. To this end, MRP planning and batch-manufacturing system control architectures were modelled using simulation to implement the MRP release logic. Simulation and experimental design were carried out based on a real case enterprise. ANOVA showed that four uncertainty factors-namely late delivery from suppliers, machine breakdowns, process batch size increments and customer design changes-have significant effects on delivery performance. This ANOVA further showed that uncertainties create knock-on and compound effects; the latter are difficult to predict in practice. Significant two-way and three-way interactions among some uncertainty factors were also found, making it more difficult to characterise the precise factor effects. It was found that the more uncertain the environment is, the later the deliveries are. It can be concluded that MRP-controlled batch-manufacturing enterprises should diagnose uncertainties that are significantly affecting delivery performance, and tackle these uncertainties most urgently to prevent diffusion of knock-on and compound effects and improve delivery performance. This conclusion was validated through the case enterprise, for which significant delivery improvement has been achieved.</description><subject>Applied sciences</subject><subject>Architectural control</subject><subject>Architecture</subject><subject>Business and Management</subject><subject>Case Oriented Papers</subject><subject>Case-Oriented Paper</subject><subject>Children</subject><subject>control</subject><subject>Customer relationship management</subject><subject>Enterprise resource planning</subject><subject>Exact sciences and technology</subject><subject>Experiment design</subject><subject>Inventory control, production control. Distribution</subject><subject>Literature reviews</subject><subject>Management</subject><subject>Manufacturing</subject><subject>Manufacturing resource planning</subject><subject>Marginal revenue products</subject><subject>Material requirements planning</subject><subject>Model theory</subject><subject>Modeling</subject><subject>Multilevel models</subject><subject>Operational research and scientific management</subject><subject>Operational research. Management science</subject><subject>Operations research</subject><subject>Operations Research/Decision Theory</subject><subject>planning</subject><subject>Planning. Forecasting</subject><subject>Production controls</subject><subject>Production planning</subject><subject>Release dates</subject><subject>Simulation</subject><subject>Simulations</subject><subject>Studies</subject><subject>Supply chain management</subject><subject>Uncertainty</subject><issn>0160-5682</issn><issn>1476-9360</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><sourceid>M0C</sourceid><recordid>eNqFkF1rFDEUhoNYcG39BwqL4OWs5ySTZOauUuoHtFREr0Mmk9RZZpP1JFPZf-8ss7V3epNDOO_H4WHsDcIGQer3ezvek33wm22ivOEKUCM8YyustapaoeA5WwEqqKRq-Av2MuctALSA7Ypd3n77WrkUC6Vx9P26s8X9rHY2TsG6MtEQ79c-PgyU4s7Hsp5i72l-nadih1gOF-ws2DH7V6d5zn58vP5-9bm6ufv05erDTeVqIUrV1KHhmgfsa1B9cA5006B0PXqpoYO-rZVtrRLOWh1qDXUQUnQyYAeymz_n7O2Su6f0a_K5mG2aKM6VhgvkChXyWSQXkaOUM_lg9jTsLB0MgjmyMo-szJGVObGafe9O4TY7Oway0Q35ySwVF7o95qtFl_dHMp6ejvhfwevFuM0l0d_gGoED4Ly-XNZDDIl29neisTfFHsZEj8eIfzf8AZBEoQE</recordid><startdate>20040301</startdate><enddate>20040301</enddate><creator>Koh, S C L</creator><general>Taylor & Francis</general><general>Palgrave Macmillan Press</general><general>Palgrave Macmillan UK</general><general>Palgrave</general><general>Taylor & Francis Ltd</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0U~</scope><scope>1-H</scope><scope>3V.</scope><scope>7RQ</scope><scope>7WY</scope><scope>7WZ</scope><scope>7X7</scope><scope>7XB</scope><scope>87Z</scope><scope>88E</scope><scope>8AL</scope><scope>8FE</scope><scope>8FG</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8FL</scope><scope>8G5</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>FYUFA</scope><scope>F~G</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>K9.</scope><scope>L.-</scope><scope>L.0</scope><scope>L6V</scope><scope>M0C</scope><scope>M0N</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>M7S</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>U9A</scope></search><sort><creationdate>20040301</creationdate><title>MRP-controlled batch-manufacturing environment under uncertainty</title><author>Koh, S C L</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c433t-84f8272f1d406dfcc078815cd1e570b0d946a9a63caa7f4704f353b5f1b05b4f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Applied sciences</topic><topic>Architectural control</topic><topic>Architecture</topic><topic>Business and Management</topic><topic>Case Oriented Papers</topic><topic>Case-Oriented Paper</topic><topic>Children</topic><topic>control</topic><topic>Customer relationship management</topic><topic>Enterprise resource planning</topic><topic>Exact sciences and technology</topic><topic>Experiment design</topic><topic>Inventory control, production control. Distribution</topic><topic>Literature reviews</topic><topic>Management</topic><topic>Manufacturing</topic><topic>Manufacturing resource planning</topic><topic>Marginal revenue products</topic><topic>Material requirements planning</topic><topic>Model theory</topic><topic>Modeling</topic><topic>Multilevel models</topic><topic>Operational research and scientific management</topic><topic>Operational research. Management science</topic><topic>Operations research</topic><topic>Operations Research/Decision Theory</topic><topic>planning</topic><topic>Planning. Forecasting</topic><topic>Production controls</topic><topic>Production planning</topic><topic>Release dates</topic><topic>Simulation</topic><topic>Simulations</topic><topic>Studies</topic><topic>Supply chain management</topic><topic>Uncertainty</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Koh, S C L</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Global News & ABI/Inform Professional</collection><collection>Trade PRO</collection><collection>ProQuest Central (Corporate)</collection><collection>Career & Technical Education Database</collection><collection>ABI商业信息数据库</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest - Health & Medical Complete保健、医学与药学数据库</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection</collection><collection>Medical Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Research Library (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Database (1962 - current)</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Business Premium Collection (Alumni)</collection><collection>Health Research Premium Collection</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Professional Standard</collection><collection>ProQuest Engineering Collection</collection><collection>ABI/INFORM global</collection><collection>Computing Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>Proquest Research Library</collection><collection>Engineering Database</collection><collection>Research Library (Corporate)</collection><collection>ProQuest advanced technologies & aerospace journals</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>One Business (ProQuest)</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering collection</collection><collection>ProQuest Central Basic</collection><jtitle>The Journal of the Operational Research Society</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Koh, S C L</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MRP-controlled batch-manufacturing environment under uncertainty</atitle><jtitle>The Journal of the Operational Research Society</jtitle><stitle>J Oper Res Soc</stitle><date>2004-03-01</date><risdate>2004</risdate><volume>55</volume><issue>3</issue><spage>219</spage><epage>232</epage><pages>219-232</pages><issn>0160-5682</issn><eissn>1476-9360</eissn><coden>JORSDZ</coden><abstract>The overall aim of this research is to model the effects of uncertainty on delivery performance in an MRP-controlled batch-manufacturing environment with multi-product and multi-level dependent demand. To this end, MRP planning and batch-manufacturing system control architectures were modelled using simulation to implement the MRP release logic. Simulation and experimental design were carried out based on a real case enterprise. ANOVA showed that four uncertainty factors-namely late delivery from suppliers, machine breakdowns, process batch size increments and customer design changes-have significant effects on delivery performance. This ANOVA further showed that uncertainties create knock-on and compound effects; the latter are difficult to predict in practice. Significant two-way and three-way interactions among some uncertainty factors were also found, making it more difficult to characterise the precise factor effects. It was found that the more uncertain the environment is, the later the deliveries are. It can be concluded that MRP-controlled batch-manufacturing enterprises should diagnose uncertainties that are significantly affecting delivery performance, and tackle these uncertainties most urgently to prevent diffusion of knock-on and compound effects and improve delivery performance. This conclusion was validated through the case enterprise, for which significant delivery improvement has been achieved.</abstract><cop>London</cop><pub>Taylor & Francis</pub><doi>10.1057/palgrave.jors.2601710</doi><tpages>14</tpages></addata></record> |
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subjects | Applied sciences Architectural control Architecture Business and Management Case Oriented Papers Case-Oriented Paper Children control Customer relationship management Enterprise resource planning Exact sciences and technology Experiment design Inventory control, production control. Distribution Literature reviews Management Manufacturing Manufacturing resource planning Marginal revenue products Material requirements planning Model theory Modeling Multilevel models Operational research and scientific management Operational research. Management science Operations research Operations Research/Decision Theory planning Planning. Forecasting Production controls Production planning Release dates Simulation Simulations Studies Supply chain management Uncertainty |
title | MRP-controlled batch-manufacturing environment under uncertainty |
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