Guidelines for the deployment and implementation of manufacturing scheduling systems

dc.contributor.authorFramiñan Torres, José Manueles_ES
dc.contributor.authorRuiz García, Rubénes_ES
dc.date.accessioned2014-11-24T08:38:13Z
dc.date.available2014-11-24T08:38:13Z
dc.date.issued2012
dc.description.abstractIt has frequently been stated that there exists a gap between production scheduling theory and practice. In order to put theoretical findings into practice, advances in scheduling models and solution procedures should be embedded into a piece of software - a scheduling system - in companies. This results in a process that entails (1) determining its functional features, and (2) adopting a successful strategy for its development and deployment. In this paper we address the latter question and review the related literature in order to identify descriptions and recommendations of the main aspects to be taken into account when developing such systems. These issues are then discussed and classified, resulting in a set of guidelines that can help practitioners during the process of developing and deploying a scheduling system. In addition, identification of these issues can provide some insights to drive theoretical scheduling research towards those topics more in demand by practitioners, and thus help to close the aforementioned gap.es_ES
dc.description.accrualMethodSes_ES
dc.description.bibliographicCitationFramiñan Torres, JM.; Ruiz García, R. (2012). Guidelines for the deployment and implementation of manufacturing scheduling systems. International Journal of Production Research. 50(7):1799-1812. doi:10.1080/00207543.2011.564670es_ES
dc.description.issue7es_ES
dc.description.referencesBaek, D. H. (1999). A visualized human-computer interactive approach to job shop scheduling. International Journal of Computer Integrated Manufacturing, 12(1), 75-83. doi:10.1080/095119299130489es_ES
dc.description.referencesComesaña Benavides, J. A., & Carlos Prado, J. (2002). Creating an expert system for detailed scheduling. International Journal of Operations & Production Management, 22(7), 806-819. doi:10.1108/01443570210433562es_ES
dc.description.referencesBensana, E. 1986. An expert-system approach to industrial job-shop scheduling. In: Proceedings of the 1986 IEEE international conference on robotics and automation. 1986. Vol. 3, pp.1645–1650.es_ES
dc.description.referencesBerglund, M., & Karltun, J. (2007). Human, technological and organizational aspects influencing the production scheduling process. International Journal of Production Economics, 110(1-2), 160-174. doi:10.1016/j.ijpe.2007.02.024es_ES
dc.description.referencesBesbes, W., Teghem, J., & Loukil, T. (2010). Scheduling hybrid flow shop problem with non-fixed availability constraints. European J. of Industrial Engineering, 4(4), 413. doi:10.1504/ejie.2010.035652es_ES
dc.description.referencesBhattacharyya, S., & Koehler, G. J. (1998). Learning by Objectives for Adaptive Shop-Floor Scheduling. Decision Sciences, 29(2), 347-375. doi:10.1111/j.1540-5915.1998.tb01580.xes_ES
dc.description.referencesBitran, G. R., & Tirupati, D. (1988). OR Practice—Development and Implementation of a Scheduling System for a Wafer Fabrication Facility. Operations Research, 36(3), 377-395. doi:10.1287/opre.36.3.377es_ES
dc.description.referencesBuxey, G. (1989). Production scheduling: Practice and theory. European Journal of Operational Research, 39(1), 17-31. doi:10.1016/0377-2217(89)90349-4es_ES
dc.description.referencesChen, J.-F. (2004). Unrelated parallel machine scheduling with secondary resource constraints. The International Journal of Advanced Manufacturing Technology, 26(3), 285-292. doi:10.1007/s00170-003-1622-1es_ES
dc.description.referencesCollinot, A., Le Pape, C., & Pinoteau, G. (1988). SONIA: A knowledge-based scheduling system. Artificial Intelligence in Engineering, 3(2), 86-94. doi:10.1016/0954-1810(88)90024-6es_ES
dc.description.referencesCowling, P. (2003). A flexible decision support system for steel hot rolling mill scheduling. Computers & Industrial Engineering, 45(2), 307-321. doi:10.1016/s0360-8352(03)00038-xes_ES
dc.description.referencesDudek, R. A., Panwalkar, S. S., & Smith, M. L. (1992). The Lessons of Flowshop Scheduling Research. Operations Research, 40(1), 7-13. doi:10.1287/opre.40.1.7es_ES
dc.description.referencesDumond, E. J. (2005). Understanding and using the capabilities of finite scheduling. Industrial Management & Data Systems, 105(4), 506-526. doi:10.1108/02635570510592398es_ES
dc.description.referencesFox, M. S., & Smith, S. F. (1984). ISIS?a knowledge-based system for factory scheduling. Expert Systems, 1(1), 25-49. doi:10.1111/j.1468-0394.1984.tb00424.xes_ES
dc.description.referencesFraminan, J. M., & Ruiz, R. (2010). Architecture of manufacturing scheduling systems: Literature review and an integrated proposal. European Journal of Operational Research, 205(2), 237-246. doi:10.1016/j.ejor.2009.09.026es_ES
dc.description.referencesFreed, T., Doerr, K. H., & Chang, T. (2007). In-house development of scheduling decision support systems: case study for scheduling semiconductor device test operations. International Journal of Production Research, 45(21), 5075-5093. doi:10.1080/00207540600818351es_ES
dc.description.referencesGao, C and Tang, L. 2008. A decision support system for color-coating line in steel industry. In: Proceedings of the IEEE international conference on automation and logistics, ICAL 2008. 2008. pp.1463–1468.es_ES
dc.description.referencesGrant, T. J. (1986). Lessons for O.R. from A.I.: A Scheduling Case Study. Journal of the Operational Research Society, 37(1), 41-57. doi:10.1057/jors.1986.7es_ES
dc.description.referencesGraves, S. C. (1981). A Review of Production Scheduling. Operations Research, 29(4), 646-675. doi:10.1287/opre.29.4.646es_ES
dc.description.referencesHALSALL, D. N., MUHLEMANN, A. P., & PRICE, D. H. R. (1994). A review of production planning and scheduling in smaller manufacturing companies in the UK. Production Planning & Control, 5(5), 485-493. doi:10.1080/09537289408919520es_ES
dc.description.referencesHiggins, P. G. (1996). Interaction in hybrid intelligent scheduling. International Journal of Human Factors in Manufacturing, 6(3), 185-203. doi:10.1002/(sici)1522-7111(199622)6:3<185::aid-hfm1>3.0.co;2-6es_ES
dc.description.referencesKanet, J. J., & Adelsberger, H. H. (1987). Expert systems in production scheduling. European Journal of Operational Research, 29(1), 51-59. doi:10.1016/0377-2217(87)90192-5es_ES
dc.description.referencesKathawala, Y., & Allen, W. R. (1993). Expert Systems and Job Shop Scheduling. International Journal of Operations & Production Management, 13(2), 23-35. doi:10.1108/01443579310025286es_ES
dc.description.referencesKerr, R. M. (1992). Expert systems in production scheduling: Lessons from a failed implementation. Journal of Systems and Software, 19(2), 123-130. doi:10.1016/0164-1212(92)90063-pes_ES
dc.description.referencesKnolmayer, G., Mertens, P., & Zeier, A. (2002). Supply Chain Management Based on SAP Systems. doi:10.1007/978-3-540-24816-3es_ES
dc.description.referencesLeachman, R. C., Benson, R. F., Liu, C., & Raar, D. J. (1996). IMPReSS: An Automated Production-Planning and Delivery-Quotation System at Harris Corporation—Semiconductor Sector. Interfaces, 26(1), 6-37. doi:10.1287/inte.26.1.6es_ES
dc.description.referencesMACCARTHY, B. L., & LIU, J. (1993). Addressing the gap in scheduling research: a review of optimization and heuristic methods in production scheduling. International Journal of Production Research, 31(1), 59-79. doi:10.1080/00207549308956713es_ES
dc.description.referencesMcKay, K. N., & Black, G. W. (2007). The evolution of a production planning system: A 10-year case study. Computers in Industry, 58(8-9), 756-771. doi:10.1016/j.compind.2007.02.002es_ES
dc.description.referencesMcKay, K. N., Safayeni, F. R., & Buzacott, J. A. (1988). Job-Shop Scheduling Theory: What Is Relevant? Interfaces, 18(4), 84-90. doi:10.1287/inte.18.4.84es_ES
dc.description.referencesMcKay, K. N., Morton, T. E., Ramnath, P., & Wang, J. (2000). ?Aversion dynamics? scheduling when the system changes. Journal of Scheduling, 3(2), 71-88. doi:10.1002/(sici)1099-1425(200003/04)3:2<71::aid-jos35>3.0.co;2-0es_ES
dc.description.referencesMCKAY, K., PINEDO, M., & WEBSTER, S. (2009). PRACTICE-FOCUSED RESEARCH ISSUES FOR SCHEDULING SYSTEMS*. Production and Operations Management, 11(2), 249-258. doi:10.1111/j.1937-5956.2002.tb00494.xes_ES
dc.description.referencesMissbauer, H., Hauber, W., & Stadler, W. (2009). A scheduling system for the steelmaking-continuous casting process. A case study from the steel-making industry. International Journal of Production Research, 47(15), 4147-4172. doi:10.1080/00207540801950136es_ES
dc.description.referencesNumao, M and Morishita, S. 1989. A scheduling environment for steel-making processes. In: Proceedings of the 5th conference on artificial intelligence applications. 1989. pp.279–286.es_ES
dc.description.referencesOlhager, J., & Rapp, B. (1995). Operations Research Techniques in Manufacturing Planning and Control Systems. International Transactions in Operational Research, 2(1), 29-43. doi:10.1111/j.1475-3995.1995.tb00003.xes_ES
dc.description.referencesPerez-Gonzalez, P., & Framinan, J. M. (2009). Scheduling permutation flowshops with initial availability constraint: Analysis of solutions and constructive heuristics. Computers & Operations Research, 36(10), 2866-2876. doi:10.1016/j.cor.2008.12.018es_ES
dc.description.referencesPinedo, M., & Yen, B. P.-C. (1997). Annals of Operations Research, 70, 359-378. doi:10.1023/a:1018986524234es_ES
dc.description.referencesPortougal, V., & Robb, D. J. (2000). Production Scheduling Theory: Just Where Is It Applicable? Interfaces, 30(6), 64-76. doi:10.1287/inte.30.6.64.11623es_ES
dc.description.referencesReisman, A., Kumar, A., & Motwani, J. (1997). Flowshop scheduling/sequencing research: a statistical review of the literature, 1952-1994. IEEE Transactions on Engineering Management, 44(3), 316-329. doi:10.1109/17.618173es_ES
dc.description.referencesSteffen, MS. 1986. A survey of artificial intelligence-based scheduling systems. In: Proceedings of the fall industrial engineering conference. 1986.es_ES
dc.description.referencesStorer, R. H., Wu, S. D., & Vaccari, R. (1992). New Search Spaces for Sequencing Problems with Application to Job Shop Scheduling. Management Science, 38(10), 1495-1509. doi:10.1287/mnsc.38.10.1495es_ES
dc.description.referencesTang, L., & Wang, G. (2008). Decision support system for the batching problems of steelmaking and continuous-casting production. Omega, 36(6), 976-991. doi:10.1016/j.omega.2007.11.002es_ES
dc.description.referencesT’kindt, V., Billaut, J.-C., Bouquard, J.-L., Lenté, C., Martineau, P., Néron, E., … Tacquard, C. (2005). The e-OCEA project: towards an Internet decision system for scheduling problems. Decision Support Systems, 40(2), 329-337. doi:10.1016/j.dss.2004.04.001es_ES
dc.description.referencesWiers, VCS. 1997. Human–computer interaction in production scheduling: Analysis and design of decision support systems for production scheduling tasks. Ph.D. Thesis, Technische Universiteit Eindhoven, Netherlandses_ES
dc.description.referencesWiers, V. C. S. (2002). A case study on the integration of APS and ERP in a steel processing plant. Production Planning & Control, 13(6), 552-560. doi:10.1080/09537280210160321es_ES
dc.description.referencesWiers, V. C. S., & Van Der Schaaf, T. W. (1997). A framework for decision support in production scheduling tasks. Production Planning & Control, 8(6), 533-544. doi:10.1080/095372897234876es_ES
dc.description.referencesZhang, L., Krishnamurthy, A., Malmborg, C. J., & Heragu, S. S. (2009). Variance-based approximations of transaction waiting times in autonomous vehicle storage and retrieval systems. European J. of Industrial Engineering, 3(2), 146. doi:10.1504/ejie.2009.023603es_ES
dc.description.upvformatpfin1812es_ES
dc.description.upvformatpinicio1799es_ES
dc.description.volume50es_ES
dc.identifier.doi10.1080/00207543.2011.564670
dc.identifier.issn0020-7543
dc.identifier.urihttps://riunet.upv.es/handle/10251/44587
dc.languageIngléses_ES
dc.publisherTaylor &amp;amp; Francis: STM, Behavioural Science and Public Health Titleses_ES
dc.relation.ispartofInternational Journal of Production Researches_ES
dc.relation.publisherversionhttp://dx.doi.org/10.1080/00207543.2011.564670es_ES
dc.relation.references10.1080/095119299130489es_ES
dc.relation.references10.1108/01443570210433562es_ES
dc.relation.references10.1016/j.ijpe.2007.02.024es_ES
dc.relation.references10.1504/EJIE.2010.035652es_ES
dc.relation.references10.1111/j.1540-5915.1998.tb01580.xes_ES
dc.relation.references10.1287/opre.36.3.377es_ES
dc.relation.references10.1016/0377-2217(89)90349-4es_ES
dc.relation.references10.1007/s00170-003-1622-1es_ES
dc.relation.references10.1016/0954-1810(88)90024-6es_ES
dc.relation.references10.1016/S0360-8352(03)00038-Xes_ES
dc.relation.references10.1287/opre.40.1.7es_ES
dc.relation.references10.1108/02635570510592398es_ES
dc.relation.references10.1111/j.1468-0394.1984.tb00424.xes_ES
dc.relation.references10.1016/j.ejor.2009.09.026es_ES
dc.relation.references10.1080/00207540600818351es_ES
dc.relation.references10.1057/jors.1986.7es_ES
dc.relation.references10.1287/opre.29.4.646es_ES
dc.relation.references10.1080/09537289408919520es_ES
dc.relation.references10.1002/(SICI)1522-7111(199622)6:3<185::AID-HFM1>3.0.CO;2-6es_ES
dc.relation.references10.1016/0377-2217(87)90192-5es_ES
dc.relation.references10.1108/01443579310025286es_ES
dc.relation.references10.1016/0164-1212(92)90063-Pes_ES
dc.relation.references10.1007/978-3-540-24816-3es_ES
dc.relation.references10.1287/inte.26.1.6es_ES
dc.relation.references10.1080/00207549308956713es_ES
dc.relation.references10.1016/j.compind.2007.02.002es_ES
dc.relation.references10.1287/inte.18.4.84es_ES
dc.relation.references10.1002/(SICI)1099-1425(200003/04)3:2<71::AID-JOS35>3.0.CO;2-0es_ES
dc.relation.references10.1111/j.1937-5956.2002.tb00494.xes_ES
dc.relation.references10.1080/00207540801950136es_ES
dc.relation.references10.1111/j.1475-3995.1995.tb00003.xes_ES
dc.relation.references10.1016/j.cor.2008.12.018es_ES
dc.relation.references10.1023/A:1018986524234es_ES
dc.relation.references10.1287/inte.30.6.64.11623es_ES
dc.relation.references10.1109/17.618173es_ES
dc.relation.references10.1287/mnsc.38.10.1495es_ES
dc.relation.references10.1016/j.omega.2007.11.002es_ES
dc.relation.references10.1016/j.dss.2004.04.001es_ES
dc.relation.references10.1080/09537280210160321es_ES
dc.relation.references10.1080/095372897234876es_ES
dc.relation.references10.1504/EJIE.2009.023603es_ES
dc.relation.senia238736
dc.rightsReserva de todos los derechoses_ES
dc.rights.accessRightsAbiertoes_ES
dc.subjectSchedulinges_ES
dc.subjectEnterprise integrationes_ES
dc.subjectEnterprise resource planninges_ES
dc.subject.classificationESTADISTICA E INVESTIGACION OPERATIVAes_ES
dc.titleGuidelines for the deployment and implementation of manufacturing scheduling systemses_ES
dc.typeArtículoes_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
dspace.entity.typePublication
upv.uuid834e03ff-e4e3-4084-8375-3233418db71ees_ES

Archivos

Bloque original

Mostrando 1 - 2 de 2
Cargando...
Miniatura
Nombre:
Guidelines.pdf
Tamaño:
277.43 KB
Formato:
Adobe Portable Document Format
Descripción:
Versión del Autor.
Cargando...
Miniatura
Nombre:
paper.pdf
Tamaño:
154.43 KB
Formato:
Adobe Portable Document Format
Descripción:
Versión editorial