Estrategias de optimización bi-objetivo para el proceso de pesaje multicabezal

Multihead weighing processes are considered an important strategy in packaging companies. Multihead weighers are used for dosing a wide range of products, from granules to large products. The packaging process consists of choosing a subset of hoppers in the multihead weigher to form a product packag...

Full description

Autores:: Pulido-Rojano, Alexander D.
García-Díaz, J. Carlos

Tipo de recurso:

Fecha de publicación:: 2019

Institución:: Universidad Simón Bolívar

Repositorio:: Repositorio Digital USB

Idioma:: spa

id	USIMONBOL2_c7adc8a5733f3fc4a670a98313d87ede
oai_identifier_str	oai:bonga.unisimon.edu.co:20.500.12442/2842
network_acronym_str	USIMONBOL2
network_name_str	Repositorio Digital USB
repository_id_str
dc.title.spa.fl_str_mv	Estrategias de optimización bi-objetivo para el proceso de pesaje multicabezal
title	Estrategias de optimización bi-objetivo para el proceso de pesaje multicabezal
spellingShingle	Estrategias de optimización bi-objetivo para el proceso de pesaje multicabezal Bi-objective optimization Multihead weighing process Setting of hoppers Reduction of variability Optimización bi-objeivo Proceso de pesaje multicabezal Configuración de llenado de tolvas Reducción de Variabilidad
title_short	Estrategias de optimización bi-objetivo para el proceso de pesaje multicabezal
title_full	Estrategias de optimización bi-objetivo para el proceso de pesaje multicabezal
title_fullStr	Estrategias de optimización bi-objetivo para el proceso de pesaje multicabezal
title_full_unstemmed	Estrategias de optimización bi-objetivo para el proceso de pesaje multicabezal
title_sort	Estrategias de optimización bi-objetivo para el proceso de pesaje multicabezal
dc.creator.fl_str_mv	Pulido-Rojano, Alexander D. García-Díaz, J. Carlos
dc.contributor.author.none.fl_str_mv	Pulido-Rojano, Alexander D. García-Díaz, J. Carlos
dc.subject.eng.fl_str_mv	Bi-objective optimization Multihead weighing process Setting of hoppers Reduction of variability
topic	Bi-objective optimization Multihead weighing process Setting of hoppers Reduction of variability Optimización bi-objeivo Proceso de pesaje multicabezal Configuración de llenado de tolvas Reducción de Variabilidad
dc.subject.spa.fl_str_mv	Optimización bi-objeivo Proceso de pesaje multicabezal Configuración de llenado de tolvas Reducción de Variabilidad
description	Multihead weighing processes are considered an important strategy in packaging companies. Multihead weighers are used for dosing a wide range of products, from granules to large products. The packaging process consists of choosing a subset of hoppers in the multihead weigher to form a product package. This paper proposes a set of filling strategies of hoppers to reduce the variability in the weight of the produced packages. The strategies are evaluated through a bi-objective optimization approach which aims to minimize the absolute difference between the target weight and the actual weight of the packages, while trying to maximize the selection of those hoppers with more time in the packaging system. In the bi-objective approach, the considered objectives are dynamically adjusted and managed in each packaging operation. In addition, the mathematical model and the packing algorithm are developed and presented. The results of the process performance parameters are obtained and analyzed to show the effectiveness of the proposed strategies. Also, conditions of minimum variability are identified and those can be used by the packaging industry where multihead weighers are used.
publishDate	2019
dc.date.accessioned.none.fl_str_mv	2019-03-27T15:24:57Z
dc.date.available.none.fl_str_mv	2019-03-27T15:24:57Z
dc.date.issued.none.fl_str_mv	2019
dc.type.spa.fl_str_mv	article
dc.type.coar.fl_str_mv	http://purl.org/coar/resource_type/c_6501
dc.identifier.issn.none.fl_str_mv	02574306
dc.identifier.uri.none.fl_str_mv	http://hdl.handle.net/20.500.12442/2842
identifier_str_mv	02574306
url	http://hdl.handle.net/20.500.12442/2842
dc.language.iso.spa.fl_str_mv	spa
language	spa
dc.rights.coar.fl_str_mv	http://purl.org/coar/access_right/c_abf2
dc.rights.license.spa.fl_str_mv	Licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional
rights_invalid_str_mv	Licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional http://purl.org/coar/access_right/c_abf2
dc.publisher.spa.fl_str_mv	Universidad de la Habana. Facultad de Matemática y Computación. Departamento de Matemática Aplicada
dc.source.spa.fl_str_mv	Revista Investigación Operacional Vol. 40, N°3 (2019)
institution	Universidad Simón Bolívar
dc.source.uri.spa.fl_str_mv	https://rev-inv-ope.univ-paris1.fr/fileadmin/rev-inv-ope/files/40319/40319-06.pdf
bitstream.url.fl_str_mv	https://bonga.unisimon.edu.co/bitstreams/bf0a7c2d-5b8d-4e16-afbe-e7d914233fd6/download https://bonga.unisimon.edu.co/bitstreams/5a90d7ee-c031-490a-8894-44ff92470fb5/download https://bonga.unisimon.edu.co/bitstreams/c480122f-e07b-4646-b0b6-9f55ee48e662/download https://bonga.unisimon.edu.co/bitstreams/4f8924e7-0fef-4caf-b335-f4a9829677e8/download https://bonga.unisimon.edu.co/bitstreams/4875d15d-ac1e-4b82-b9e8-3be5ffbb2657/download https://bonga.unisimon.edu.co/bitstreams/8b64350d-662b-4b63-8ea4-bdd89bf07aec/download
bitstream.checksum.fl_str_mv	0cab64b5a05a2770c22c0a6010df65c1 3fdc7b41651299350522650338f5754d f4708e20297c16d7f878d8f1c328cad5 1fb3b034b88d9544aae53e78afd34fc1 c1fe6a16525ea099fbcc5112cfdc513b f6f6bea6010bf750a25c2b81a933154b
bitstream.checksumAlgorithm.fl_str_mv	MD5 MD5 MD5 MD5 MD5 MD5
repository.name.fl_str_mv	Repositorio Digital Universidad Simón Bolívar
repository.mail.fl_str_mv	repositorio.digital@unisimon.edu.co
_version_	1814076097435795456
spelling	Licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2Pulido-Rojano, Alexander D.47cdcfa7-d175-4c10-a791-acbd7631d915-1García-Díaz, J. Carlos98f0422a-d3e2-4ff9-a2c1-8dd757159d54-12019-03-27T15:24:57Z2019-03-27T15:24:57Z201902574306http://hdl.handle.net/20.500.12442/2842Multihead weighing processes are considered an important strategy in packaging companies. Multihead weighers are used for dosing a wide range of products, from granules to large products. The packaging process consists of choosing a subset of hoppers in the multihead weigher to form a product package. This paper proposes a set of filling strategies of hoppers to reduce the variability in the weight of the produced packages. The strategies are evaluated through a bi-objective optimization approach which aims to minimize the absolute difference between the target weight and the actual weight of the packages, while trying to maximize the selection of those hoppers with more time in the packaging system. In the bi-objective approach, the considered objectives are dynamically adjusted and managed in each packaging operation. In addition, the mathematical model and the packing algorithm are developed and presented. The results of the process performance parameters are obtained and analyzed to show the effectiveness of the proposed strategies. Also, conditions of minimum variability are identified and those can be used by the packaging industry where multihead weighers are used.Los procesos de pesaje multicabezal son actualmente considerados una estrategia importante en empresas de envasado. Maquinas pesadoras multicabezal son utilizadas para la dosificación de amplia gama de productos, desde granulados a productos de gran tamaño. El proceso de envasado consiste en la selección de un subconjunto de tolvas en la pesadora multicabezal para formar un paquete de producto. La presente investigación propone un conjunto de estrategias de llenado de tolvas para reducir la variabilidad en el peso de los paquetes producidos. Las estrategias son evaluadas mediante un enfoque de optimización bi-objeivo que busca minimizar la diferencia absoluta entre el peso objetivo y el peso real de los paquetes, al tiempo que intenta maximizar la selección de aquellas tolvas con mayor tiempo en el sistema de envasado. En el enfoque biobjetivo, los objetivos considerados son dinámicamente ajustados y gestionados en cada operación de envasado. Además, el modelo matemático que representa nuestro problema y el algoritmo de envasado son desarrollados y presentados. Los resultados de los parámetros de rendimiento del proceso son obtenidos y analizados como una medida de la efectividad de las estrategias propuestas. Asimismo, las condiciones de mínima variabilidad son identificadas para motivar su uso en la industria de envasado de producto en donde se utilicen máquinas de pesaje multicabezal.spaUniversidad de la Habana. Facultad de Matemática y Computación. Departamento de Matemática AplicadaRevista Investigación OperacionalVol. 40, N°3 (2019)https://rev-inv-ope.univ-paris1.fr/fileadmin/rev-inv-ope/files/40319/40319-06.pdfBi-objective optimizationMultihead weighing processSetting of hoppersReduction of variabilityOptimización bi-objeivoProceso de pesaje multicabezalConfiguración de llenado de tolvasReducción de VariabilidadEstrategias de optimización bi-objetivo para el proceso de pesaje multicabezalarticlehttp://purl.org/coar/resource_type/c_6501BERETTA, A. and SEMERARO¸ Q. (2012): On a RSM approach to the multihead weigher configuration. The 11th biennial Conference on Engineering Systems Design and Analysis, Nantes, France.BERETTA, A. SEMERARO¸ Q. and DEL CASTILLO, E. (2016): On the Multihead Weigher Machine Setup Problem. Packaging Technology and Science, 29 , 175 –188.BIERLAIRE, M. (2015): Optimization: principles and algorithms, 1st edition. EPFL Press, Lausana.BLUM, C., BLESA-AGUILERA, M.J., ROLI, A. and SAMPELS, M. (2008): Hybrid Metaheuristics: An Emerging Approach to Optimization. Springer, Berlin.COOK, W., CUNNINGHAM, W., PULLEYBLANK, W. and SCHRIJVER, A. (1998): Combinatorial Optimization. John Wiley & Sons, New York.DEL CASTILLO, E., BERETTA A. and SEMERARO, Q. (2017): Optimal setup of a multihead weighing machine. European Journal of Operational Research, 259, 384 – 393.DUARTE, A., PANTRIGO, J.J. and GALLEGO CARRILLO, M. (2007): Metahuerísticas. Dykinson, S.L., Madrid.EHRGOTT, M. (2005): Multicriteria Optimization (2nd ed)., Springer, Berlin.ERDOGDU, F. (2009): Optimization in Food Engineering. Taylor and Francis, London.GAREY M.R. and JOHNSON, D.S. (1979): Computers and Intractability: A guide to the Theory of NP-Completeness. WH Freeman and Company, New York.GARCÍA-DÍAZ, J.C. and PULIDO-ROJANO, A. (2017): Monitoring and control of the multihead weighing process through a modified control chart. DYNA, 84, 135-142.GARCÍA-DÍAZ, J.C., PULIDO-ROJANO, A. and GINER-BOSCH, V. (2017): Bi-objective optimisation of a multihead weighing process. European Journal of Industrial Engineering, 11, 403 – 423.IMAHORI, S., KARUNO, Y., NAGAMOCHI, H. and WANG, X. (2011): Kansei engineering humans and computers: Efficient dynamic programming algorithms for combinatorial food packing problems. International Journal of Biometrics, 3, 228-245.IMAHORI, S., KARUNO, Y., NISHIZAKI R. and YOSHIMOTO, Y. (2012): Duplex and Quasi- Duplex Operations in Automated Food Packing Systems. International Symposium on System Integration (SII), Fukuoka, Japan.KARUNO, Y., NAGAMOCHI, H. and WANG, X. (2007): Bi-criteria food packing by dynamic programming. Journal of the Operations Research Society of Japan, 50, 376-389.KARUNO, Y., NAGAMOCHI, H. and WANG, X. (2010): Optimization Problems and Algorithms in Double-layered Food Packing Systems. Journal of Advanced Mechanical Design, System, and Manufacturing, 4, 605-615.KARUNO, Y., TAKAHASHI K. and YAMADA, A. (2013): Dynamic Programming Algorithms with data rounding for combinatorial food packing problems. Journal of Advanced Mechanical Design, System, and Manufacturing, 7, 233-243.KARUNO Y. and TATEISHI, K. (2014): Improved Heuristics with data rounding for combinatorial food packing problems. IEEE 2014 7th international conference on service-oriented computing and applications, Matsue, Japan.KARUNO Y. and SAITO, R. (2017): Heuristic algorithms with rounded weights for a combinatorial food packing problem. Journal of Advanced Mechanical Design, System, and Manufacturing, 11, DOI: https://doi.org/10.1299/jamdsm.2017jamdsm0003.KERAITA, J.N. and KIM, K-H. (2006): A Study on the optimum scheme for Determination of Operation time of Line Feeders in Automatic Combination Weighers. Journal of Mechanical Science and Technology, 20, 1567-1575.KERAITA, J.N. and KIM, K-H. (2007): A Weighing Algorithm for Multihead Weighers. International Journal of Precision Engineering and Manufacturing, 8, 21-26.MARLER, T. (2009): Multi-Objective Optimization: Concepts and Methods for Engineering. VDM Verlag, Saarbrücken.MARLER, R.T. and ARORA, J.S. (2004): Survey of multi-objective optimization methods for engineering. Structural and Multidisciplinary Optimization, 26, 369–395.PULIDO-ROJANO, A., GARCÍA-DÍAZ, J.C. and GINER-BOSCH, V. (2015): A multiobjective approach for optimization of the multihead weighing process. International Conference on Industrial Engineering and Systems Management (IEEE-IESM’2015), Seville, Spain.PULIDO-ROJANO, A. and GARCÍA-DÍAZ, J.C. (2014): Optimization of multihead weighing process using the Taguchi loss function. IIE International 8th International Conference on Industrial Engineering and Industrial Management and XX International Conference on Industrial Engineering and Operations Management, Málaga, Spain.PULIDO-ROJANO, A. and GARCÍA-DÍAZ, J.C. (2016): Analysis of the Filling Setting in the Multihead Weighing Process. International Joint Conference - CIO-ICIEOM-IIE-AIM, Donostia- San Sebastián, Spain.PULIDO-ROJANO, A. and GARCÍA-DÍAZ, J.C. (2016): A modified control chart for monitoring the multihead weighing process. International Conference on Computational Statistics (COMPSTAT), Oviedo, Spain.PULIDO-ROJANO, A. y GARCÍA-DÍAZ, J.C. (2018): Simulación y mejora del proceso de pesaje multicabezal. Decima Séptima Conferencia Iberoamericana en Sistemas, Cibernetica e Informatica (CISCI 2018), Orlando-Florida, EEUU.PULIDO-ROJANO, A., SANCHEZ-SANCHEZ, P. y MELAMED-VARELA, E. (2018): Nuevas tendencias en Investigación de Operaciones y Ciencias Administrativas: Un enfoque desde estudios iberoamericanos. Ediciones Universidad Simón Bolívar, Barranquilla, Colombia. ISBN: 978-958-5430-88-4.RIQUELME, P., GATICA, G. y OROZCO. E. (2015): Diseño de un Modelo de Operación para Ruteo de Transporte Urbano Basado en Simulación Discreta. Investigación e Innovación en Ingenierías, 3,10.17081/invinno.3.2.2026SÁNCHEZ-SÁNCHEZ, P., GARCÍA-GONZÁLEZ, J. R., FAJARDO TORO, C. H., PULIDOROJANO. A. y MELAMED-VARELA, E. (2018): Simulación de sistemas de emergencia en salud. En: Pulido-Rojano, A., Sánchez-Sánchez, P. y Melamed-Varela. E. (eds.). Nuevas tendencias en investigación de operaciones y ciencias administrativas: Un enfoque desde estudios iberoamericanos, 165-210. Ediciones Universidad Simón Bolívar, Barranquilla, Colombia.ORIGINALPDF.pdfPDF.pdfPDFapplication/pdf11640459https://bonga.unisimon.edu.co/bitstreams/bf0a7c2d-5b8d-4e16-afbe-e7d914233fd6/download0cab64b5a05a2770c22c0a6010df65c1MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-8368https://bonga.unisimon.edu.co/bitstreams/5a90d7ee-c031-490a-8894-44ff92470fb5/download3fdc7b41651299350522650338f5754dMD52TEXTEstrategias de optimización bi-objetivo para el proceso de pesaje multicabezal.pdf.txtEstrategias de optimización bi-objetivo para el proceso de pesaje multicabezal.pdf.txtExtracted texttext/plain48291https://bonga.unisimon.edu.co/bitstreams/c480122f-e07b-4646-b0b6-9f55ee48e662/downloadf4708e20297c16d7f878d8f1c328cad5MD53PDF.pdf.txtPDF.pdf.txtExtracted texttext/plain48596https://bonga.unisimon.edu.co/bitstreams/4f8924e7-0fef-4caf-b335-f4a9829677e8/download1fb3b034b88d9544aae53e78afd34fc1MD55THUMBNAILEstrategias de optimización bi-objetivo para el proceso de pesaje multicabezal.pdf.jpgEstrategias de optimización bi-objetivo para el proceso de pesaje multicabezal.pdf.jpgGenerated Thumbnailimage/jpeg1689https://bonga.unisimon.edu.co/bitstreams/4875d15d-ac1e-4b82-b9e8-3be5ffbb2657/downloadc1fe6a16525ea099fbcc5112cfdc513bMD54PDF.pdf.jpgPDF.pdf.jpgGenerated Thumbnailimage/jpeg5097https://bonga.unisimon.edu.co/bitstreams/8b64350d-662b-4b63-8ea4-bdd89bf07aec/downloadf6f6bea6010bf750a25c2b81a933154bMD5620.500.12442/2842oai:bonga.unisimon.edu.co:20.500.12442/28422024-07-26 03:02:04.348open.accesshttps://bonga.unisimon.edu.coRepositorio Digital Universidad Simón Bolívarrepositorio.digital@unisimon.edu.coPGEgcmVsPSJsaWNlbnNlIiBocmVmPSJodHRwOi8vY3JlYXRpdmVjb21tb25zLm9yZy9saWNlbnNlcy9ieS1uYy80LjAvIj48aW1nIGFsdD0iTGljZW5jaWEgQ3JlYXRpdmUgQ29tbW9ucyIgc3R5bGU9ImJvcmRlci13aWR0aDowIiBzcmM9Imh0dHBzOi8vaS5jcmVhdGl2ZWNvbW1vbnMub3JnL2wvYnktbmMvNC4wLzg4eDMxLnBuZyIgLz48L2E+PGJyLz5Fc3RhIG9icmEgZXN0w6EgYmFqbyB1bmEgPGEgcmVsPSJsaWNlbnNlIiBocmVmPSJodHRwOi8vY3JlYXRpdmVjb21tb25zLm9yZy9saWNlbnNlcy9ieS1uYy80LjAvIj5MaWNlbmNpYSBDcmVhdGl2ZSBDb21tb25zIEF0cmlidWNpw7NuLU5vQ29tZXJjaWFsIDQuMCBJbnRlcm5hY2lvbmFsPC9hPi4=

Estrategias de optimización bi-objetivo para el proceso de pesaje multicabezal

Publicaciones similares