A multi-period programming model for the production optimization of a polyurethane foaming plant

Autores
Rodriguez, Maria Analia; Vecchietti, Aldo; Montagna, Jorge Marcelo; Corsano, Gabriela
Año de publicación
2016
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
This work presents a multi-period production planning model for the simultaneous optimization of the manufacturing process and the stock management of a polyurethane foaming plant. The basic stages of the plant consist of the blooming process that produces polyurethane foam pieces with certain characteristics such as density and dimensional features, and the curing stage that involves the location of these pieces in a limited area during certain time such that the produced blocks attain the required properties: temperature, rigidity and stability. After this time, the blocks get the necessary conditions to be stored and further processed.A single foaming machine is used for producing the polyurethane blocks of different densities and dimensions and a long setup machine is required between width changes. The objective function considers the cost of the set up involved, mainly labor cost, when a change of width is required from one day to the other. Also a loss of material occurs when a transition of densities is presented. This cost is included in the objective function. In summary, the model performance measure takes into account the cost of width and density changes in the production plan and penalizes unsatisfied demand and unfulfilled safety stock.Due to the volume of the foam pieces and the limited area of the curing step and the final storage, an efficient stock management is crucial in order to minimize costs and satisfy demand; and that is the reason to include those decisions in the production planning model. As it was mentioned, a multi-period approach is considered where the production requirements based on the estimated demand are known. The proposed model provides a detailed production program for a set of days selected by the manager, while a more general plan is obtained for the rest of the days of the planning horizon, in an overall multi-period formulation. The detailed program includes information about how to place the foamed blocks in the curing area taking into account precedence constraints. The purpose of the first part of the plan is to facilitate the production decisions on the plant floor considering all relevant constraints involved in the process. On the other hand, the approximated production plan, determined for the rest of the days in the planning horizon, gives information to estimate raw material purchases, labor requirements and operational costs, among others. In addition, for each day in the planning horizon, the model determines the blocks to be foamed and the inventory management. Several relations among the problem stages and the involved decisions are assessed; therefore a Generalized Disjunctive Programming (GDP) approach allows a clear outline of the simultaneous optimization problem. GDP provides a quantitative and qualitative framework to formulate the problem and their relationships in a natural way. Different study cases are solved which represent typical plant floor scenarios and their solutions are compared, in order to assess the model capabilities and facilitate the decision-making of the company.
Fil: Rodriguez, Maria Analia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (I). Grupo Vinculado al Plapiqui - Investigación y Desarrollo en Tecnología Química; Argentina
Fil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Montagna, Jorge Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Corsano, Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
5th International Conference on Engineering Optimization
Cataras del Iguazú
Brasil
Universidad Federal de Río de Janeiro
Materia
MULTI-PERIOD PLANNING
POLYURETHANE FOAMING PLANT
MILP
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/162709

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network_name_str CONICET Digital (CONICET)
spelling A multi-period programming model for the production optimization of a polyurethane foaming plantRodriguez, Maria AnaliaVecchietti, AldoMontagna, Jorge MarceloCorsano, GabrielaMULTI-PERIOD PLANNINGPOLYURETHANE FOAMING PLANTMILPhttps://purl.org/becyt/ford/2.11https://purl.org/becyt/ford/2This work presents a multi-period production planning model for the simultaneous optimization of the manufacturing process and the stock management of a polyurethane foaming plant. The basic stages of the plant consist of the blooming process that produces polyurethane foam pieces with certain characteristics such as density and dimensional features, and the curing stage that involves the location of these pieces in a limited area during certain time such that the produced blocks attain the required properties: temperature, rigidity and stability. After this time, the blocks get the necessary conditions to be stored and further processed.A single foaming machine is used for producing the polyurethane blocks of different densities and dimensions and a long setup machine is required between width changes. The objective function considers the cost of the set up involved, mainly labor cost, when a change of width is required from one day to the other. Also a loss of material occurs when a transition of densities is presented. This cost is included in the objective function. In summary, the model performance measure takes into account the cost of width and density changes in the production plan and penalizes unsatisfied demand and unfulfilled safety stock.Due to the volume of the foam pieces and the limited area of the curing step and the final storage, an efficient stock management is crucial in order to minimize costs and satisfy demand; and that is the reason to include those decisions in the production planning model. As it was mentioned, a multi-period approach is considered where the production requirements based on the estimated demand are known. The proposed model provides a detailed production program for a set of days selected by the manager, while a more general plan is obtained for the rest of the days of the planning horizon, in an overall multi-period formulation. The detailed program includes information about how to place the foamed blocks in the curing area taking into account precedence constraints. The purpose of the first part of the plan is to facilitate the production decisions on the plant floor considering all relevant constraints involved in the process. On the other hand, the approximated production plan, determined for the rest of the days in the planning horizon, gives information to estimate raw material purchases, labor requirements and operational costs, among others. In addition, for each day in the planning horizon, the model determines the blocks to be foamed and the inventory management. Several relations among the problem stages and the involved decisions are assessed; therefore a Generalized Disjunctive Programming (GDP) approach allows a clear outline of the simultaneous optimization problem. GDP provides a quantitative and qualitative framework to formulate the problem and their relationships in a natural way. Different study cases are solved which represent typical plant floor scenarios and their solutions are compared, in order to assess the model capabilities and facilitate the decision-making of the company.Fil: Rodriguez, Maria Analia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (I). Grupo Vinculado al Plapiqui - Investigación y Desarrollo en Tecnología Química; ArgentinaFil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Montagna, Jorge Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Corsano, Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina5th International Conference on Engineering OptimizationCataras del IguazúBrasilUniversidad Federal de Río de JaneiroUniversidad Federal de Río de Janeiro2016info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectConferenciaBookhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/162709A multi-period programming model for the production optimization of a polyurethane foaming plant; 5th International Conference on Engineering Optimization; Cataras del Iguazú; Brasil; 2016; 1-2978-85-7650-522-8CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://engopt.org/view_abstract.php?cod=71Internacionalinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:40:33Zoai:ri.conicet.gov.ar:11336/162709instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:40:33.35CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A multi-period programming model for the production optimization of a polyurethane foaming plant
title A multi-period programming model for the production optimization of a polyurethane foaming plant
spellingShingle A multi-period programming model for the production optimization of a polyurethane foaming plant
Rodriguez, Maria Analia
MULTI-PERIOD PLANNING
POLYURETHANE FOAMING PLANT
MILP
title_short A multi-period programming model for the production optimization of a polyurethane foaming plant
title_full A multi-period programming model for the production optimization of a polyurethane foaming plant
title_fullStr A multi-period programming model for the production optimization of a polyurethane foaming plant
title_full_unstemmed A multi-period programming model for the production optimization of a polyurethane foaming plant
title_sort A multi-period programming model for the production optimization of a polyurethane foaming plant
dc.creator.none.fl_str_mv Rodriguez, Maria Analia
Vecchietti, Aldo
Montagna, Jorge Marcelo
Corsano, Gabriela
author Rodriguez, Maria Analia
author_facet Rodriguez, Maria Analia
Vecchietti, Aldo
Montagna, Jorge Marcelo
Corsano, Gabriela
author_role author
author2 Vecchietti, Aldo
Montagna, Jorge Marcelo
Corsano, Gabriela
author2_role author
author
author
dc.subject.none.fl_str_mv MULTI-PERIOD PLANNING
POLYURETHANE FOAMING PLANT
MILP
topic MULTI-PERIOD PLANNING
POLYURETHANE FOAMING PLANT
MILP
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.11
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv This work presents a multi-period production planning model for the simultaneous optimization of the manufacturing process and the stock management of a polyurethane foaming plant. The basic stages of the plant consist of the blooming process that produces polyurethane foam pieces with certain characteristics such as density and dimensional features, and the curing stage that involves the location of these pieces in a limited area during certain time such that the produced blocks attain the required properties: temperature, rigidity and stability. After this time, the blocks get the necessary conditions to be stored and further processed.A single foaming machine is used for producing the polyurethane blocks of different densities and dimensions and a long setup machine is required between width changes. The objective function considers the cost of the set up involved, mainly labor cost, when a change of width is required from one day to the other. Also a loss of material occurs when a transition of densities is presented. This cost is included in the objective function. In summary, the model performance measure takes into account the cost of width and density changes in the production plan and penalizes unsatisfied demand and unfulfilled safety stock.Due to the volume of the foam pieces and the limited area of the curing step and the final storage, an efficient stock management is crucial in order to minimize costs and satisfy demand; and that is the reason to include those decisions in the production planning model. As it was mentioned, a multi-period approach is considered where the production requirements based on the estimated demand are known. The proposed model provides a detailed production program for a set of days selected by the manager, while a more general plan is obtained for the rest of the days of the planning horizon, in an overall multi-period formulation. The detailed program includes information about how to place the foamed blocks in the curing area taking into account precedence constraints. The purpose of the first part of the plan is to facilitate the production decisions on the plant floor considering all relevant constraints involved in the process. On the other hand, the approximated production plan, determined for the rest of the days in the planning horizon, gives information to estimate raw material purchases, labor requirements and operational costs, among others. In addition, for each day in the planning horizon, the model determines the blocks to be foamed and the inventory management. Several relations among the problem stages and the involved decisions are assessed; therefore a Generalized Disjunctive Programming (GDP) approach allows a clear outline of the simultaneous optimization problem. GDP provides a quantitative and qualitative framework to formulate the problem and their relationships in a natural way. Different study cases are solved which represent typical plant floor scenarios and their solutions are compared, in order to assess the model capabilities and facilitate the decision-making of the company.
Fil: Rodriguez, Maria Analia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (I). Grupo Vinculado al Plapiqui - Investigación y Desarrollo en Tecnología Química; Argentina
Fil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Montagna, Jorge Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Corsano, Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
5th International Conference on Engineering Optimization
Cataras del Iguazú
Brasil
Universidad Federal de Río de Janeiro
description This work presents a multi-period production planning model for the simultaneous optimization of the manufacturing process and the stock management of a polyurethane foaming plant. The basic stages of the plant consist of the blooming process that produces polyurethane foam pieces with certain characteristics such as density and dimensional features, and the curing stage that involves the location of these pieces in a limited area during certain time such that the produced blocks attain the required properties: temperature, rigidity and stability. After this time, the blocks get the necessary conditions to be stored and further processed.A single foaming machine is used for producing the polyurethane blocks of different densities and dimensions and a long setup machine is required between width changes. The objective function considers the cost of the set up involved, mainly labor cost, when a change of width is required from one day to the other. Also a loss of material occurs when a transition of densities is presented. This cost is included in the objective function. In summary, the model performance measure takes into account the cost of width and density changes in the production plan and penalizes unsatisfied demand and unfulfilled safety stock.Due to the volume of the foam pieces and the limited area of the curing step and the final storage, an efficient stock management is crucial in order to minimize costs and satisfy demand; and that is the reason to include those decisions in the production planning model. As it was mentioned, a multi-period approach is considered where the production requirements based on the estimated demand are known. The proposed model provides a detailed production program for a set of days selected by the manager, while a more general plan is obtained for the rest of the days of the planning horizon, in an overall multi-period formulation. The detailed program includes information about how to place the foamed blocks in the curing area taking into account precedence constraints. The purpose of the first part of the plan is to facilitate the production decisions on the plant floor considering all relevant constraints involved in the process. On the other hand, the approximated production plan, determined for the rest of the days in the planning horizon, gives information to estimate raw material purchases, labor requirements and operational costs, among others. In addition, for each day in the planning horizon, the model determines the blocks to be foamed and the inventory management. Several relations among the problem stages and the involved decisions are assessed; therefore a Generalized Disjunctive Programming (GDP) approach allows a clear outline of the simultaneous optimization problem. GDP provides a quantitative and qualitative framework to formulate the problem and their relationships in a natural way. Different study cases are solved which represent typical plant floor scenarios and their solutions are compared, in order to assess the model capabilities and facilitate the decision-making of the company.
publishDate 2016
dc.date.none.fl_str_mv 2016
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A multi-period programming model for the production optimization of a polyurethane foaming plant; 5th International Conference on Engineering Optimization; Cataras del Iguazú; Brasil; 2016; 1-2
978-85-7650-522-8
CONICET Digital
CONICET
url http://hdl.handle.net/11336/162709
identifier_str_mv A multi-period programming model for the production optimization of a polyurethane foaming plant; 5th International Conference on Engineering Optimization; Cataras del Iguazú; Brasil; 2016; 1-2
978-85-7650-522-8
CONICET Digital
CONICET
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dc.publisher.none.fl_str_mv Universidad Federal de Río de Janeiro
publisher.none.fl_str_mv Universidad Federal de Río de Janeiro
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