Simulação da dinâmica operacional de um processo industrial de abate de aves

Detalhes bibliográficos
Autor(a) principal: Ebert, Douglas Cezar
Data de Publicação: 2007
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Biblioteca Digital de Teses e Dissertações do UNIOESTE
Texto Completo: http://tede.unioeste.br:8080/tede/handle/tede/2679
Resumo: Slaughter and meat processing of poultries occur at the environment called poultry slaughter industry where are carried out unitary operations logically organized. According to Operations Research fundaments a poultry slaughter industry is characterized as system which is associated the following factors: (i) input variables example: daily number of poultries to be slaughtered; and daily schedules; (ii) system parameters example: processing rates and water and vapor availabilities; and (iii) output variables example: production quantities of meats and derivatives, fixed and variable costs, and waist volumes. In reason of the number of factors involved, and the fact of theses could be stochastic, it is hard to define mental scenarios to support decision processes. In reason of that, use of simulation technique is appropriate, because it permit to realize experiments such as: sensitivity analysis, scenario analysis, optimization, and Monte Carlo simulation. Therefore, this work was carried out with objective to develop a computational model, using the simulation language EXTENDTM to (a) simulate the dynamic of poultry slaughter industry; and (b) realize sensitivity analysis. Developed model was classified as dynamic, stochastic and discrete. The real system modeled is located in Paraná State at Southwest Region and has daily slaughter capacity of 500,000 poultries, using three processing lines and operating in three daily schedules. At model validation was obtained data related to three schedules that were slaughtered 174,239; 166,870 and 144,021 poultries, respectively. Output variables contrasted, considering data obtained from system and generated by model, were: (i) processing time; (i) total live weight (kg); (iii) available live weight (kg); (iv) sub product weight (kg); (v) total production weight (kg); (vi) whole slaughtered poultry weight (kg); and (vii) total slaughtered poultry part weight (kg). Sensitivity analysis carried out, by changes lines processing rates in 7,000; 8,000 and 9,000 poultries per hour, showed the following averages for processing time 8.69, 7.86 and 7.86 hours, respectively. Results demonstrate that for current situation, the increase of processing rates in 9,000 poultries h-1 does not imply in a directly decrease of processing time, because current frequency of cargos arrives can establish idle periods of poultry slaughter facility.
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spelling Silva, Luis César daCPF:49709771604http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4793547H0Boas, Marcio Antonio VilasCPF:55200834600http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4723608D4&dataRevisao=nullChrist, DivairCPF:66206863972http://lattes.cnpq.br/6200553304840204Yamaguchi, Margarida MasamiCPF:57846609630http://lattes.cnpq.br/5674856275136661CPF:64408841900http://lattes.cnpq.br/1801334165088213Ebert, Douglas Cezar2017-07-10T19:23:59Z2007-12-102007-07-17EBERT, Douglas Cezar. Dynamic simulation of an industrial process of poultry slaughter. 2007. 64 f. Dissertação (Mestrado em Engenharia) - Universidade Estadual do Oeste do Parana, Cascavel, 2007.http://tede.unioeste.br:8080/tede/handle/tede/2679Slaughter and meat processing of poultries occur at the environment called poultry slaughter industry where are carried out unitary operations logically organized. According to Operations Research fundaments a poultry slaughter industry is characterized as system which is associated the following factors: (i) input variables example: daily number of poultries to be slaughtered; and daily schedules; (ii) system parameters example: processing rates and water and vapor availabilities; and (iii) output variables example: production quantities of meats and derivatives, fixed and variable costs, and waist volumes. In reason of the number of factors involved, and the fact of theses could be stochastic, it is hard to define mental scenarios to support decision processes. In reason of that, use of simulation technique is appropriate, because it permit to realize experiments such as: sensitivity analysis, scenario analysis, optimization, and Monte Carlo simulation. Therefore, this work was carried out with objective to develop a computational model, using the simulation language EXTENDTM to (a) simulate the dynamic of poultry slaughter industry; and (b) realize sensitivity analysis. Developed model was classified as dynamic, stochastic and discrete. The real system modeled is located in Paraná State at Southwest Region and has daily slaughter capacity of 500,000 poultries, using three processing lines and operating in three daily schedules. At model validation was obtained data related to three schedules that were slaughtered 174,239; 166,870 and 144,021 poultries, respectively. Output variables contrasted, considering data obtained from system and generated by model, were: (i) processing time; (i) total live weight (kg); (iii) available live weight (kg); (iv) sub product weight (kg); (v) total production weight (kg); (vi) whole slaughtered poultry weight (kg); and (vii) total slaughtered poultry part weight (kg). Sensitivity analysis carried out, by changes lines processing rates in 7,000; 8,000 and 9,000 poultries per hour, showed the following averages for processing time 8.69, 7.86 and 7.86 hours, respectively. Results demonstrate that for current situation, the increase of processing rates in 9,000 poultries h-1 does not imply in a directly decrease of processing time, because current frequency of cargos arrives can establish idle periods of poultry slaughter facility.O abate de aves e o processamento da carne desenrolam-se no ambiente denominado matadouro-frigorífico em que são realizadas operações unitárias, lógicas e seqüenciadas. De acordo com os preceitos da Pesquisa Operacional, um matadouro-frigorífico é caracterizado como um sistema quando os fatores associados são: (i) variáveis de entrada - exemplos: número de aves abatidas diariamente e turnos de funcionamento; (ii) parâmetros do sistema, exemplos: velocidades das linhas de processamento e disponibilidades de água e vapor; e (iii) variáveis de saída - exemplos: volumes de produção de carnes e derivados, custos fixos e variáveis e volume de dejetos. Em razão do número de fatores envolvidos e, além disso, devido ao fato desses poderem ser estocásticos; tornase árdua a definição mental de cenários para fundamentação de tomadas de decisão. Perante essa situação, o uso da técnica de simulação é pertinente por propiciar a condução de experimentos tais como: análise de sensibilidade, comparação de cenários, otimização e simulação de Monte Carlo. Deste modo, o presente trabalho foi conduzido com o objetivo de implementar um modelo computacional, por meio da linguagem de simulação EXTENDTM, para: (a) simular a dinâmica de atividades de um matadouro-frigorífico de aves e (b) conduzir análises de sensibilidade. O modelo implementado foi classificado como dinâmico, estocástico e discreto. O sistema real modelado está localizado na Região Sudoeste do Paraná e tem capacidade diária de abate próxima a 500.000 aves, utilizando-se três linhas de processamento, com operação em três turnos de trabalho diários. Para validação do modelo, foram coletados dados relativos a três turnos, em que foram abatidas 174.239, 166.870 e 144.021 aves, respectivamente. As variáveis de saída comparadas, considerando os dados obtidos do sistema real e gerados pelo modelo, foram: (i) tempo de processamento; (ii) peso vivo total; (iii) peso vivo aproveitado; (iv) peso de subproduto; (v) peso produção total; (vi) peso frango inteiro; (vii) peso total cortes. O modelo apresentou-se aplicável, uma vez que os erros médios percentuais foram inferiores a 1% para as variáveis comparadas. Análises de sensibilidades, conduzidas mediante as alterações das velocidades de processamento das linhas em 7.000, 8.000 e 9.000 frangos h-1, apresentaram os seguintes valores médios para variável tempo de processamento: 8,69, 7,86 e 7,86 horas, respectivamente. Os resultados demonstram que, para a atual situação, o aumento da velocidade de processamento para 9.000 frangos h-1 não implicará diretamente na redução do tempo de processamento, pois, a cadência atual da chegada das cargas do campo pode estabelecer períodos de ociosidade do matadouro-frigorífico.Made available in DSpace on 2017-07-10T19:23:59Z (GMT). No. of bitstreams: 1 Douglas Cezar Ebert.pdf: 309790 bytes, checksum: f0e2ece9bbf557060d09d5530f238727 (MD5) Previous issue date: 2007-07-17application/pdfporUniversidade Estadual do Oeste do ParanaPrograma de Pós-Graduação "Stricto Sensu" em Engenharia AgrícolaUNIOESTEBREngenhariacarnematadouropesquisa operacionalmeatslaughter industryoperations researchCNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLASimulação da dinâmica operacional de um processo industrial de abate de avesDynamic simulation of an industrial process of poultry slaughterinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações do UNIOESTEinstname:Universidade Estadual do Oeste do Paraná (UNIOESTE)instacron:UNIOESTEORIGINALDouglas Cezar Ebert.pdfapplication/pdf309790http://tede.unioeste.br:8080/tede/bitstream/tede/2679/1/Douglas+Cezar+Ebert.pdff0e2ece9bbf557060d09d5530f238727MD51tede/26792017-07-10 16:23:59.672oai:tede.unioeste.br:tede/2679Biblioteca Digital de Teses e Dissertaçõeshttp://tede.unioeste.br/PUBhttp://tede.unioeste.br/oai/requestbiblioteca.repositorio@unioeste.bropendoar:2017-07-10T19:23:59Biblioteca Digital de Teses e Dissertações do UNIOESTE - Universidade Estadual do Oeste do Paraná (UNIOESTE)false
dc.title.por.fl_str_mv Simulação da dinâmica operacional de um processo industrial de abate de aves
dc.title.alternative.eng.fl_str_mv Dynamic simulation of an industrial process of poultry slaughter
title Simulação da dinâmica operacional de um processo industrial de abate de aves
spellingShingle Simulação da dinâmica operacional de um processo industrial de abate de aves
Ebert, Douglas Cezar
carne
matadouro
pesquisa operacional
meat
slaughter industry
operations research
CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA
title_short Simulação da dinâmica operacional de um processo industrial de abate de aves
title_full Simulação da dinâmica operacional de um processo industrial de abate de aves
title_fullStr Simulação da dinâmica operacional de um processo industrial de abate de aves
title_full_unstemmed Simulação da dinâmica operacional de um processo industrial de abate de aves
title_sort Simulação da dinâmica operacional de um processo industrial de abate de aves
author Ebert, Douglas Cezar
author_facet Ebert, Douglas Cezar
author_role author
dc.contributor.advisor1.fl_str_mv Silva, Luis César da
dc.contributor.advisor1ID.fl_str_mv CPF:49709771604
dc.contributor.advisor1Lattes.fl_str_mv http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4793547H0
dc.contributor.advisor-co1.fl_str_mv Boas, Marcio Antonio Vilas
dc.contributor.advisor-co1ID.fl_str_mv CPF:55200834600
dc.contributor.advisor-co1Lattes.fl_str_mv http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4723608D4&dataRevisao=null
dc.contributor.referee1.fl_str_mv Christ, Divair
dc.contributor.referee1ID.fl_str_mv CPF:66206863972
dc.contributor.referee1Lattes.fl_str_mv http://lattes.cnpq.br/6200553304840204
dc.contributor.referee2.fl_str_mv Yamaguchi, Margarida Masami
dc.contributor.referee2ID.fl_str_mv CPF:57846609630
dc.contributor.referee2Lattes.fl_str_mv http://lattes.cnpq.br/5674856275136661
dc.contributor.authorID.fl_str_mv CPF:64408841900
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/1801334165088213
dc.contributor.author.fl_str_mv Ebert, Douglas Cezar
contributor_str_mv Silva, Luis César da
Boas, Marcio Antonio Vilas
Christ, Divair
Yamaguchi, Margarida Masami
dc.subject.por.fl_str_mv carne
matadouro
pesquisa operacional
topic carne
matadouro
pesquisa operacional
meat
slaughter industry
operations research
CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA
dc.subject.eng.fl_str_mv meat
slaughter industry
operations research
dc.subject.cnpq.fl_str_mv CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA
description Slaughter and meat processing of poultries occur at the environment called poultry slaughter industry where are carried out unitary operations logically organized. According to Operations Research fundaments a poultry slaughter industry is characterized as system which is associated the following factors: (i) input variables example: daily number of poultries to be slaughtered; and daily schedules; (ii) system parameters example: processing rates and water and vapor availabilities; and (iii) output variables example: production quantities of meats and derivatives, fixed and variable costs, and waist volumes. In reason of the number of factors involved, and the fact of theses could be stochastic, it is hard to define mental scenarios to support decision processes. In reason of that, use of simulation technique is appropriate, because it permit to realize experiments such as: sensitivity analysis, scenario analysis, optimization, and Monte Carlo simulation. Therefore, this work was carried out with objective to develop a computational model, using the simulation language EXTENDTM to (a) simulate the dynamic of poultry slaughter industry; and (b) realize sensitivity analysis. Developed model was classified as dynamic, stochastic and discrete. The real system modeled is located in Paraná State at Southwest Region and has daily slaughter capacity of 500,000 poultries, using three processing lines and operating in three daily schedules. At model validation was obtained data related to three schedules that were slaughtered 174,239; 166,870 and 144,021 poultries, respectively. Output variables contrasted, considering data obtained from system and generated by model, were: (i) processing time; (i) total live weight (kg); (iii) available live weight (kg); (iv) sub product weight (kg); (v) total production weight (kg); (vi) whole slaughtered poultry weight (kg); and (vii) total slaughtered poultry part weight (kg). Sensitivity analysis carried out, by changes lines processing rates in 7,000; 8,000 and 9,000 poultries per hour, showed the following averages for processing time 8.69, 7.86 and 7.86 hours, respectively. Results demonstrate that for current situation, the increase of processing rates in 9,000 poultries h-1 does not imply in a directly decrease of processing time, because current frequency of cargos arrives can establish idle periods of poultry slaughter facility.
publishDate 2007
dc.date.available.fl_str_mv 2007-12-10
dc.date.issued.fl_str_mv 2007-07-17
dc.date.accessioned.fl_str_mv 2017-07-10T19:23:59Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
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dc.identifier.citation.fl_str_mv EBERT, Douglas Cezar. Dynamic simulation of an industrial process of poultry slaughter. 2007. 64 f. Dissertação (Mestrado em Engenharia) - Universidade Estadual do Oeste do Parana, Cascavel, 2007.
dc.identifier.uri.fl_str_mv http://tede.unioeste.br:8080/tede/handle/tede/2679
identifier_str_mv EBERT, Douglas Cezar. Dynamic simulation of an industrial process of poultry slaughter. 2007. 64 f. Dissertação (Mestrado em Engenharia) - Universidade Estadual do Oeste do Parana, Cascavel, 2007.
url http://tede.unioeste.br:8080/tede/handle/tede/2679
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dc.publisher.program.fl_str_mv Programa de Pós-Graduação "Stricto Sensu" em Engenharia Agrícola
dc.publisher.initials.fl_str_mv UNIOESTE
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dc.publisher.department.fl_str_mv Engenharia
publisher.none.fl_str_mv Universidade Estadual do Oeste do Parana
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