Technical-economic analysis of grapple saw: A stochastic approach
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.5552/crojfe.2020.681 http://hdl.handle.net/11449/200427 |
Resumo: | The processing of Eucalyptus logs is a stage that follows the full tree system in mechanized forest harvesting, commonly performed by grapple saw. Therefore, this activity presents some as-sociated uncertainties, especially regarding technical and silvicultural factors that can affect productivity and production costs. To get around this problem, Monte Carlo simulation can be applied, or rather a technique that allows to measure the probabilities of values from factors that are under conditions of uncertainties, to which probability distributions are attributed. The objective of this study was to apply the Monte Carlo method for determining the probabilistic techni-cal-economical coefficients of log processing using two different grapple saw models. Field data were obtained from an area of forest planted with Eucalyptus, located in the State of São Paulo, Brazil. For the technical analysis, the time study protocol was applied by the method of continuous reading of the operational cycle elements, which resulted in production. As for the estimated cost of programmed hour, the applied methods were recommended by the Food and Agriculture Organization of the United Nations. The incorporation of the uncertainties was carried out by applying the Monte Carlo simulation method, by which 100,000 random values were generated. The results showed that the crane empty movement is the operational element that most impacts the total time for processing the logs; the variables that most influence the productivity are specific to each grapple saw model; the difference of USD 0.04 m3 in production costs was observed between processors with gripping area of 0.58 m2 and 0.85 m2. The Monte Carlo method proved to be an applicable tool for mechanized wood harvesting for presenting a range of probability of occurrences for the operational elements and for the production cost. |
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Repositório Institucional da UNESP |
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Technical-economic analysis of grapple saw: A stochastic approachEucalyptusForest harvestingMonte CarloProduction costsProductivityThe processing of Eucalyptus logs is a stage that follows the full tree system in mechanized forest harvesting, commonly performed by grapple saw. Therefore, this activity presents some as-sociated uncertainties, especially regarding technical and silvicultural factors that can affect productivity and production costs. To get around this problem, Monte Carlo simulation can be applied, or rather a technique that allows to measure the probabilities of values from factors that are under conditions of uncertainties, to which probability distributions are attributed. The objective of this study was to apply the Monte Carlo method for determining the probabilistic techni-cal-economical coefficients of log processing using two different grapple saw models. Field data were obtained from an area of forest planted with Eucalyptus, located in the State of São Paulo, Brazil. For the technical analysis, the time study protocol was applied by the method of continuous reading of the operational cycle elements, which resulted in production. As for the estimated cost of programmed hour, the applied methods were recommended by the Food and Agriculture Organization of the United Nations. The incorporation of the uncertainties was carried out by applying the Monte Carlo simulation method, by which 100,000 random values were generated. The results showed that the crane empty movement is the operational element that most impacts the total time for processing the logs; the variables that most influence the productivity are specific to each grapple saw model; the difference of USD 0.04 m3 in production costs was observed between processors with gripping area of 0.58 m2 and 0.85 m2. The Monte Carlo method proved to be an applicable tool for mechanized wood harvesting for presenting a range of probability of occurrences for the operational elements and for the production cost.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)São Paulo State University (Unesp)School of Agriculture, Botucatu Avenue Universitária, 3780São Paulo State University (Unesp), Campus of Itapeva Street Geraldo Alckmin, 519, Vila Nossa Sra. de FátimaSão Paulo State University (Unesp)São Paulo State University (Unesp), Campus of Itapeva Street Geraldo Alckmin, 519, Vila Nossa Sra. de FátimaCAPES: 001Universidade Estadual Paulista (Unesp)School of AgricultureMiyajima, Ricardo Hideaki [UNESP]Fenner, Paulo TorresBatistela, Gislaine Cristina [UNESP]Simões, Danilo [UNESP]2020-12-12T02:06:19Z2020-12-12T02:06:19Z2020-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article1-11http://dx.doi.org/10.5552/crojfe.2020.681Croatian Journal of Forest Engineering, v. 41, n. 2, p. 1-11, 2020.1845-5719http://hdl.handle.net/11449/20042710.5552/crojfe.2020.6812-s2.0-85084847591Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengCroatian Journal of Forest Engineeringinfo:eu-repo/semantics/openAccess2021-10-23T12:40:01Zoai:repositorio.unesp.br:11449/200427Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:51:17.249993Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Technical-economic analysis of grapple saw: A stochastic approach |
title |
Technical-economic analysis of grapple saw: A stochastic approach |
spellingShingle |
Technical-economic analysis of grapple saw: A stochastic approach Miyajima, Ricardo Hideaki [UNESP] Eucalyptus Forest harvesting Monte Carlo Production costs Productivity |
title_short |
Technical-economic analysis of grapple saw: A stochastic approach |
title_full |
Technical-economic analysis of grapple saw: A stochastic approach |
title_fullStr |
Technical-economic analysis of grapple saw: A stochastic approach |
title_full_unstemmed |
Technical-economic analysis of grapple saw: A stochastic approach |
title_sort |
Technical-economic analysis of grapple saw: A stochastic approach |
author |
Miyajima, Ricardo Hideaki [UNESP] |
author_facet |
Miyajima, Ricardo Hideaki [UNESP] Fenner, Paulo Torres Batistela, Gislaine Cristina [UNESP] Simões, Danilo [UNESP] |
author_role |
author |
author2 |
Fenner, Paulo Torres Batistela, Gislaine Cristina [UNESP] Simões, Danilo [UNESP] |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) School of Agriculture |
dc.contributor.author.fl_str_mv |
Miyajima, Ricardo Hideaki [UNESP] Fenner, Paulo Torres Batistela, Gislaine Cristina [UNESP] Simões, Danilo [UNESP] |
dc.subject.por.fl_str_mv |
Eucalyptus Forest harvesting Monte Carlo Production costs Productivity |
topic |
Eucalyptus Forest harvesting Monte Carlo Production costs Productivity |
description |
The processing of Eucalyptus logs is a stage that follows the full tree system in mechanized forest harvesting, commonly performed by grapple saw. Therefore, this activity presents some as-sociated uncertainties, especially regarding technical and silvicultural factors that can affect productivity and production costs. To get around this problem, Monte Carlo simulation can be applied, or rather a technique that allows to measure the probabilities of values from factors that are under conditions of uncertainties, to which probability distributions are attributed. The objective of this study was to apply the Monte Carlo method for determining the probabilistic techni-cal-economical coefficients of log processing using two different grapple saw models. Field data were obtained from an area of forest planted with Eucalyptus, located in the State of São Paulo, Brazil. For the technical analysis, the time study protocol was applied by the method of continuous reading of the operational cycle elements, which resulted in production. As for the estimated cost of programmed hour, the applied methods were recommended by the Food and Agriculture Organization of the United Nations. The incorporation of the uncertainties was carried out by applying the Monte Carlo simulation method, by which 100,000 random values were generated. The results showed that the crane empty movement is the operational element that most impacts the total time for processing the logs; the variables that most influence the productivity are specific to each grapple saw model; the difference of USD 0.04 m3 in production costs was observed between processors with gripping area of 0.58 m2 and 0.85 m2. The Monte Carlo method proved to be an applicable tool for mechanized wood harvesting for presenting a range of probability of occurrences for the operational elements and for the production cost. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-12-12T02:06:19Z 2020-12-12T02:06:19Z 2020-01-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.5552/crojfe.2020.681 Croatian Journal of Forest Engineering, v. 41, n. 2, p. 1-11, 2020. 1845-5719 http://hdl.handle.net/11449/200427 10.5552/crojfe.2020.681 2-s2.0-85084847591 |
url |
http://dx.doi.org/10.5552/crojfe.2020.681 http://hdl.handle.net/11449/200427 |
identifier_str_mv |
Croatian Journal of Forest Engineering, v. 41, n. 2, p. 1-11, 2020. 1845-5719 10.5552/crojfe.2020.681 2-s2.0-85084847591 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Croatian Journal of Forest Engineering |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
1-11 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129258154885120 |