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Master's Dissertation
DOI
10.11606/D.11.2016.tde-30092016-101059
Document
Author
Full name
Eduardo Shigueiti Maekawa
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
Piracicaba, 2016
Supervisor
Committee
Milan, Marcos (President)
Molin, Jose Paulo
Rodrigues, Luiz Henrique Antunes
Title in Portuguese
Estimativa do custo da colheita mecanizada de cana-de-açúcar utilizando modelos de regressão
Keywords in Portuguese
Colhedora de cana
Custo operacional
Modelos lineares generalizados
Modelos lineares generalizados mistos
Abstract in Portuguese
A colheita mecanizada é uma das mais significativas e onerosas operações do processo de produção de cana-de-açúcar, tornando-se importante o entendimento das relações que envolvem o seu custo. Atualmente, as metodologias para estimar o custo da colheita partem do conceito de custo fixo e variável. No entanto, considerando a complexidade desse processo, faz-se necessário avaliar métodos capazes de relacionar os parâmetros operacionais com o custo final. Neste contexto, a modelagem estatística por meio da regressão permite tratar tais relações e prever tendências. O objetivo deste trabalho foi desenvolver um modelo empírico para o cálculo do custo da colheita mecanizada de cana-de-açúcar. Desenvolveu-se um modelo linear generalizado (MLG) e um modelo linear generalizado misto (MLGM) ambos com distribuição gama, utilizando indicadores operacionais e dados de custo de 20 usinas do setor sucroalcooleiro. Por meio do MLGM, obteve-se uma aderência satisfatória quando comparado aos modelos MLG, nulo (média) e linear (supondo normalidade). Os indicadores que explicaram o custo foram: produtividade (t maq-1), consumo (l t-1), horímetro (h) e número de operadores por colhedora (nop).
Title in English
Estimated cost of mechanized harvesting of sugarcane using regression models
Keywords in English
Generalized linear mixed models
Generalized linear models
Operational cost
Sugarcane harvester
Abstract in English
The mechanized harvesting of sugarcane is one of the most significant and costly operations of the production process, thus it is important to understand the relationships involving its cost. Currently, methods to estimate these costs rise from the concept of fixed and variable cost. However, considering the complexity of the harvesting process, it is necessary to evaluate techniques to relate the operating parameters with the final cost. In this context, statistical modeling by regression allows to treat such relationship and predict trends. The objective of this study was to develop an empirical model to calculate the cost of mechanical harvesting of sugarcane. A generalized linear model (GLM) and a generalized linear mixed model (GLMM) both with gamma distribution was developed using operational indicators and cost data from 20 plants in the sugarcane industry. Through the GLMM, satisfactory adhesion was obtained when compared to the GLM, null model (average) and linear (assuming normality). The indicators that explained the cost were: productivity (t mach-1), consumption (l t-1), hourmeter (h) and number of operators per harvester (nop).
 
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Publishing Date
2016-10-13
 
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