MÉTODO INTEGRADO PARA AVALIAÇÃO ERGONÔMICA DE MÁQUINAS NA COLHEITA DE MADEIRA

Abstract

The advancement of mechanization in wood harvesting operations has raised concerns such as the increase in vibration and noise levels, inadequate postures, repetitive movements, visibility difficulties, being necessary the search for new models of integrated ergonomic evaluation, contributing to the improvement of work conditions. The objective of this research was to propose a new method for the ergonomic evaluation of mechanized wood harvesting operations, capable of correlating the ergonomic variables in an integrated way, seeking solutions to improve the ergonomic performance and the safety and health conditions of the workers. The research was conducted in the operational areas of a forestry company in the state of Paraná, Brazil, evaluating the machines: feller buncher, skidder, forest processor, harvester and forwarder. The productivity of the machines was determined by a time and motion study and it was evaluated the levels of exposure of the operators to the occupational whole-body vibration, to the noise, the heat and the illuminance. The postures and the repeatability of the operator movements and the angles of visibility were also evaluated. The ergonomic instruments were installed inside the machines' workstations simultaneously to obtain the ergonomic data. The standardization of the results of the ergonomic evaluations was performed by adapting the Degree of Compliance (V) of the variables in relation to the norms in the legislation and it was proposed an ergonomic urgency classification in a color scale. The data were also submitted to a multivariate clusters analysis to identify groups of similar machines in relation to the ergonomic variables, as well as a multivariate factor analysis to determine the variables of influence in the composition of the Integrated Ergonomic Indicator (IEI). The results showed that none of the machines studied presented a 100% compliance in relation to the studied ergonomic variables. The skidder was classified as the machine with the greatest ergonomic problems, requiring the adoption of emergency corrective measures regarding vibrations, noise and visibility in the lateral plane. The machines with the best ergonomic performances were the forest processor and the wheeled harvester, caused by the low levels of vibration and noise, conditions to provide adequate posture and good visibility. The classification of the results according to the need for ergonomic intervention through the color scale allowed a better interpretation of the ergonomic indicators, helping the identification of the priority variables for a corrective ergonomic intervention. The multivariate analysis allowed to identify three groups of machines in relation to the ergonomic variables, being the groups that included skidder and forwarder, those that presented the worst values. The productivity was satisfactorily used as an aid to the explanation of the data in the ergonomic evaluation and in the determination of IEI. The proposed method proved to be effective in the integrated ergonomic evaluation.