Modelagem fuzzy e geoestatística na avaliação da salubridade de trabalhadores

Abstract

The main objective of this research was to evaluate the well-being of agricultural machine operators with respect to thermal and acoustic environments considering the work arrangements and the activity type. For that, data of air temperature, black globe temperature, relative humidity and noise level were measured for four different agricultural machinery. Seeking a mathematical tool to classify the work environment, a mathematical model based on fuzzy sets theory was developed, where comfort is classified based on the interaction among thermal, acoustic, activity type and rest periods parameters to which the worker is being submitted. Experimental data were used to test the system, running simulations to predict the well-being index and the ideal rest time for each equipment evaluated. Then, the characterization of spatial variability of the noise was performed through geostatistics, allowing set the points with different noise levels from the sample area. The proposed model can be used to determine the level of well-being for agricultural machine operators, assisting in decisions making regarding the arrangements of work and use of safety equipment, and the use of geostatistics allowed to verify the spatial distribution of noise levels for each equipment and its influence on the workers welfare.