Capacities characterization of wood harvest machine operators’ by cognitive and motor processes

Abstract

ABSTRACT The work of the wood harvest machine operator is an important variable for the performance of a forestry company, impacting the operation quality, productivity, and profit. However, the lack of skilled operators with the desirable profile for machine operation is a current challenge. This research proposes a method to evaluate the operational skills required of forest machine operators to increase the quality of the selection and training processes and to improve their subsequent performance . Focusing on a forestry company in Brazil, we developed assessments for cognition, behavior, memory, focused attention, and motor skills to measure the worker’s efficiency with each mechanism used for operation of the harvest machine. The outcomes data were analyzed by principal component analysis and factor analysis to understand how every variable was responsible for the operators’ scores, attributing values to operator’s classification by cluster analysis. Results showed that all capacities evaluated were relevant, with variations among operators, with these key factors for feller bunchers versus skidder operators: cognition (26.5%, vs. 31%), behavior (38% vs. 37%), memory (18% vs. 13%), focused attention (5% vs. 6%), and motor skills (9% vs. 11%). Based on these data, the operators were classified into three distinct profiles. Conclusions were that the proposed assessment of individual characteristics was able to identify variations in the operators’ profiles.