Sistema probabilístico basado en redes bayesianas para predecir el grado de riesgo ergonómico por movimientos repetitivos

Abstract

With the purpose of minimizing the incidence of suffering muscular-skeletal disorders that the personnel of the construction of tires of the company Continental Tire Andina S.A. of the city of Cuenca, a descriptive study was established, which allowed to examine the work procedure in the elaboration of tires, in the same way the analytical and experimental study allowed to obtain variables that guided the simulation which represented the level of ergonomic risk by repetitive movements, being able to evaluate 83 operators of 112, excluding 29 workers due to the deficit of personal information and performance, To carry out the experimentation through the artificial intelligence technique Bayesian Networks 13 variables were contextualized and associated to groups of diverse character, having the problem variable, informative variables and intermediate variables, these were related through a causal approach developing a network structure allowing to predict the ergonomic risk by repetitive movements giving a classification or success rate of 76%, also is presented 0.65 in terms of the indicator Area Below the Curve (ROC), reflecting the performance of the Bayesian Networks, which confirms that it is a useful and useful forecasting tool for dealing with situations of exposure to ergonomic risk due to repetitive movements.