Objetivo: Analizar los efectos de las variables altura vertical y la frecuencia de levantamiento sobre la frecuencia cardiaca en trabajadores en la tarea de levantamiento de cargas.
Método: Diseño experimental factorial con bloques, considerando como variables independientes la altura vertical y la frecuencia de levantamiento y la dependiente la frecuencia cardiaca. El experimento se desarrolló con 20 trabajadores entre 18 y 40 años con al menos seis meses de experiencia en tareas de almacén y empaque en una empresa de productos lácteos. Se calculó el coeficiente FRIMAT para determinar la carga fisiológica de la tarea.
Resultados: Existe un efecto significativo sobre la respuesta de la frecuencia cardiaca debido a la interacción de la frecuencia y la altura vertical del levantamiento. Además, basados en el coeficiente FRIMAT, se obtuvo una calificación de “carga de trabajo mínima” para el 85% de los tratamientos, y en un tratamiento, se presentó una calificación de “algo difícil”.
Conclusiones: La altura y frecuencia de levantamiento no actúan de manera independiente y tienen un efecto sobre la carga fisiológica del trabajador en el levantamiento manual de cargas manifestada en la frecuencia cardiaca.
In traditional scheduling problems, job processing times are considered constant and known in advance. This assumption is, however, a simplification when it comes to hand-intensive real-life production contexts because workers usually induce variability in the job processing times due to several factors such as learning, monotony, fatigue, psychological factors, etc. These effects can decrease or increase the actual processing time when workers execute a job. The academic literature has reported several modeling and resolution approaches to deal with the phenomenon in a variety of configurations. However, there is no comprehensive review of these research outputs to the best of our knowledge. In this paper, we follow a systematic approach to review relevant contributions addressing the scheduling problem with learning and deterioration effects. Modeling approaches for learning and deterioration effects, objective functions, and solution methods employed in the literature are the main topics for the taxonomy proposed in this review. A total of 455 papers from 1999 to 2021 are included and analyzed. Different areas of interest are presented, and some opportunities for future research are identified.
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