Establishment of overall workload assessment technique for various tasks and workplaces

Abstract

A model for assessing workloads called overall workload level (OWL) was developed by introducing linguistic variable sets and applying the analytic hierarchy process (AHP) to estimate the external workload imposed on a human operator in man–machine systems. To do this, a five-point linguistic variable set scale was constructed and their hierarchical prioritization procedures were set up. The task and workplace variables (e.g., physical, environmental, postural, and mental job demand workloads) which can obtain the operator's perception of workload are selected as workload factors and the AHP technique is used to collect different weights. Finally, OWL is calculated using a computer-assisted system to determine the level of overall workload impinged on an operator. The OWL was implemented in an actual industrial environment from a physiological and epidemiological viewpoint to determine the validity of the model. Furthermore, the results obtained by applying OWL were compared to the results obtained by applying the overall workload (OW) of the NASA task load index (TLX). The results show that there is a close linear relationship among the physiological measurements, the severity of injury and illness rates, OW, and OWL. Thus, this approach can be used for problem identification and for solving widespread occupational workloads. Relevance to industry The determination of workloads imposed on a human operator plays an important role in designing and evaluating an existing man–machine system. Therefore, a model for assessing workloads was developed to estimate the external workload imposed on a human operator in man–machine systems. This model can be used for problem identification and for solving widespread occupational workload.