Modeling manual material lifting risk evaluation: A fuzzy logic approach

Abstract

Manual lifting is common in some occupational groups with substantial rates of injuries. Risk and safety management are therefore become important issues in such workplaces. This study proposed a Fuzzy Logic Expert System (FLES) for manual material lifting risk evaluation. The objective is to develop a fuzzy rule based Expert System which traditional methods are unable to offer effectively. The FLES, implemented in MATLAB (version 7.8), used load (kg), posture (degree), and frequency of lift (lift/min) as inputs variables and risk as the output variable. The algorithm of the inference engine applied sets of rules to generate the output. The validation process between Human Experts’ Calculation (HEC) and FLES risk values indicated a correlation coefficient of 0.91. The result shows a linear relationship between HEC and FLES risk values. Hence the FLES is capable of generating results of the same quality as the ones provided by human experts. It allows inference to be performed in a more natural way using linguistic variables. It is very simple and computationally inexpensive.