Abstract
Manual material handling (MMH) is one of the most physically demanding operations where workers are exposed to repetitive movements, awkward postures, contact stresses, and forceful exertions. MMH results in biomechanical and physiological strain on material handlers. Numerous observational and direct methods are used for assessing MMH tasks. In industrial settings, observational methods are best suited for ergonomic assessments of MMH tasks. But issues such as unclear classification levels, need of expertise, obstructive and invasive nature of data collection procedures, and time and cost requirements create difficulty for safety and ergonomic engineers in using observational methods. The objective of the study is to propose a decision aid to help safety and ergonomic engineers in making an easy ergonomic assessment of MMH tasks for the case study plant in West Bengal. In the current study, WEKA is used to classify the MMH tasks using J48 algorithm. The input data for this study is obtained from our previous work on the development of Cube model-2 (Rajesh et al. in IIE Trans Occup Ergon Human Factors, 2(1):39–51, 2014), in which a field survey of MMH tasks is conducted and classified the MMH tasks into three categories. The output MMH task classifications in WEKA are also classified into three levels. Overall true-positive rate of 0.813, false-positive rate of 0.170, and ROC value of 0.851 are obtained. The weighted Kappa statistic is 0.715. The results from WEKA are encouraging and enable us to use the simple decision tree to judge the physical demands of material handlers. The practical relevance of the study is that the decision tree is helpful for industry practitioners in assessing the MMH tasks therein.
Published Version
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