Abstract
This article is based on the planning of human movements in different joints to reduce energy and fatigue of the working subjects. For this a simulation model is generated which complies with the constraints of the process. It requires verifying the capability of human postures and movements in different working conditions for the evaluation of effectiveness of the new workplace design. Here, a simple human performance measure is introduced which enables the mathematical model for evaluation of a cost function, i.e., discomfort function and energy expenditure rate. The basic study is to evaluate human performance in the form of cost functions. It aims to optimize the movement of the limbs with the above-mentioned cost factors. The method is tested with a case study of a fly ash brick manufacturing unit using two subjects for stacking bricks in stacking pan. MOO method is used for posture prediction. For an optimized posture prediction cost functions are minimized with less joint discomfort and less energy expenditure.
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Rout, B., Tripathy, P.P., Dash, R.R., Dhupal, D. (2020). Optimization of Posture Prediction Using MOO in Brick Stacking Operation. In: Behera, H., Nayak, J., Naik, B., Pelusi, D. (eds) Computational Intelligence in Data Mining. Advances in Intelligent Systems and Computing, vol 990. Springer, Singapore. https://doi.org/10.1007/978-981-13-8676-3_40
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DOI: https://doi.org/10.1007/978-981-13-8676-3_40
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