Abstract

Vibration transmission in the hand of operators while working with handheld power tools is one of the important concerns with respect to the safety of operators. The handheld power tools are widely used in manufacturing industry, construction industry, service centres, road construction, etc. The operation on powered handheld tools such as grinders, drills, etc., exposes workers to hand arm vibration. Hand arm vibration (HAV) is the vibration transmitted to the parts of hand arm during the operation of handheld power tools. Vibrations transmitted can originate several types of illness with associated symptoms of blood supply, nerves, muscles of hand arm system and lead neurological, vascular and oesteoarticular disorders. Vibration-induced white finger is one of the vibration-induced disorders in fingers and hand because of blanching along with tingling and numbness in fingers and hand. Workers who are repeatedly exposed to intense hand-transmitted vibration are at risk of developing health problems. The research is focused to analyse effects of hand arm vibration on human energy consumption during drilling operation by female operators. For experimentation, seven different postures and two age group of operator between 18 and 40 years were identified. A mathematical model is developed for human energy consumption by female operator considering the different parameters, viz. age, weight, posture angle of operator during working, hardness of commonly used different materials and push force applied by the operator. Dimensional analysis is used for developing the mathematical model. Actual human energy consumption is calculated considering the pulse rate, age and weight of operator, etc. Artificial neural network (ANN) is developed for human energy consumption using MATLAB software. Then actual human energy consumption is validated with mathematical model and ANN prediction model. Sensitivity analysis is used to identify the most dominant parameter in mathematical model for human energy consumption by operators. Age of the operator is observed to be a most dominant factor in human energy consumption. Mathematical modelling, ANN and experimental results are well agreed with R2 value 0.99 and absolute error of 1.1898.

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