Computation of safety design indexes of industry vehicle operators based on the reach angle,the distance from elbow to ground and the popliteal height |
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| Affiliation: | 1. Intelligent Manufacturing Key Laboratory of Ministry of Education, Shantou University, Shantou, China;2. Department of Engineering Design, MIT Academy of Engineering (MAE), Pune, MH, 412105, India;3. Department of Mechanical Engineering, MIT Academy of Engineering (MAE), Pune, MH, 412105, India;4. Department of Design, Indian Institute of Technology (IIT), Guwahati, India;5. Shantou Ruixiang Mould Co. Ltd., Jinping S&T Park, Chaoshan Road, Shantou, 515064, China;1. Industrial Engineering, College of Engineering, University of Miami, 1251 Memorial Drive, McArthur Engineering Building, Coral Gables, FL, 33146, USA;2. St. Jude Children''s Research Hospital, 262 Danny Thomas Pl, Memphis, TN, 38105, USA;3. University of Miami, Department of Kinesiology and Sport Sciences, 1507 Levante Ave, Max Orovitz Building, Coral Gables, FL, 33146, USA;1. Mechanical Engineering Department, École de technologie supérieure, Montreal, Canada;2. Industrial Engineering Department, K.N. Toosi University of Technology, Tehran, Iran;3. School of Public Health, Tehran University of Medical Sciences, Tehran, Iran;4. Institute of Ergonomics and Human Factors, Technische Universität, Darmstadt, Germany;1. State Key Laboratory of Automotive Safety and Energy, Department of Automotive Engineering, Tsinghua University, Beijing, 100084, China;2. Center for Advanced Orthopedic Studies, Beth Israel Deaconess Medical Center, Boston, MA, 02215, USA;1. Ocean Safety Research, Marine Institute of Memorial University, St. John''s, Newfoundland and Labrador, Canada;2. School of Human Kinetics and Recreation, Memorial University, St. John''s, Newfoundland and Labrador, Canada |
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| Abstract: | For safety design of industrial vehicles, it is important to understand the optimum posture parameters such as the elbow-ground distance, the popliteal height and the reach angle. RULA and REBA, which are most commonly adopted to evaluate the risk associated with posture exhibit higher dependence on the mentioned parameters. The relative significance of these parameters is not known for drivers in industrial vehicle. The main objective of this study is to develop a model using an automated neural network search (ANS) approach for the prediction of RULA and REBA based on the coupled interactions of posture parameters. In the context of model development, field study that contains measurement of these posture parameters was utilized. RULA and REBA were assessed from these posture parameters using CATIA software. Further, the study also reveals the relative significance of these posture parameters and identifies the most optimum parameters for minimum risk to driver's health. |
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| Keywords: | Neural networks RULA REBA Industrial vehicles Posture parameters Neural networks |
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