Maximum acceptable lifting frequency model in manual material handling task at automotive industries in Malaysia / Mirta Widia

• Main Author: Mirta , Widia
• Format: Thesis
• Published: 2017
• Subjects: TJ Mechanical engineering and machinery; TS Manufactures
• Online Access: http://studentsrepo.um.edu.my/7902/1/All.pdf; http://studentsrepo.um.edu.my/7902/9/mirta.pdf; http://studentsrepo.um.edu.my/7902/
• Institution: Universiti Malaya

Manual material handling (MMH) tasks have been recognised as the major source of work-related musculoskeletal disorders (WMSDs), which is one of the big concerns in automotive industry. In these tasks, the worker acts as a material transfer device in the process of loading and unloading products from pallets to machines in a highly repetitive environment. Frequency is one of the important factors which influences an operator’s capability to perform the MMH tasks. Currently, there is a scarcity of studies in which the lifting frequency is used as a quantifying variable. Moreover, no studies have yet to develop a model to predict the maximum acceptable lifting frequency (MALF) in Malaysia. The main objective of this study is to develop a model for predicting the MALF for MMH tasks in Malaysian automotive industries. The methodology adopted in this study comprised of two phases; industrial survey and experimental tasks for phase one and phase two, respectively. A total of 211 workers participated in the industrial survey (automotive industry) while, 15 workers and 15 novices participated in the experimental tasks. The results of the industrial survey revealed that 82.46% of the workers experienced WMSDs on various regions of their body. The significant factors that were associated with the WMSDs were job tenure (p<0.05), bending the trunk slightly forward with hands above knee level (p<0.05) and twisting the trunk (over 45°) while bending sideways (p<0.05). The experimental tasks revealed that the MALF decreases as the weight of the load increased from 1 to 5 kg (novice: 24.8%, worker: 24.42%). Meanwhile, the increased in loads significantly increases the energy expenditure, muscle activity and rating perceived exertion (RPE). The maximum energy expenditure is attained when the novices and workers performed their tasks at 5 kg weight of load (4.45 and 4.00 kcal/min, respectively). In addition, the right biceps brachii and right trapezius p. descendenz muscles were found to be the muscles with highest activities, for all tasks. These results were supported by the higher rate of RPE obtained for the upper arms and shoulders. Another important finding was found on the subject’s significant differences for both loads in the energy expenditure, RPE and the muscle activities. For MALF, it was found that there is no significant difference between the subjects for both loads. A regression model was developed specifically to predict the novice’s MALF based on the strong correlation and linear relationship between load, energy expenditure, muscle activities and MALF (R=0.971). For workers, the MALF model was developed based on the strong correlation and linear relationship between load, RPE, muscle activities and MALF (R=0.962). Major contribution from this study are the development of two regression models, which separately predicts the MALF for the novices and workers. The models would be beneficial to the automotive industry, as a guideline in designing the MMH tasks. A safe lifting frequency which considered the worker’s limitations and capabilities should be determined, to prevent them from WMSDs and increase their work productivity.