Doctor of Philosophy (PhD)
Mechanical and Industrial Engineering
Manual Material Handling (MMH) is one of the main causes of overexertion. Overexertion leads to work-related musculoskeletal disorders. To prevent overexertion during the MMH tasks, redesigning them must include sufficient rest periods. Task characteristics play a significant role in the redesign of the work. This study aimed to evaluate the effect of multiple task characteristics on recovery time and develop a rest interval model based on the task characteristics. The task characteristics considered for the study were the weight of lift (8 and 12 kg), duration of lift (5 and 10 minutes), frequency of lift (6 and 12 lifts per minute), distance of lift (35 and 70 centimeters), and angle of symmetry (0 and 90 degrees). The impact of five task characteristics combinations was studied on the maximum voluntary contraction recovery rate (MVCRT) of muscles, heart rate recovery time (HRRT), and Borgs scale. The experiment used a two-factorial block design where participants performed only one treatment. Each of the five task characteristics had lower and higher levels. Thirty-two treatments were used in the study. The treatments were allocated randomly to the participants. Regression analysis was used on MVCRT and HRRT to build models for rest intervals between the tasks' characteristics. ANOVA was used to study the impact of task characteristics at α=0.05. Weight (p=0.0024) and duration (p=0.0131) significantly impacted the MVCRT, which increased by 32% with an increase in weight and for the duration by 21%. In addition, the interaction of frequency and distance with a p-value of 0.0351 also significantly impacted MVCRT. Weight (p=0.002) and duration (p=0.0101) also significantly impacted the HRRT. HRRT increased by 33% with an increase in weight and for the duration by 22%. The weight, frequency, and duration interaction effect with a p-value of 0.0208 significantly impacted the HRRT. The frequency with a p-value of 0.0039 and distance with a p-value of 0.0277 are the task characteristics that xv significantly impacted the Borgs scale of perceived exertion with an increase of 63% and 43%, respectively. A simplified mathematical model for the prediction of MVCRT was developed with the five task characteristics. Similarly, another model was built using the task characteristics for HRRT, which had four task characteristics. An ANOVA test was performed between the actual results and the predicted results. There was no significant difference between the actual and predicted times for MVCRT (p=0.8972) and HRRT (p=0.8484). The study's results and mathematical models may be used to design lifting tasks in the workplace to reduce work-related musculoskeletal disorders.
Pusapati, Vamsi Krishna Varma, "Mathematical Modeling of Rest Intervals Using Task Characteristics during Repetitive Lifting" (2023). LSU Doctoral Dissertations. 6125.
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