Yaar Harari, Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel
Raziel Riemer, Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel
To plan a new manual material handling work process, it is necessary to predict the times required to complete each task. Current time prediction models lack validity when the handled object's mass exceeds 2 kg. In this study, we investigated the effect of workplace design parameters on continuous sequential lifting, carrying, and lowering of boxes weighing from 2 kg to 14 kg. Both laboratory and field experiments were conducted. Results revealed that the box's weight and the lifting and lowering heights influenced the tasks' times. Further, the time to perform a task was influenced by the performance of other tasks in the same work process. New time prediction models were developed using the laboratory experiment data. Our models were found to be more accurate on average than the Maynard Operation Sequence Technique (MOST) and Methods Time Measurement (MTM-1) by 42% and 20%, respectively, for predicting the times of real workers at an actual workplace.
Yaar Harari, Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel
Raziel Riemer, Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel
To plan a new manual material handling work process, it is necessary to predict the times required to complete each task. Current time prediction models lack validity when the handled object's mass exceeds 2 kg. In this study, we investigated the effect of workplace design parameters on continuous sequential lifting, carrying, and lowering of boxes weighing from 2 kg to 14 kg. Both laboratory and field experiments were conducted. Results revealed that the box's weight and the lifting and lowering heights influenced the tasks' times. Further, the time to perform a task was influenced by the performance of other tasks in the same work process. New time prediction models were developed using the laboratory experiment data. Our models were found to be more accurate on average than the Maynard Operation Sequence Technique (MOST) and Methods Time Measurement (MTM-1) by 42% and 20%, respectively, for predicting the times of real workers at an actual workplace.