Abstract
Assembly cells often depend on the human elements when an extended automation is not (economically, even if technologically) possible. The workers’ natural variability is impossible to avoid in a manual assembly system. Usually when simulating an assembly system, a given task time distribution is assumed as the representation of the workers time performance. Workers have variations in their performance that can incur in the shifting of this distribution relative to the expected performance time distribution, as well as in the widening of this distribution, by the increase or decrease of dispersion. This paper presents a discrete event simulation model of an assembly system where the operators have different time distributions, aiming to assess their influence in the overall system performance. Those time distributions were obtained in industrial context, in a previous study, by observing workers in an assembly cell, so representing real performance of workers. The results indicate that the worst performing worker will “pace” the output system performance to a slower rhythm, while better performances of a single worker will only increase very slightly the system productivity.
Highlights
Dealing with variability is a normal task when managing a manufacturing or assembly system (Tan, 1998)
In order to assess the impact of the different types of workers performance on the system, the system was simulated for 480 min (8h hour shift)
4.1 Scenarios A – 7 Workers, all with Same Time Performance The analysis of the average frequency per assembly system CT value shows how the system cycle times are distributed for the different time performance scenarios (Figure 4)
Summary
Dealing with variability is a normal task when managing a manufacturing or assembly system (Tan, 1998). Data from an industrial setting is used as an example of the different time performances that can be found when performing manual high motor content assembly tasks These several performances (slower/faster; higher/lower variability) are tested in different scenarios of. According to the referred study, 46 time performances of fully trained workers on an industrial setting, performing assembly tasks, were registered Their performances were compared with the overall average performance, by calculating the deviations to it. It was considered that for a given type of assembly tasks of high motor content the expected average task time and standard deviation is 15 seconds and 1.95 seconds, respectively. The variance is calculated, by calculating the average of the variances obtained for each run and applying the square root to this value, to obtain the cycle time standard deviation
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