In this paper, a genetic algorithm for the robotic assembly line balancing problem (RALBP) is developed that supports multimodal stochastic processing times and multiple parallel-working robots per workstation. It has the objective to minimize the amount of workstations at a given production rate and probability limit for violating the cycle time (PL). The algorithm is evaluated on the BARTHOLD data set in a range of 1 % to 50 % for PL using an experimentally determined and a normal distribution for the task times. The increase of PL results in a shift of tasks from rear to front stations, because more tasks can be assigned to each station. The shift using normal distributed task times is stronger. This demonstrates the importance of realistic stochastic distribution assumptions. For practical applicability, more constraint types have to be included in the future.
Robotic Assembly Line Balancing with Multimodal Stochastic Processing Times
ARENA2036
Stuttgart Conference on Automotive Production ; 2022 ; Stuttgart, Germany November 16, 2022 - November 18, 2022
Advances in Automotive Production Technology – Towards Software-Defined Manufacturing and Resilient Supply Chains ; Chapter : 8 ; 78-84
2023-06-05
7 pages
Article/Chapter (Book)
Electronic Resource
English
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