Material Consumption Smoothing for Mixed-model Assembly Lines Using an Improved Target Tracking Method

Yongyang Zhang, Hanhua Mai*, Junhao Luo, Huarui Qiao, Pai Liu

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

To improve the material consumption smoothing for mixed-model assembly lines, this paper proposes a new optimized approach based on Euclidean distance and an improved target tracking algorithm. With this new method, the average demands for materials for each product are calculated, and the distances between the actual usage and average demand are computed with the Euclidean distance formula, which is the consumption rate of materials. Then, the material consumption rates of each product are sorted in order, and the minimum value is listed as the optimal scheduling. Therefore, by moving in circles, the optimal scheduling of all products can be achieved. In addition, the production simulation model is established using the FlexSim software to decrease the processing bottleneck. Through running the simulation model, the cycle time is reduced, and the line balance is increased.

Original languageEnglish
Article number012047
JournalJournal of Physics: Conference Series
Volume2562
Issue number1
DOIs
Publication statusPublished - 2023
Event2023 3rd International Conference on Artificial Intelligence and Industrial Technology Applications, AIITA 2023 - Suzhou, China
Duration: 24 Mar 202326 Mar 2023

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