TY - JOUR
T1 - Material Consumption Smoothing for Mixed-model Assembly Lines Using an Improved Target Tracking Method
AU - Zhang, Yongyang
AU - Mai, Hanhua
AU - Luo, Junhao
AU - Qiao, Huarui
AU - Liu, Pai
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85169416383&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/2562/1/012047
DO - 10.1088/1742-6596/2562/1/012047
M3 - Conference article
AN - SCOPUS:85169416383
SN - 1742-6588
VL - 2562
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012047
T2 - 2023 3rd International Conference on Artificial Intelligence and Industrial Technology Applications, AIITA 2023
Y2 - 24 March 2023 through 26 March 2023
ER -