TY - GEN
T1 - On the optimization of cycle time in assembly lines with parallel workstations and tasks requiring multiple workers
AU - Shin, Jinho
AU - Lee, Minho
AU - Morrison, James R.
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - The assembly line worker assignment and balancing problem (ALWABP) is classified into two types according to the objective of the problem. One seeks to find the minimum resource consumption plan (number of required workstations) with the satisfaction of the targeted cycle time, ALWABP-1. The other involves an allocation of limited workers to production tasks to minimize the cycle time, ALWABP-2. In this research, we extend ALWABP-2 to allow for parallel workstations and tasks requiring multiple workers (PALMWABP). We develop a mixed linear integer program (MILP) that can be solved in small cases with state-of-the-art MILP solvers. For practical use, we provide an intuitive heuristic method to obtain fast solutions of good quality. Comparison of the effectiveness of both approaches is provided for our case dataset. For example, for dataset 2, our heuristic takes about a second to obtain a solution, compared to 42 mins for PALMWABP with only 2.3% difference in objective value; our heuristic can also obtain solutions for larger problems that cannot be solved exactly.
AB - The assembly line worker assignment and balancing problem (ALWABP) is classified into two types according to the objective of the problem. One seeks to find the minimum resource consumption plan (number of required workstations) with the satisfaction of the targeted cycle time, ALWABP-1. The other involves an allocation of limited workers to production tasks to minimize the cycle time, ALWABP-2. In this research, we extend ALWABP-2 to allow for parallel workstations and tasks requiring multiple workers (PALMWABP). We develop a mixed linear integer program (MILP) that can be solved in small cases with state-of-the-art MILP solvers. For practical use, we provide an intuitive heuristic method to obtain fast solutions of good quality. Comparison of the effectiveness of both approaches is provided for our case dataset. For example, for dataset 2, our heuristic takes about a second to obtain a solution, compared to 42 mins for PALMWABP with only 2.3% difference in objective value; our heuristic can also obtain solutions for larger problems that cannot be solved exactly.
UR - http://www.scopus.com/inward/record.url?scp=85072953484&partnerID=8YFLogxK
U2 - 10.1109/COASE.2019.8842915
DO - 10.1109/COASE.2019.8842915
M3 - Conference contribution
AN - SCOPUS:85072953484
T3 - IEEE International Conference on Automation Science and Engineering
SP - 916
EP - 921
BT - 2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019
PB - IEEE Computer Society
T2 - 15th IEEE International Conference on Automation Science and Engineering, CASE 2019
Y2 - 22 August 2019 through 26 August 2019
ER -