Modifying Mixed-Model Assembly Line Sequencing Methods to Consider Weighted Variations for Just-In-Time Production Systems

Abstract

Mixed-model assembly lines are widely used in just-in-time (JIT) production systems. One of the commonly used goals in sequencing mixed-model assembly lines in JIT production systems is to maintain nearly constant rates of part usage on the line. In this paper the sequencing problem is generalized to consider weights for different models in evaluating their influence on the part usage rate. The existing methods for sequencing mixed-model assembly lines are modified for the generalized problem. Computational comparisons are made between the modified heuristic methods and an optimal procedure for the squared variation objective. The computational results show that the modified heuristic methods obtain nearly optimal solutions and require moderate CPU times.

Additional information

Notes on contributors

Liping Cheng

Liping Cheng is a graduate student of Industrial Engineering and Management as well as Computer Science and Operations Research at North Dakota State University. He holds a B.S. degree in electrical engineering from the Southeast University in the People’s Republic of China. His primary areas of interest include production and inventory control and operations research.

Fong-Yuen Ding

Fong-Yuen Ding is an Associate Professor of Industrial Engineering and Management at North Dakota State University. He received his Ph.D. in Industrial Engineering from North Carolina State University. He is a member of IIE, INFORMS and APICS. His primary areas of interest include production scheduling, just-in-time manufacturing, flexible manufacturing systems, and cellular manufacturing.