A comparative evaluation of heuristic line balancing techniques
Management Science
A survey of exact algorithms for the simple assembly line balancing problem
Management Science
Neural networks: algorithms, applications, and programming techniques
Neural networks: algorithms, applications, and programming techniques
Artificial immune systems for assembly sequence planning exploration
Engineering Applications of Artificial Intelligence
Nested partitions method for assembly sequences merging
Expert Systems with Applications: An International Journal
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An assembly sequence is considered to be optimal when the sequence satisfies assembly constraints and yields the minimum assembly cost. While, a line balancing solution is considered to be optimal when the solution has the minimum idle time of the line, i.e. the minimum number of workstations for a given cycle time. Although optimal assembly sequences are generated without considering line balancing, they may not guarantee the minimum number of workstations. In such case, additional cost should be required to accommodate the increased number of workstations. Therefore, it is essential to consider line balancing in the generation of cost-effective assembly sequences. To generate such line-balanced assembly sequences for robotic assembly, this paper treats a single-model and deterministic (SMD) assembly line balancing (ALB) problem, and proposes a new method using a simulated annealing. In this method, an energy function is derived in consideration of the satisfaction of assembly constraints, and the minimization of assembly cost and the idle time. Then, the energy function is iteratively minimized and occasionally perturbed by a simulated annealing. When no further change in energy occurs, a solution of assembly sequence with consideration of line balancing is finally obtained. To show the effectiveness of the proposed scheme, case studies are presented for industrial products such as an electrical relay and an automobile alternator.