Controlling mixed-model assembly lines in real-time by using distributed systems
The production of large quantities is frequently handled by the use of assembly lines. These systems yield significant reductions of variable costs for the production of homogenous products. But due to increasing competition and differentiated demands, today it is no longer sufficient to offer only standardized products. To combine the wishes and requirements of the customers with the advantages of an efficient flow line production, different product variants are produced simultaneously on the same mixed-model assembly line. Therefore, the task of controlling such production processes is becoming more complex since an efficient production execution has to be realized in spite of the occurring oscillating work content of the different variants. Additionally, unforeseen disturbances in the production process can compromise its planned execution. To deal with these problems, this paper proposes a new approach for an adaptive real-time control of assembly lines that extends the pure sequencing problem by the integration of specific line-balancing aspects and the mapping of consequences of possible disturbance scenarios. Such a scenario could be, for instance, the loss of a worker, a material bottleneck or a machine breakdown. To guarantee an efficient continuation of the production process, the controlling instrument reacts instantly to a disturbance by adapting the current plan in a very short time, consisting of only a few cycle times, to reduce the additional costs caused by the disturbances.
assembly line real-time control combinatorial optimization parallel computing metaheuristics