Clusters and filling-curve-based storage assignment in a circuit board assembly kitting area

Abstract

Kitting is the process that gathers all of the components necessary to assemble a batch of circuit boards on production machines. An objective in kitting storage design is to minimize the travel involved in collecting the components in the storage area so as to decrease labor costs. From outward appearances, the kitting process is similar to order picking in a warehouse. Closer observation, however, reveals that its unique characteristics favor a cluster-based allocation over the storage strategies usually adopted in warehouses. We present a clustering and cluster assignment method. In the clustering method we develop a new objective function and incorporate it into a genetic algorithm. In the cluster assignment method we first develop a new index for cluster assignment priorities. We then prove optimum assignments of clusters under restrictive conditions and extend the result to realistic storage configurations using filling curves. We analyze the properties affecting the quality of filling curves and develop a class of filling curves with good performance characteristics. Finally, we perform numerical analyses to show that the cluster and filling-curve-based assignment in the kitting area can reduce travel distances.