Component allocation and feeder arrangement for a dual-gantry multi-head surface mounting placement tool

We consider operational optimization problems for a multi-head surface mounting placement tool with dual-gantry robots. We discuss operational decisions and their interrelationships. We focus on the component allocation and feeder arrangement decisions, which are most essential for cycle time optimization. We propose a way of decomposing and structuring the operational decision problems. We propose a genetic algorithm of optimizing the two decisions simultaneously. The two decisions are optimized by maximizing the number of simultaneously picked up components for each access of a multi-head module, or equivalently minimizing the number of pickups, and balancing the workload between the two gantries. We propose a gene encoding method that incorporates interference between the feeders of different widths. In order to evaluate the workload at each gantry for the fitness function, we propose a greedy heuristic for the work cycle formation and pickup sequencing decisions. Computational performance is examined using real industrial data.