Modified artificial bee colony algorithm for scheduling optimization for printed circuit board production

Abstract

The production scheduling of placement machines strongly influences the efficiency of printed circuit board (PCB) production. This study focuses on the scheduling optimization for PCB production, that is, on maximizing throughput and minimizing total assembly time and head moving distance. Three problems—the automatic nozzle changer (ANC) assignment problem, the nozzle assignment problem, and the component pick-and-place sequence problem—are investigated using a modified artificial bee colony algorithm (MABCA) to enhance the production efficiency of placement machines.The proposed scheduling optimization algorithm comprises three phases. First, the proportional distribution method is applied to optimize ANC assignment. Second, considering the component height as well as the pick, simultaneous pickup, and component shape restrictions, the MABCA generates the nozzle assignment. Third, under the constraints of place restriction and the predetermined nozzle assignment, the MABCA and the 2-opt algorithm generates the place sequence with the minimal PCB assembly time. Finally, the proposed algorithm is experimentally demonstrated. The average number of pickups in the solutions generated by the proposed method, the onsite engineer, and two related studies are 159.3, 167.2, 208.6, and 210.6, respectively. The proposed approach yields the least PCB assembly time. The average total assembly time (Ttotal) improved between on-site engineer and the proposed MABCA is 4.08%.