Reduction of Printed Circuit Card Placement Time Through the Implementation of Panelization


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Virginia Tech


Decreasing the cycle time of panels in the printed circuit card manufacturing process has been a significant research topic over the past decade. The research objective in such literature has been to reduce the placement machine cycle times by finding the optimal placement sequences and component-feeder allocation for a given, fixed, panel component layout for a given machine type. Until now, no research has been found which allows the alteration of the panel configuration itself, when panelization is a part of that electronic panel design. This research will be the first effort to incorporate panelization into the cycle time reduction field. The PCB circuit design is not to be altered; rather, the panel design (i.e., the arrangement of the PCB in the panel) is altered to reduce the panel assembly time. Component placement problem models are developed for three types of machines: The automated insertion machine (AIM), the pick-and-place (PAPM) machine, and the rotary turret head machine (RTHM). Two solution procedures are developed which are based upon a genetic algorithm (GA) approach. One procedure simultaneously produces solutions for the best panel design and component placement sequence. The other procedure first selects a best panel design based upon an estimation of its worth to the minimization problem. Then that procedure uses a more traditional GA to solve for the component placement and component type allocation problem for that panel design. Experiments were conducted to discover situations where the consideration of panelization can make a significant difierence in panel assembly times. It was shown that the PAPM scenario benefits most from panelization and the RTHM the least, though all three machine types show improvements under certain conditions established in the experiments.

NOTE: An updated copy of this ETD was added on 09/17/2010.



design for manufacturing, electronic assembly, genetic algorithm, component placement