Multiple setup PCB assembly planning using genetic algorithms

Authors:
Shantanu Deo;Roya Javadpour;Gerald M. Knapp
Affiliations:
US R&D Center, Juki Corporation, Morrisville, NC;12 Corporation, Irving, TX;Industrial and Manufacturing Systems Engineering, Louisiana State University, 3128 CEBA, Baton Rouge, LA
Venue:
Computers and Industrial Engineering
Year:
2002

Citing 3
Cited 4

Component allocation and partitioning for a dual delivery placement machine

Operations Research
Sequencing of insertions in printed circuit board assembly

Operations Research
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning

Enhancing optimal feeder assignment of the multi-head surface mounting machine using genetic algorithms

Applied Soft Computing
A memetic algorithm-based heuristic for a scheduling problem in printed circuit board assembly

Computers and Industrial Engineering
Operations planning for collect-and-place machines in PCB assembly

Computers and Industrial Engineering
Optimization of electronics component placement design on PCB using self organizing genetic algorithm (SOGA)

Journal of Intelligent Manufacturing

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Abstract

A Genetic Algorithm (GA) program is developed for simultaneously optimizing component placement sequence and feeder assignments in the assembly of Printed Circuit Boards (PCBs). The program extends the application of GA to this problem by providing handling of two practical but complicating factors: (1) feeder constraints forcing multiple setups, and (2) new generation assembly machines which can place from both sequenced tape and component feeders within the same setup. This paper details the algorithm developed, demonstrates the approach on several examples, and investigates the performance of the GA and the impact of its various parameters.