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Component placement sequence optimization in printed circuit board assembly using genetic algorithms

Over the last two decades, the assembly of printed circuit boards (PCB) has generated
a huge amount of industrial activity. One of the major developments in PCB assembly
was introduction of surface mount technology (SMT). SMT has displaced through-hole
technology as a primary means of assembling PCB over the last decade. It has
also made it easy to automate PCB assembly process.
The component placement machine is probably the most important piece of
manufacturing equipment on a surface mount assembly line. It is used for placing
components reliably and accurately enough to meet the throughput requirements in a
cost-effective manner. Apart from the fact that it is the most expensive equipment on
the PCB manufacturing line, it is also often the bottleneck. There are a quite a few
areas for improvements on the machine, one of them being component placement
sequencing. With the number of components being placed on a PCB ranging in
hundreds, a placement sequence which requires near minimum motion of the
placement head can help optimize the throughput rates.
This research develops an application using genetic algorithm (GA) to solve the
component placement sequencing problem for a single headed placement machine. Six
different methods were employed. The effects of two parameters which are critical to
the execution of a GA were explored at different levels. The results obtained show that
the one of the methods performs significantly better than the others. Also, the
application developed in this research can be modified in accordance to the problems
or machines seen in the industry to optimize the throughput rates. / Graduation date: 2004

Identiferoai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/30048
Date11 December 2003
CreatorsHardas, Chinmaya S.
ContributorsDoolen, Tori L.
Source SetsOregon State University
Languageen_US
Detected LanguageEnglish
TypeThesis/Dissertation

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