Printed circuit board (PCB) assembly forms the core of a vast array of contemporary manufactured products. The requirements for higher component densities on PCBs, rigid functional specifications, smaller packages and greater reliability, move the electronics manufacturing industry towards automating PCB assembly. Owing to the complexity of PCBs, it becomes impractical to plan the assembly sequence manually. This paper presents a prototype genetic algorithms (GAs) enhanced planning system for surface mount PCB assembly. The prototype system uses GAs to generate the component placement sequence and the component-feeder arrangement for a rotary disk turret, concurrent pick and place SMD machine equipped with a time-delay function. The sequencing process is formulated as a multi-objective optimisation problem under constraints. A framework of the prototype system and the derivation of the multi-objective function are described. The prototype system was validated using examples gleaned from literature. Details of the validation are reported.
[1]
S. H. Yeo,et al.
A rule-based frame system for concurrent assembly machines
,
1996
.
[2]
Ming-Chuan Leu,et al.
Adaptive Genetic Algorithm for Optimal Printed Circuit Board Assembly Planning
,
1993
.
[3]
Ming-Chuan Leu,et al.
Planning of Component Placement/Insertion Sequence and Feeder Setup in PCB Assembly Using Genetic Algorithm
,
1993
.
[4]
Krishnaswami Srihari,et al.
Placement sequence identification using artificial neural networks in surface mount PCB assembly
,
1996
.
[5]
Junie McCree.
The travelling salesman
,
1913
.
[6]
Manfred Gronalt,et al.
Job sequencing and component set-up on a surface mount placement machine
,
1998
.
[7]
L. P. Khoo,et al.
PCB assembly planning using genetic algorithms
,
1998
.
[8]
Hans-Otto Günther,et al.
A heuristic for component switching on SMT placement machines
,
1997
.