PCB assembly planning using genetic algorithms

1998 ◽  
Vol 14 (5) ◽  
pp. 363-368 ◽  
Author(s):  
L. P. Khoo ◽  
N. S. Ong
Keyword(s):  
Genetic Algorithms ◽  
Assembly Planning ◽  
Pcb Assembly

Multiple setup PCB assembly planning using genetic algorithms

2002 ◽  
Vol 42 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Shantanu Deo ◽  
Roya Javadpour ◽  
Gerald M. Knapp
Keyword(s):  
Genetic Algorithms ◽  
Assembly Planning ◽  
Pcb Assembly

Assembly Planning: A Genetic Approach

1998 ◽  
Author(s):  
Shiang-Fong Chen
Keyword(s):  
Genetic Algorithms ◽  
Fitness Function ◽  
Assembly Planning ◽  
Genetic Approach ◽  
Genetic Operators ◽  
Complex Problems ◽  
All Solutions ◽  
Assembly Problem ◽  
Optimal Assembly

Abstract The difficulty of an assembly problem is the inherent complexity of possible solutions. If the most suitable plan is selected after all solutions are found, it will be very time consuming and unrealistic. Motivated by the success of genetic algorithms (GAs) in solving combinatorial and complex problems by examining a small number of possible candidate solutions, GAs are employed to find a near-optimal assembly plan for a general environment. Five genetic operators are used: tree crossover, tree mutation, cut-and-paste, break-and-joint, and reproduction. The fitness function can adapt to different criteria easily. This assembly planner can help an inexperienced technician to find a good solution efficiently. The algorithm has been fully implemented. One example product is given to show the applications and results.

Planning of Component Placement/Insertion Sequence and Feeder Setup in PCB Assembly Using Genetic Algorithm

1993 ◽  
Vol 115 (4) ◽  
pp. 424-432 ◽  
Author(s):  
M. C. Leu ◽  
H. Wong ◽  
Z. Ji
Keyword(s):  
Genetic Algorithm ◽  
Printed Circuit Board ◽  
Circuit Board ◽  
Assembly Planning ◽  
Genetic Operators ◽  
Printed Circuit Board Assembly ◽  
Component Placement ◽  
Pcb Assembly ◽  
Circuit Board Assembly ◽  
Genetic Algorithm Approach

A new application of the genetic algorithm approach is introduced to solve printed circuit board assembly planning problems. The developed genetic algorithm finds the sequence of component placement/insertion and the arrangement of feeders simultaneously, for achieving the shortest assembly time, for three main types of assembly machines. The algorithm uses links (parents) to represent possible solutions and it applies genetic operators to generate new links (offspring) in an iterative procedure to obtain nearly optimal solutions. Examples are provided to illustrate solutions generated by the algorithm.

Automatic Assembly Planning Based on Genetic Algorithms

1996 ◽  
Vol 29 (1) ◽  
pp. 553-558
Author(s):  
Milad F. Sebaaly ◽  
Hideo Fujimoto
Keyword(s):  
Genetic Algorithms ◽  
Assembly Planning ◽  
Automatic Assembly

Concurrent assembly planning with genetic algorithms

2000 ◽  
Vol 16 (1) ◽  
pp. 65-72 ◽  
Author(s):  
Nicola Senin ◽  
Roberto Groppetti ◽  
David R Wallace
Keyword(s):  
Genetic Algorithms ◽  
Assembly Planning

Modeling of Order Oriented Planning for Printed Circuit Board Assembly Line

2015 ◽  
Vol 789-790 ◽  
pp. 1245-1251
Author(s):  
Ullah Saif ◽  
Zai Lin Guan ◽  
Zong Dong He ◽  
Cong He ◽  
Cao Jun
Keyword(s):  
Assembly Line ◽  
Printed Circuit Board ◽  
Circuit Board ◽  
Mixed Integer ◽  
Assembly Planning ◽  
Sequencing Problem ◽  
Printed Circuit ◽  
Pcb Assembly ◽  
Planning Problems ◽  
Model Sequencing

Printed circuit board (PCB) assembly planning problem has been given lot of attention to efficiently manage the orders of different PCB products. However, little effort has been paid to describe its comprehensive model which can demonstrate all the planning problems collectively considering in the surface mount technology (SMT) lines. A mixed integer model for PCB assembly line which includes the integration of different levels of the planning problems and considered component allocation problem (line balancing), PCB model sequencing problem (mixed model sequencing problem), feeder arrangement problem and component placement sequencing problem on different SMT machines collectively. Current research is significant to solve different planning problems of the PCB assembly line simultaneously to get the overall global solution of the problem in future.

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