An Ant Colony Optimization Algorithm for the PCB Assembly Using A Turret Style Surface Mount Placement Machine

• Main Authors: Ying-Chieh Fang, 方英傑
• Other Authors: Chiuh-Cheng Chyu
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/81271579545628683720

碩士 === 元智大學 === 工業工程與管理學系 === 91 === The electronics industry continues to grow worldwide nowadays. Most electronic products manufactured today contain printed circuit boards (PCBs) as critical elements. In order to meet the increasing demands for PCBs in the highly competitive electronics industry, placing PCB components efficiently is critically important. The purpose of this thesis is to develop an efficient algorithm for solving the component placement problem using a turret style surface mount placement machine, for example, the Fuji CP series machines. This problem consists of two interdependent subproblems: (1) feeder rack assignment (FRA), that concerns which component type being assigned to which location on the feeder rack, and (2) component placement sequence (CPS), that concerns the order of all components being placed on the board. The amount of time for each component placement takes the maximum value among the three machine movements: feeder carriage, PCB table, and turret. In this paper, an Ant Colony Optimization (ACO) algorithm is developed to solve the integrated problem based on the strategy, CPS first and FRA second (CPS-FRA). The algorithm is states as follows: at first the CPS problem is solved by an ACO with 3-Opt improvement, and then a type-to-type communication matrix recording the number of times for the movements between any pair of component types is established according to the CPS solution. Finally another ACO with bottleneck positions swaps is applied to find an Open-TSP solution with respect to the matrix. The solution produces the FRA. In order to learn how effective the developed ACO is, three another algorithms using the same strategy and three algorithms using the strategy FRA-CPS are developed. The first three algorithms solve the CPS problem using TSP solving method such as Hungarian method + Patching operations + Local improvement (HPL) and ACO, and then group the component types according to the number of communications in the CPS solution. Finally, an FRA solution is found using the HP method to connect the disjoint groups. The algorithms using the FRA-CPS are developed based on the principle: placing all components of one type at a time. Ten test problems, three of them drawn from previous researches and the remainder randomly generated, are used for the seven algorithms to make comparison with one another. The PCB table movement time, the turret movement time, and the feeder carriage movement time are counted according to estimator functions given in a research paper. As a result, we conclude that the proposed ACO algorithm performs the best. The other three CPS-FRA algorithms perform next, and the three FRA-CPS algorithms have the worst performance.