A genetic algorithm to optimise the component placement process in PCB assembly

In printed circuit board (PCB) assembly, the efficiency of the component placement process is dependent on two interrelated issues: the sequence of component placement, that is, the component sequencing problem, and the assignment of component types to feeders of the placement machine, that is, the feeder arrangement problem. In cases where some components with the same type are assigned to more than one feeder, the component retrieval problem should also be considered. Due to their inseparable relationship, a hybrid genetic algorithm is adopted to solve these three problems simultaneously for a type of PCB placement machines called the sequential pick-and-place (PAP) machine in this paper. The objective is to minimise the total distance travelled by the placement head for assembling all components on a PCB. Besides, the algorithm is compared with the methods proposed by other researchers in order to examine its effectiveness and efficiency.     

A genetic-based algorithm for the operational sequence of a high speed chip placement machine

Surface mount component placement machines are widely used in electronic manufacturing industry for automated placement of components on printed circuit boards. In this paper, we propose a new approach to the component placement problem using high speed turret style chip shooter machine and investigate the case of one single machine and one board type case with the objective of minimizing the assembly (cycle) time per board. The proposed method first groups the component types that can be processed at the same machine speed. Then the minimum spanning tree technique is employed to perform feeder duplications, reducing the distance effect between components of each type. Finally, a genetic-based algorithm with 2-opt local search using feeder arrangement list as solution representation is applied to determine the component placement sequence. Our experimental results indicate that the algorithm produces satisfactory solutions when a lower bound on cycle time per board is used as the evaluation criterion. It is also shown that the overuse of feeder duplication will produce a negative effect on the cycle time. Finally, the algorithm can help management to make a production plan that takes both component inventory cost and cycle time into consideration.     

A genetic algorithm approach to optimising component placement and retrieval sequence for chip shooter machines

A chip shooter machine in printed circuit board (PCB) assembly has three movable mechanisms: an X-Y table carrying a PCB, a feeder carrier with several feeders holding components and a rotary turret with multiple assembly heads to pick up and place components. In order to get the minimal placement or assembly time for a PCB on the machine, all the components on the board should be placed in a perfect sequence, and the components should be set up on a right feeder, or feeders since two feeders can hold the same type of components, and additionally, the assembly head should retrieve or pick up a component from a right feeder. The entire problem is very complicated, and this paper presents a genetic algorithm approach to tackle it.     

A particle swarm optimization approach to optimize component placement in printed circuit board assembly

The particle swarm optimization (PSO) approach has been successfully applied in continuous problems in practice. However, its application on the combinatorial search space is relatively new. The component assignment/sequencing problem in printed circuit board (PCB) has been verified as NP-hard (non-deterministic polynomial time). This paper presents an adaptive particle swarm optimization (APSO) approach to optimize the sequence of component placements on a PCB and the assignment of component types to feeders simultaneously for a pick-and-place machine with multiple heads. The objective of the problem is to minimize the total traveling distance (the traveling time) and the total change time of head nozzle. The APSO proposed in the paper incorporates three heuristics, namely, head assignment algorithm, reel grouping optimization and adaptive particle swarm optimization. Compared with the results obtained by other research, the performance of APSO is not worse than the performance of genetic algorithms (GA) in terms of the distance traveled by the placement head.     

Production preparation and numerical control in PCB assembly

In this article, we analyze numerical control problems arising in a component insertion line for printed circuit board mounting. Such a line consists of a number of fully automated placement machines, connected by an automated, carrierless conveyor system. At each machine, the placement device consists of an arm equipped with a number of placement heads. Each head may serve certain component types; there is some freedom in the choice of equipment for each head. Components are supplied to each machine by tape feeders (each containing components of only one type) which are placed at certain feeder positions along the machine. Before actually operating such a line, a careful production preparation phase has to be completed, specifying for each printed circuit board type the exact way in which such a board should be mounted. Problems arising in this production preparation phase include: the choice of heads to be mounted on the placement arm of each machine, the choice of components to be placed at each machine (workload balancing), an assignment of feeders to feeder positions on each machine, clustering of components to be placed in one pick-and-place move, and the sequencing of component insertions at one machine. Formulations and solutions for all these problems are given and numerical results for some industrial examples are given. The numerical control system developed has been tested and implemented and has resulted in software, which is in use at several sites of Philips' Electronics.     

基于差分算法的贴装顺序优化问题求解

元器件取料、贴放顺序是影响印刷电路板(PCB)贴片机工作效率的关键因素之一.针对拱架型多头贴片机建立以时间为研究对象的取料、贴放顺序优化数学模型.给定解的整数编码形式,利用差分算法解决此优化问题.将迁徙操作思想引入差分算法,建立带迁徙操作的差分算法,并给出算法流程及实现方式.通过实验选择差分算法的较佳参数,用两组实验将差分算法、带迁徙操作的差分算法与遗传算法进行比较,实验表明差分算法、带迁徙操作的差分算法能够有效地解决拱架型多头贴片机元器件的取料、贴放优化问题,且优化结果较遗传算法好.     

Collision and interference correction for impeller machining with non-orthogonal four-axis machine tool

Aiming at the four-axis machining with inclined rotary working table, an approach for collision and interference correction is proposed in this paper. Based on the principle that the tool axis vector is limited in the corresponding rotation plane of four-axis machine tools, collision and interference can be eliminated by using the rotation of the ellipse which is the intersection of the plane and the cutter surface. And the minimum necessary rotation angle for the cutter to eliminate interference is obtained by solving the quartic polynomial equations with numerical method. Finally, the process techniques involved in impeller machining with non-orthogonal four-axis machine tools are developed thoroughly, and the experiments of free-form centrifugal impeller machining are rendered with details. Experiment results show that the approach is an effective approach to detect collision and avoid interference for four-axis machining and it can be directly implemented into current CAD/CAM software to promote impeller machining in industry.     

基于视觉的平面关节机器人避障路径规划

针对平面关节机器人工作平面相对固定的特性,利用相机获取工作平面的环境信息。从图片构建地图信息的过程中,提取障碍物轮廓作为障碍物栅格,并将世界坐标下的安全距离映射为像素坐标下的安全像素距离,再将轮廓曲线沿法向向外扩展安全像素距离得到完整的地图信息。考虑到传统A*算法搜索的路径存在冗余节点会对后续机器人的速度规划带来较大的困难,利用改进的A*算法,剔除了路径上的冗余节点,减小了速度规划的复杂度;同时,障碍物轮廓已被扩展安全像素距离,保证了路径搜索过程中节点到障碍物的最小距离,实现了安全距离可控的避障路径规划。     

A switching formation strategy for obstacle avoidance of a multi-robot system based on robot priority model

This paper describes a switching formation strategy for multi-robots with velocity constraints to avoid and cross obstacles. In the strategy, a leader robot plans a safe path using the geometric obstacle avoidance control method (GOACM). By calculating new desired distances and bearing angles with the leader robot, the follower robots switch into a safe formation. With considering collision avoidance, a novel robot priority model, based on the desired distance and bearing angle between the leader and follower robots, is designed during the obstacle avoidance process. The adaptive tracking control algorithm guarantees that the trajectory and velocity tracking errors converge to zero. To demonstrate the validity of the proposed methods, simulation and experiment results present that multi-robots effectively form and switch formation avoiding obstacles without collisions.     

Automated Surface Roughness Measurement

A non-contact roughness sensor is described that is suited for integration with a computer-controlled coordinate measuring machine (CMM). The sensor employs a fibre optic interferometer, electronic control system and data-processing software. The combination of the sensor and computer controlled CMM allows surface texture assessment to be made during scheduled dimensional inspections of complex curved surface components, such as turbine blades. The sensor system will measure surface roughness parameters, for example Ra, using a method that reflects standard procedures. The lightweight sensor head can be mounted on a touch probe arm and the associated articulated mounting head; this combination gives quasi 5-axis positioning ability to the overall sensor. This is suitable for automated surface finish inspection of compound curved surface blades. The sensor and its control unit are integrated with the CMM controller and its operation can be controlled through standard part-program commands used by the CMM.     

Five-axis rough machining for impellers

The most important components used in aerospace, ships, and automobiles are designed with free form surfaces. An impeller is one of the most important components that is difficult to machine because of its twisted blades. Rough machining is recognized as the most crucial procedure influencing machining efficiency and is critical for the finishing process. An integrated rough machining course with detailed algorithms is presented in this paper. An algorithm for determining the minimum distance between two surfaces is applied to estimate the tool size. The space between two blades that will be cleared from the roughcast is divided to generate CC points. The tool axis vector is confirmed based on flank milling using a simple method that could eliminate global interference between the tool and the blades. The result proves that the machining methodology presented in this paper is useful and successful.     

基于组件及多感知机制的快速碰撞检测方法

提出了一种面向虚拟装配的碰撞检测方法，其方法在传统基于包围盒层次的碰撞检测基础上，引入了多感知机制和组件技术。通过对虚拟场景中不同的装配情景和装配阶段进行分析，采用层次检测思想，基于组件层次和时序进行检测，通过距离、时间、关系和运动趋势等信息排除大量非碰撞组件，实现了快速检测。该方法已在虚拟装配平台中得到初步应用，结果表明该方法是有效和实用的，能够满足虚拟装配对碰撞检测性能的要求。     

Multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm

This paper presents a new approach to the tolerance synthesis of the component parts of assemblies by simultaneously optimizing three manufacturing parameters: manufacturing cost, including tolerance cost and quality loss cost; machining time; and machine overhead/idle time cost. A methodology has been developed using the genetic algorithm technique to solve this multi-objective optimization problem. The effectiveness of the proposed methodology has been demonstrated by solving a wheel mounting assembly problem consisting of five components, two subassemblies, two critical dimensions, two functional tolerances, and eight operations. Significant cost saving can be achieved by employing this methodology.     

汽车追尾碰撞主动头枕数学模型的建立与分析

追尾碰撞事故易导致前车乘员的挥鞭伤,从而造成一定的社会经济损失。根据生物力学的研究成果,在追尾碰撞发生时,适度减小头枕与头部的水平距离可以降低挥鞭伤的程度。为弥补传统纯机械主动头枕响应滞后的不足,采用机电结合的方法,根据感知系统提供的信息,判断行驶安全性,并提前启动主动式头枕,从而保护乘员。根据主动头枕的控制策略,提出头枕控制的算法流程,并建立了追尾碰撞的数学模型,得出前后车不同行驶状态下的最小安全距离表达式,分析了模型中关键参数的随机性与动态性;借助安全裕度开关指标实施控制操作,并以算例进行验证。     

基于虚拟加工技术的数控程序优化

针对传统数控程序中进给速度固定限制加工效率的缺点,开发了面向粗铣加工的数控程序优化系统。系统基于虚拟加工技术,能完成数控程序驱动下的切削过程仿真、切削力预测、碰撞检测等。系统利用粒子群进化算法,在满足加工条件的下,实现了数控程序中进给速度和主轴转速的优化,数控程序加工效率得到显著提高。     

模因内三角概率选择混合蛙跳算法

为优化拱架型多头贴片机贴装顺序,建立了贴装顺序数学模型。按照三角概率分布选择多只蛙实现模因进化的策略,改进混合蛙跳算法,构建模因内三角概率选择混合蛙跳算法,解决了贴装顺序优化问题。实验表明,新算法具有比混合蛙跳算法更高的收敛率,比基因遗传算法具有更好的准确性及更高的收敛率,有效解决了贴装顺序优化问题。通过算法参数分析得出,随着蛙群个体数量的增加,算法能够得到更优解;模因组数对算法的影响小于蛙群的个体数量;对应不同蛙群的个体数量,有一个与之对应的模因组数,使算法相对稳定。     

基于单片机的汽车防撞激光预警系统设计

运用激光测距理论,提出汽车防撞预警系统的设计。该系统将单片机的实时控制及数据处理功能与激光测距技术相结合,可检测汽车运行中前方障碍物与汽车的距离,通过数显装置显示距离,并由发声电路根据距离远近情况发出警告声,通知驾驶员采取相应措施,从而避免事故发生。     

Optimization of PCB component placements for the collect-and-place machines

This paper presents two hybrid genetic algorithms (HGAs) to optimize the component placement operation for the collect-and-place machines in printed circuit board (PCB) assembly. The component placement problem is to optimize (i) the assignment of components to a movable revolver head or assembly tour, (ii) the sequence of component placements on a stationary PCB in each tour, and (iii) the arrangement of component types to stationary feeders simultaneously. The objective of the problem is to minimize the total traveling time spent by the revolver head for assembling all components on the PCB. The major difference between the HGAs is that the initial solutions are generated randomly in HGA1. The Clarke and Wright saving method, the nearest neighbor heuristic, and the neighborhood frequency heuristic are incorporated into HGA2 for the initialization procedure. A computational study is carried out to compare the algorithms with different population sizes. It is proved that the performance of HGA2 is superior to HGA1 in terms of the total assembly time.     

Monitoring and classification of dimensional faults for automotive body assembly

Sudden process changes occurring during automobile body assembly processes will influence the downstream assembly process and the functionality and final appearance of the vehicle. Furthermore, these faults could result in a decreased production rate and an increase in the cost if sudden process changes are so serious that the production line has to be stopped for investigation. Thus, sudden process changes should be detected and eliminated as soon as possible to prevent defective products from being produced and to reduce the cost of repairs/reworks. A monitoring algorithm is developed to detect, classify, and group process changes by analyzing the dimensional data of car bodies. The results of this monitoring algorithm can help diagnose the root causes of variation according to the locations of measurement points, body structure, assembly sequence, and tooling layout. Measurement data obtained from an optical coordinate measuring machine (OCMM) are used to demonstrate the monitoring technique.     

共空间模式和超限学习机的模拟电路故障诊断

主成分分析属于代数特征分析方法,是一种线性映射方法,降维后的表示是由线性映射生成的,更主要的信息保留在投影空间里,而剩余的信息则被过滤掉,但保留的信息是一体的,而不是每个特征向量分别表示一个主成分,在一定程度上影响了PCA方法的效果。提出了一种基于共空间模式对主成分方法改进的模拟电路故障诊断方法。此方法利用CSP算法对PCA得到的特征向量进行处理,然后将得到的主成分输入到超限学习机以进行网络训练或故障判断。通过Sallen-Key带通滤波器电路的实例,结果表明该研究方法的有效性。