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Application of an improved Spider Monkey Optimization algorithm for component assignment problem in PCB assembly

机译：改进蜘蛛猴优化算法在PCB组件中的组件分配问题中的应用

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This paper presents a new optimization method for printed circuit board assembly (PCBA) process based on improved spider monkey optimization (SMO) algorithm, and a production model for PCBA is created. The proposed method proves to be suitable for product-service system (PSS). PCBA process mainly consists of three parts. First is the assignment of PCB, second is the assignment of machines, the last is the component assignment problem. In this research, the SMO algorithm is applied on optimization of component assignment which is divided into two stages: local leader phase (LLP) and global leader phase (GLP). In the first stage, the electronic components are assigned to the feeders by GLP. In the second stage, the component placement sequence, which is apparently known as a travelling salesman problem (TSP), is determined by LLP. Numerical experiments are performed to compare the performance of SMO algorithm with others under various experimental settings, the results show that the proposed method is more effective than other traditional methods. A production model is created with the proposed method, which is calimed to be able to increase the efficiency of the product services.
机译：本文介绍了一种新的用于印刷电路板组件（PCBA）过程的新优化方法，基于改进的蜘蛛猴优化（SMO）算法，创建了PCBA的生产模型。所提出的方法证明适用于产品 - 服务系统（PSS）。 PCBA过程主要由三个部分组成。首先是PCB的分配，第二是机器的分配，最后是组件分配问题。在这项研究中，SMO算法应用于优化组件分配的优化，该分配分为两个阶段：本地领导阶段（LLP）和全球领导阶段（GLP）。在第一阶段，电子元件通过GLP分配给馈线。在第二阶段，由LLP确定显然被称为旅行推销员问题（TSP）的组件放置序列。进行数值实验以比较各种实验设置下与他人的SMO算法的性能进行比较，结果表明该方法比其他传统方法更有效。使用所提出的方法创建生产模型，该方法是能够提高产品服务的效率。

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