Complex Low Volume Electronics Simulation Tool to Improve Yield and Reliability
Complex Low Volume Electronics Simulation Tool to Improve Yield and Reliability
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复杂的小批量电子仿真工具可提高产量和可靠性
DOI：
10.1109/iemt.2007.4417046
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发表时间：
2007
期刊：
影响因子：
--
通讯作者：
L. Huertas
中科院分区：
文献类型：
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作者：
D. Velandia;P. Conway;A. West;D. Whalley;A. Wilson;L. Huertas
小批量和高混合的印刷电路板（PCB）的组装在产品制造期间需要一定程度的人工干预，这导致首次良率差和生产成本增加。组件级故障和非组件原因（即系统级）引起的故障，如设计和制造缺陷，可以解释这种低良率。这些因素尚未纳入预测模型中，因为系统故障原因不是由特征明确的确定性过程驱动的。本文提出了一种基于一套具有良好定义的功能和接口的交互模块化组件的仿真和分析支持工具。CLOVES（复杂小批量电子仿真）工具能够对完整的设计、制造和业务流程（贯穿整个产品生命周期）进行表征和动态仿真，以了解其产生可能导致产品故障的缺陷的倾向。本文介绍了该系统的详细信息以及如何开发该系统以满足不断变化的业务需求。使用历史数据和以前的印刷电路组件（PCA）设计规范和制造经验的知识，缺陷和良率结果可以有效地存储和重新应用于未来的问题解决。例如，过去的PCA设计规范可以在设计阶段用于修改设计或定义工艺选项，以优化产品产量和服务可靠性。
Assembly of Printed Circuit Boards (PCB) in low volumes and a high-mix requires a level of manual intervention during product manufacture, which leads to poor first time yield and increased production costs. Failures at the component-level and failures that stem from non-component causes (i.e. system-level), such as defects in design and manufacturing, can account for this poor yield. These factors have not been incorporated in prediction models due to the fact that system-failure causes are not driven by well-characterised deterministic processes. A simulation and analysis support tool being developed that is based on a suite of interacting modular components with well defined functionalities and interfaces is presented in this paper. The CLOVES (Complex Low Volume Electronics Simulation) tool enables the characterisation and dynamic simulation of complete design; manufacturing and business processes (throughout the entire product life cycle) in terms of their propensity to create defects that could cause product failure. Details of this system and how it is being developed to fulfill changing business needs is presented in this paper. Using historical data and knowledge of previous printed circuit assemblies (PCA) design specifications and manufacturing experiences, defect and yield results can be effectively stored and re-applied for future problem solving. For example, past PCA design specifications can be used at design stage to amend designs or define process options to optimise the product yield and service reliability.