Collaborative Research/GOALI: Analysis and Optimization Method for Distributed Sensor Systems in Electronics Assembly Processes Systems

该合作研究/工业学术联络机会(GOALI)为开发和实施一种分析和优化电子组装过程中的分布式传感器系统的方法提供资金，目的是为了诊断过程故障。所提出的建模工具将使用站索引状态空间模型在多工位装配系统框架中集成产品质量信息和工艺特征。然后，通过扩展控制论中可观测性的概念，探讨一般分布式传感器系统的可诊断性。这将进一步促进基于多元数据分析的故障特征提取的故障诊断方法的发展。通过对状态空间质量-故障模型和可诊断性分析所提供的质量信息转换的理解，将指导传感系统的优化设计。该项目将由德克萨斯A&M大学、威斯康星大学麦迪逊分校和摩托罗拉佛罗里达研究实验室(MFRL)密切合作实施。方法的开发将基于摩托罗拉无线电组装过程，由此产生的技术将在其中进行测试和实施。如果成功，该项目的结果将有助于制造业的传感和信息技术：将定义关于传感器系统性能的新概念和标准，并将开发用于传感优化和数据分析的有效算法。根据研究成果开发的课程将对质量工程和生产系统的教育产生长期影响。由此产生的技术也将使面临来自国际竞争对手巨大压力的美国电子制造商受益。根据互连技术研究所1999年发布的一份白皮书，在过去5年中，美国650家电子制造商中有100多家倒闭。缺乏六西格玛质量被认为是美国制造商的最薄弱环节。由此产生的方法在工业上的实施将有助于美国制造商保持竞争力，并可能产生重大的经济影响。

This Collaborative Research/Grant Opportunities for Academic Liaison with Industry (GOALI) provides funding for the development and implementation of a methodology for the analysis and optimization of a distributed sensor system in electronics assembly processes for the purpose of process fault diagnosis. The proposed modeling tool will integrate product quality information and process characteristics in a multi-station assembly system framework using a station-indexed state space model. Then, the diagnosability of a generic distributed sensor system will be explored by expending the concept of observability in control theory. This will further lead to development of the fault diagnosis method for fault feature extraction based on the multivariate data analysis. The understanding of the transformation of quality information, offered by the state space quality-fault model and diagnosability analysis, will guide the optimal design of a sensing system. This project will be carried out through a close collaboration partnered by Texas A&M University, the University of Wisconsin - Madison, and Motorola Florida Research Labs (MFRL). The methodology development will be based on, and the resulting technology will be tested and implemented in, the Motorola radio assembly process. If successful, the results of this project will contribute to sensing and information technology in manufacturing: new concepts and criteria regarding the performance of sensor systems will be defined and effective algorithms for sensing optimization and data analysis will be developed. Curriculum developed from research accomplishments will generate long-term impacts on the education of quality engineering and production system. The resulting technology will also benefit the US electronics manufacturers who are under great pressure from their international competitors. According to a White Paper issued by the Interconnection Technology Research Institute in 1999, over 100 of 650 U.S. electronics fabricators have gone out of business in the past five years. The lack of six-sigma quality is identified as the weakest point of for US manufacturers. Industrial implementation of the resulting methodology will aid US manufacturers in remaining competitive and could generate substantial economic impacts.