SST/GOALI/Collaborative Research: Multi-Sensor Planning, Integration, and Analysis for Dimensional Quality Control of Complex Manufacturing Processes

该传感器和传感器网络（NSF 05-526），传感器小型团队（SST）/学术研究资助机会（GOALI）/合作研究资助提供资金，以建立，验证和实施全面的多传感器规划，集成，分布和决策方法，用于复杂制造过程的有效尺寸质量控制。该研究将建立和整合：（i）一个新的尺寸传感系统，以提供空间和时间密集的中间和最终产品的尺寸测量。 基本的方法是将不同的坐标测量传感器与这样的特点，如接触探针点传感器与高精度，但速度低，区域光学传感器与低精度，但速度高;（ii）一个基于数学的决策方法，有效的根本原因识别过程中的复杂制造过程中的变化，通过集成传感数据和大量的产品和工艺设计信息;以及（iii）用于传感器分布的系统级最优传感器分布策略，以实现用于质量和生产率改进的最优可诊断性和可检查性。 该项目将与威斯康星州-麦迪逊大学、伊利诺伊理工学院和尺寸控制系统公司密切合作进行。该方法的开发将基于，并由此产生的技术将在DCS过程模拟软件中进行测试和实施。 多传感器规划、集成和分析技术将把系统理论、计算机辅助设计、优化和高级统计等不同领域联系起来，以解决制造过程控制问题。因此，将开发一种新的传感器和多传感器网络系统，以帮助制造商大大减少过程变化，同时显着提高生产率和质量。这项技术如果开发成功，将大大提高美国工业的整体竞争力。该项目还将大大有助于新课程和教育工作的发展，因为它将为学生提供机械和工业工程，系统科学和统计领域的多学科培训。研究成果将被转移到本科和研究生课程，并导致实验室的发展。

This Sensors and Sensor Networks (NSF 05-526), Sensors Small Team (SST)/Grant Opportunity for Academic Research (GOALI)/Collaborative Research grant provides funding to establish, validate, and implement a comprehensive multi-sensor planning, integration, distribution, and decision-making methodology for effective dimensional quality control of complex manufacturing processes. The research will establish and integrate: (i) A new dimensional sensing system to provide spatially- and temporally-dense dimensional measurements of intermediate and final products. The basic approach is to integrate different coordinate measurement sensors with such characteristics as touch-probe point sensor with high accuracy but low speed; and area optical sensor with low accuracy but high speed; (ii) A math-based decision making methodology for effective root cause identification of process variation in complex manufacturing processes by integrating sensing data and a vast array of product and process design information; and (iii) A system-level optimal sensor distribution strategy for sensor distribution to achieve optimal diagnosability and inspectability for quality and productivity improvement. This project will be carried out in close collaboration with the University of Wisconsin - Madison, Illinois Institute of Technology and Dimensional Control System, Inc. The methodology development will be based on, and the resulting technology will be tested and implemented in the DCS process simulation software. The multi-sensor planning, integration, and analysis techniques will link such varied areas as system theory, computer aided design, optimization, and advanced statistics to solve problems on manufacturing process control. As a result, a new sensor and multi-sensor network system will be developed to help manufacturers considerably reduce process variation while at the same time significantly improve productivity and quality. This technique, if successfully developed, will provide a substantial boost to the overall competitiveness of US industries. The project will also significantly contribute towards the development of new curriculum and educational efforts as it will provide multidisciplinary training for students in the areas of mechanical and industrial engineering, system science, and statistics. Research accomplishments will be transferred into undergraduate and graduate curricula and also result in laboratory development.