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）、传感器小团队(SST)/学术研究资助机会(GOALI)/合作研究资助为建立、验证和实施全面的多传感器规划、集成、分布和决策方法提供资金，用于复杂制造过程的有效尺寸质量控制。这项研究将建立和整合：(i)一个新的尺寸感应系统，提供中间产品和最终产品在空间和时间上密集的尺寸测量。基本方法是将不同的坐标测量传感器集成在一起，这些传感器具有精度高、速度慢的触点传感器等特点；以及精度低但速度快的区域光学传感器；一种以数学为基础的决策方法，通过综合传感数据和大量产品和工艺设计资料，有效查明复杂制造过程中工艺变化的根本原因；（iii）用于传感器分布的系统级最佳传感器分布策略，以实现最佳的可诊断性和可检查性，从而提高质量和生产率。该项目将与威斯康星大学麦迪逊分校、伊利诺伊理工学院和尺寸控制系统公司密切合作。方法学的发展将基于，最终的技术将在DCS过程仿真软件中进行测试和实施。多传感器规划、集成和分析技术将连接系统理论、计算机辅助设计、优化和高级统计等不同领域，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工艺变化，同时显着提高生产率和质量。这项技术如果开发成功，将大大提升美国工业的整体竞争力。该项目还将对新课程和教育工作的发展作出重大贡献，因为它将为机械和工业工程、系统科学和统计学领域的学生提供多学科培训。研究成果将转移到本科和研究生课程，并导致实验室发展。

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.