CAREER: Collaborative Information Processing of Distributed Sensor Networks for Manufacturing Quality Improvement

该学院早期职业发展（Career）计划开发、教授和实施分布式传感器网络的协同信息处理方法，以提高制造质量，以支持综合研究和教育计划。最近的研究集中在硬件（传感器设备）和网络技术的发展上。现在的挑战是提供决策支持能力，以实现分布式传感器网络在制造质量控制方面的全部潜力。为了实现这一目标，提出的方法包括：(i)网络化传感器系统的协同故障诊断；（ii）在役传感器系统自诊断；(3)面向诊断的传感器分布优化设计。CAREER项目将采用多学科方法，将工程知识、多元统计（如时空分析）以及控制理论（如宇称空间方法）相结合，以解决技术挑战。CAREER项目将进行各种合作努力，为本科生和本地高中教师/学生扩大研究机会。如果成功，该CAREER项目将通过为分布式传感器网络的信息处理能力提供新的概念、标准和算法，并为下一代制造诊断系统创造一种可行的方法，从而推动分布式传感器网络的发展。实现这一目标将显著降低成本，提高质量，减少停机时间，提高美国工业和我国经济的竞争力。职业教育计划将通过课程和实验室开发、教学创新和其他推广活动为劳动力培训做出积极贡献。与少数民族大学和当地高中的合作将加强对代表性不足的群体的工程教育。通过会议/期刊出版物和国际/工业合作的广泛传播将导致所产生的方法广泛应用于许多其他分布式传感器网络，这些网络对国家的经济增长至关重要。

This Faculty Early Career Development (CAREER) proposes to develop, teach, and implement collaborative information processing methodologies for distributed sensor networks in manufacturing quality improvement to support an integrated research and education program. Recent research has focused on development of hardware (sensor devices) and network techniques. The challenge now is to provide decision support capabilities that will allow the full potential of distributed sensor networks to be realized for manufacturing quality control. Toward that goal, the proposed methodology includes: (i) collaborative fault diagnoses in networked sensor systems; (ii) in-service sensor system self-diagnosis; and (iii) diagnosis-oriented optimal design of sensor distribution. The CAREER project will employ a multidisciplinary approach, where engineering knowledge, multivariate statistics (such as spatio-temporal analysis), as well as control theory (such as parity space approaches) will be integrated to address the technological challenges. The CAREER project will undertake various collaborative efforts to expand research opportunities for undergraduate students and teachers/students from local high schools. If successful, this CAREER project will advance the state of the art on distributed sensor networks by contributing new concepts, criteria, and algorithms to its information-processing capabilities and create an enabling methodology for next-generation manufacturing diagnostic systems. Accomplishing the goal will lead to a remarkable cost reduction as a result of improved quality and reduced downtime, boosting the competitiveness of US industries and our nation's economy. The CAREER education program will make a positive contribution to workforce training through curriculum and lab development, teaching innovations, and other outreach activities. Collaboration with a minority-serving university and local high schools will enhance engineering education for underrepresented groups. Broad dissemination through conference/journal publications and international/industrial collaborations will lead to wide application of the resulting methodology to many other distributed sensor networks that are of vital importance to the nation's economic growth.