چکیده مقاله
Although additive manufacturing AM technologies continue to improve, some primary challenges still hinder its broad adoption The challenges include the following: parts qualification; quality assurance; process reliability needs for in situ, real time monitoring systems; and predictive modeling approaches that support fault detection, diagnosis, and prediction In situ AM monitoring systems can be designed and implemented using a wide range of sensors; each sensor can independently measure a specific parameter The amount, type, and speed of the collected data from these sensors are unprecedented It needs to be combined and processed into meaningful information for monitoring systems and closed loop control processes In such cases, all sensors' independent measurements are combined into a complete measurement value, and unique signal processing algorithms are used to make a comprehensive overview of the measurement This process is named multi sensor data fusion MSDF This paper will summarize the MSDF architectures and algorithms; it also demonstrates the current applications of MSDF in AM technologies
کلیدواژهها
نویسندگان
Ahmed Shany Khusheef
PhD student, School of Mechanical Engineering Iran University of Science and Technology Kut Technical Institute, Middle Technical University, Baghdad, IRAQ
Mohammad Shahbazi
Assistant Professor, School of Mechanical Engineering Iran University of Science and Technology
Ramin Hashemi
Associate Professor, School of Mechanical Engineering Iran University of Science and Technology
شیوه ارجاع
Shany Khusheef, Ahmed and Shahbazi, Mohammad and Hashemi, Ramin,1399,Multi-Sensor Data Fusion for Additive Manufacturing: An Overview,17th National Conference and 6th International Conference on Manufacturing Engineering,Tehran
ارائهشده در
مجموعه مقالات هفدهمین همایش ملی و ششمین کنفرانس بین المللی مهندسی ساخت و تولید12 اسفند 1399 · تهران