In-Process Quality Characterization of Grinding Processes: A Sensor-Fusion Based Approach
作者： Matteo Maggioni , Elena Marzorati , Marco Grasso , Bianca Maria Colosimo , Paolo Parenti
关键词: Reliability engineering 、 Work in process 、 Process (engineering) 、 Quality (business) 、 Statistical process control 、 Engineering 、 Frame (networking) 、 Sample (statistics) 、 Grinding 、 Mechanical engineering 、 Sensor fusion
摘要: The quality assessment of manufacturing processes has been traditionally based on sample measures performed the process output. This leads to common “product-based Statistical Process Control (SPC)” framework. However, there are applications actual industrial interest where post-process measurement procedures involve time-consuming inspections strongly related operator’s experience and/or expensive equipment. Cylindrical grinding large rolls may be one them. final acceptability a ground cylinder, in terms surface finish, is challenging task with traditional measuring tools, and it often depends visual his subjective evaluations. In this frame, paradigm shift required substitute troublesome monitoring in-process signal-based ones. paper reviews control issues big vibrations (i.e. chatter) major concerns. A multi-sensor approach for vibration onset detection, use multi-channel implementation Principal Component Analysis, proposed. potential benefits, issues, main criticalities discussed by analysing data real application.Copyright © 2014 ASME
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