SCORING MODELS FOR PROCESS MONTIORING IN INDUSTRY A MECHATRONIC APPLICATION | ||||
| The International Conference on Applied Mechanics and Mechanical Engineering | ||||
| Article 72, Volume 15, 15th International Conference on Applied Mechanics and Mechanical Engineering., May 2012, Page 1-14 PDF (223.99 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/amme.2012.37053 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| R. M. Shahin; W. M. Hussein; A. F. El-Sherif; H. M. Mahgoub | ||||
| Egyptian Armed Forces. | ||||
| Abstract | ||||
| ABSTRACT To compete on a global level, manufacturers must strive to find new solutions to ensure high product quality while maximizing productivity. One way to address many of the challenges this creates is to turn increasingly to mechatronic design approach and automation. To successfully realize automation, a mechatronic system for online process monitoring is required to take the place of an expert’s judgment. This paper outlines the use of a statistical multivariate technique called Projection to Latent Structure (PLS), and applies it to the monitoring of a machining process as an application. This approach is used to integrate machine tool sensory data from a milling machine. Experiments were conducted on a milling machine under three conditions, sharp, worn and chatter tools. The score models were tested under different conditions with the results showing that the proposed technique can be used for tool wear monitoring and can successfully differentiate between new process conditions. | ||||
| Keywords | ||||
| Process monitoring; Multivariate Analysis; Sensors; Surface roughness; Projection to Latent Structure; milling; Mechatronic system | ||||
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