In-process sensing for tool wear monitoring

Abstract

With the ever-increasing availability of data, it has been crucial for every industries to collect as much data as possible and to make sense of these data to improve the efficiency of their factory or operation. As the world is moving ahead and entering the 4th industrial revolution, it is important for manufacturing company to produce better quality product at lower price. This can be achieve by gathering real-time data and making use of such data to improve the process while the product is being produce.

In this project, an attempt to produce a model which correlate the applied force from the machine and input to the Acoustic Emission (AE) model will be developed. This model will be develop using Mass-Spring-Damper as its core model along with Newton’s Second Law of Motion as it mathematical foundation.