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SOFT COMPUTING APPROACH

The development of reliable cutting tool monitoring system is an important step for the development of unmanned CNC turning centre. In the absence of a human operator, the automated system must compensate for the lack of human experience and judgment abilities. The present industrial scenario is to produce quality products at competitive prices. This is possible with the increased productivity aimed at zero error. To achieve this, industries are now moving towards unmanned factory where the human error is reduced to great extent. Timely change of the cutting tool towards the end of its useful life prevents inferior surface finish quality or worse damage to the machine tool itself. Initially the wear has been measured with the help of tool maker’s microscope under laboratory conditions. This requires human inspector to determine the worn region based on the textural difference between the worn and unworn surfaces. Obviously the process is not correct place and is time consuming. To achieve full automation in the turning centre, it is important that some soft-computing technique is adopted in conjunction with the cutting process to predict the tool wear taking place. Artificial Neural Network and Fuzzy Logic techniques are adopted in this project to predict the tool wear. Cutting parameters values like velocity, feed, depth of cut are obtained from the experimental results. To reduce manufacturing lead time and number of rejections there are various processing procedures and extreme efforts of the tool and machines are required.



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