Development of machine learning strategy for acquiring on-line machining skills during turning process

The selection of machining parameters in machining process needs to be automated; currently a skilled machinist does the selection. Due to the complexity of representing the process in any mathematical model, an intelligent system needs to analyse and make a decision on the process. An intelligent system was recommended to acquire the skilled of machinists on-line, while performing turning process. A recurrent Artificial Neural Network was developed and incorporated into the machine learning strategy for the ability of learning and obtain a new knowledge in turning process. The inputs for the system are the cutting parameters which are mainly controlled by the skilled machinist. The results show the system’s ability to predict the appropriate cutting parameters.