Automated material characterisation for machinability prediction (CHARMA)
Final report - Study
The CHARMA project has aimed at prediction of machinability features before the cutting operation through the use of fast and useful techniques of steel characteristics. The analytical techniques used were Magnetic Barkhausen Noise (MBN) and pulse distribution analysis optical emission spectrometry (PDA-OES). Two carburizing steels have been compared: one with standard metallurgy and the other was Ca-treated. A quench and tempering steel was included as well. Bars and samples were heat treated to five microstructures. The steels and samples were analysed thoroughly with the PDA-OES and MBN... techniques, and with corresponding reference methods. A number of cutting tests were performed, e.g. tool life tests, designed cutting tests, cutting forces, etc. The PDA-OES technique could clearly identify Ca-treated steel from a standard steel indicating also that it could differentiate between a “successful” and “not successful” Ca-treatment. The MBN technique used, could classify the different microstructures evaluated. A scheme was implemented evaluating features of both soft phase and hard phase microstructural constituents. Two designed machining tests were developed. The “abrasivity” test revealed the contributions on abrasive wear of cutting tools coming from microstructural constituents and inclusion characteristics of the steel. A chip load test could be linked to the microstructural features recorded with MBN. However, chip breakability was found independent of the steel characteristics. In addition, a prediction model of machinability, based on input from MBN and PDA-OES was developed. Blind test samples were used for validation. The model was successful in some aspects. However, further development is recommended.