Burn threshold prediction for high efficiency deep grinding: Fid-Bau Portal

Burn threshold prediction for high efficiency deep grinding

Bell, A. / Jin, T. / Stephenson, D.J.

Burn threshold diagrams are useful for the prediction of thermally induced grinding damage and were originally developed to describe the conventional shallow cut grinding regime. With the development of new high stock removal grinding processes such as High Efficiency Deep Grinding (HEDG), the prevention of thermal damage to the workpiece is of particular concern. The principle of HEDG is based around the change in thermal characteristics of the grinding process at high Peclet numbers, whereby less heat is partitioned to the workpiece. Conventional burn threshold diagrams are valid for Peclet numbers below 50, well below the values expected in HEDG. This study presents a modified approach to the construction of burn threshold diagrams which takes account of the change in thermal partitioning with Peclet number. The approach has been validated through grinding trials over a range of specific material removal rates. By considering the fundamental changes in thermal behaviour which result from the HEDG process it has been possible to develop a new relationship between the process variables and the specific grinding energy. This relationship produces an inflected curve, which allows for an increased specific grinding energy before the occurrence of grinding burn when in the HEDG regime. Experimental results for spheroidal graphite (SG) cast iron demonstrate a good correlation with a predicted boundary for a 150 deg C temperature rise. This temperature rise was estimated from the best fit between burnt and unburnt samples when workpieces were inspected visually. The temperature rise may be considered low; however, it is of an appropriate magnitude for the material in question. Further work is required to validate this approach fully with a test programme utilising a quantitative method of burn validation such as X-ray diffraction or magnetic Barkhausen noise analysis. This work will determine if threshold temperatures are related to time temperature transformation data for specific materials.