Statistical modelling of process parameters in micro cutting

Abstract

Micro production, with an annual forecasted growth rate of 20 per cent will clearly be a key technology of the 21st century. High-precision engineering, which uses miniaturized conventional manufacturing techniques, e.g. milling, turning, and drilling, has significant potential for application to the manufacture of micro-sized products with exacting precision and accuracy requirements. Owing to its flexibility and its ability to produce complex three-dimensional geometric shapes in a broad variety of different materials, micro cutting is of special importance both for small scale and mass production environments. However, cutting in micro dimensions follows special rules caused by size effects. Successful micro cutting depends on statistically reliable and robust processes and therefore on knowledge about parameter adjustments and process characterization. Statistical analyses of experimental micro cutting data and modelling studies are used to study the effects and interactions of process parameter variations for workpiece material, cutting edge radii, cutting speed, depth of cut, and application of a lubricant. The results show a significant influence of most of the mentioned factors on the response variable surface roughness and specific cutting force. Based on the experimental data and the statistical modelling studies, linear models for the specific cutting force and surface roughness are proposed. In addition, the outcome is compared to the empirical cutting model of Victor-Kienzle derived for application in macro dimensions.