Inspection of Thermo-mechanical Behaviour Linearity within Different Configurations of Large Grinding Machine

Abstract

Machine tool thermal errors are an important element in machined workpiece inaccuracies. In the past few decades, thermal errors have been successfully reduced by software compensation techniques such as multiple linear regression analysis, finite element method, neural network, transfer function (TF). A phenomenological approach based on TFs is used for thermal error modelling in this research. The approach respects basic heat transfer mechanisms in the MT structure, requires a minimum of additional gauges and enables an insight into the share of individual sources in the total machine thermal error. The aim of this paper is to investigate applicability of thermal error compensation model on large grinding machine within different configurations of headstock, tailstock and workpiece. Limits of a derived linear parametric model, its implementation into machine control system and model industrial use are discussed in more detail.