Assessment of micro turning machine stiffness response and material characteristics by fuzzy rule based pattern matching of cutting force plots

In micro-nano systems technology (MNST), application of mechanical based machining operations such as micro turning, micro milling, micro EDM have shown promising trends to produce micro parts in batch scale. In order to ensure reproducibility better understanding on micro cutting process dynamics and sensitivity of machine stiffness and material characteristics becomes critical. In this paper, a methodology has been developed to assess machine stiffness and material dependent characteristics and demonstrated for micro turning operations conducted on DT-110 micro machining center. In this method, authors incorporate pattern matching algorithm to compare run data image of cutting force plots with that of reference plot. The reference plots of cutting forces v/s time were drawn from simulation run data computed from the micro turning process models. The run data plots of cutting force v/s time were drawn from the processed signal data obtained from the dynamometer during machining operation. The plots were fragmented into patterns and Euclidean distance computed between pair patterns of reference and measured cutting forces v/s time plot image represents the changes happened in machining conditions. This has been used to perform backward calculation to assess the machine stiffness response and material characteristic constants variations over machining time. In order to perform these comparative pattern error adjustments between reference and measured cutting force plots a fuzzy rule based algorithm has been developed.