Part thermal damage is a process limitation in finish hard turning and understanding process parameter effects, especially, tool wear, on cutting temperatures is fundamental for process modeling and optimization. This study develops an analytical model for cutting temperature predictions, in particular, at the machined-surfaces, in finish hard turning by either a new or worn tool. A mechanistic...

In this paper, predictive modeling of cutting and ploughing forces, stress distributions on tool faces, and temperature distributions in the presence of tool flank wear are presented. The analytical and thermal modeling of orthogonal cutting that is introduced in Part I of the paper is extended for worn tool case in order to study the effect of flank wear on the predictions. Work material const...

Tool condition monitoring (TCM) plays an important role in improving machining efficiency and guaranteeing workpiece quality. In order to realize reliable recognition of the tool condition, a robust classifier needs to be constructed to depict the relationship between tool wear states and sensory information. However, because of the complexity of the machining process and the uncertainty of the...

The quality of a machined surface is becoming more and more important to justify the increasing demands of sophisticated component performance, longevity, and reliability. Usually, any machining operation leaves its own characteristic evidence on the machined surface in the form of finely spaced micro irregularities (surface roughness) left by the associated indeterministic characteristics of t...

Metal matrix composites have been widely used in industries, especially aerospace industries, due to their excellent engineering properties. However, it is difficult to machine them because of the hardness and abrasive nature of reinforcement elements like silicon carbide particles (SiCp).In the present study, an attempt has been made to investigate the influence of spindle speed (N), feed rate...

Artificial neural networks of sigmoidal and McCullochPitts neurons have found increasing favour in industry research because of their most attractive features, abstraction of hardly accessible knowledge and generalisation from distorted sensor signals. In recent years experimental evidence has been accumulating to suggest that biological neural networks, which communicate through spikes, use th...