Influence of microstructure and batch variations on the machinability of steels

Doctoral thesis, 2026

Material variations in steels – even within specific standards – can significantly influence machinability, leading to inconsistent tool wear behaviour that challenges process reliability, compels conservative machining strategies and increases production costs in industrial manufacturing. Although general trends are recognised within machinists, the machinability of steels is governed by a complex interplay of numerous factors that are difficult to isolate. This thesis investigates the influence of microstructural variations and non-metallic inclusion characteristics on the machinability of steels, with particular emphasis on tool wear behaviour and tribological interactions at the tool-chip interface. The thesis integrates experimental observations with modelling approaches to improve the understanding of thermo-mechanical conditions in machining. An enhanced semi-analytical model for predicting tool-chip interface temperature is developed, enabling more accurate estimation of thermal loads that govern wear mechanisms.

A multi-faceted experimental approach is adopted, combining detailed material characterisation with controlled machining tests across several steel grades, including case-hardening steels, micro-alloyed steels, bearing steels, and stainless steels. Microstructural features such as ferrite fraction, grain size, and pearlite morphology are quantified alongside non-metallic inclusion populations, including sulphides, oxides, and nitrides. These material characteristics are systematically correlated with tool wear mechanisms observed under well-defined cutting conditions. Across all investigated materials, the results demonstrate that even subtle variations in microstructure – such as reduced ferrite content, finer grain size, or decreased interlamellar spacing – lead to differences in tool wear response. In parallel, the role of non-metallic inclusions is shown to be equally critical. Soft, deformable inclusions such as MnS contribute positively to machinability by promoting chip segmentation and, in some cases, forming lubricating tribo-layers at the tool surface. In contrast, hard inclusions such as alumina-rich oxides and titanium nitrides act as abrasive particles, accelerating coating degradation and tool failure. Importantly, the findings highlight that machinability is not governed solely by inclusion quantity, but by a complex interplay of inclusion size, morphology, and chemical composition. A key contribution of this thesis lies in advancing the understanding of tribo-layer formation during machining. Through advanced characterisation techniques, including SEM, EDS, and FIB-STEM, the formation of protective layers composed of inclusion-derived material is identified as a decisive factor in tool performance. These tribo-layers can reduce friction and shield the tool surface; however, their formation is shown to be highly sensitive to both inclusion chemistry and tool coating composition.

The research further demonstrates that machinability must be interpreted as a system-level response, influenced not only by material properties but also by process conditions, geometric factors as well as cutting tool selection. Variations in tool-workpiece engagement, such as changes in effective depth of cut, are shown to significantly alter wear behaviour, particularly in industrial environments where such variations are difficult to control. The findings provide a foundation for improved material design through inclusion engineering, as well as for the development of predictive models and adaptive machining strategies aimed at achieving consistent and optimised tool performance in industrial applications.