• Proven capability to run machining processes up to 40 per cent faster without accelerating tool wear, offering a direct route to major production time savings.
• Achieved high-productivity stainless steel turning using less than half the CO2 flow rates of previous studies, leaving a clean surface that simplifies post-process handling.
• Successfully translated complex cutting fluid and machine learning science into actionable industrial data, triggering a new wave of collaborative R&D projects with UK aerospace manufacturers.

Challenge

To investigate the fundamental response of machining processes when cooling and lubrication is provided by combining supercritical CO2 (scCO2) with minimum quantity lubrication (MQL). 

Background

Research engineers at the University of Sheffield AMRC secured a three-year grant from the UK’s Engineering and Physical Sciences Research Council (EPSRC) ‘Manufacturing the Future’ competition to advance cooling and lubrication science. This £274,000 award — part of a wider collaboration with the University of Sheffield and the University of Leeds — united experts in machining science, tribology, machine learning and computational fluid dynamics.

The project was driven by a need to understand the ‘why’ behind global productivity gains in advanced machining. While early research literature showed promise, the underlying scientific phenomena weren’t well understood. The team set out to bridge this gap, specifically investigating how machine learning could be leveraged to optimise process outcomes and predict performance.

Innovation

Guided by the project’s industrial steering group, the AMRC team investigated novel subtractive configurations to align research with current and future sector needs. The AMRC conducted five experimental trial periods, bridging the gap between fundamental heat transfer studies and the practical milling and turning of high-performance, hard-to-cut alloys.

The fundamental phase utilised a novel tribometer arrangement to analyse the sliding interface between tungsten carbide pins and rotating titanium and stainless steel discs. By supplying scCO2 and MQL directly into the interface, the team captured critical data on friction, temperature, adhesive build-up and disc wear.

The project then transitioned to application-focused trials, performing tool-life testing on Ti-6Al-4V (milling) and 304L stainless steel (turning). By measuring real-time heat transfer and conducting post-process laboratory inspections of worn tools, the researchers successfully identified the dominant wear mechanisms and the precise cooling efficacy of the media.

Results

Major achievements emerging from the project have included:

1. Significant time savings calculated for the milling of titanium alloys in production, based on surface speeds which were up to 40 per cent higher for a given tool wear rate. 
2. High productivity and no discernible lubricant residue in stainless steel finish turning, with CO2 flow rates less than half of typical numbers reported in prior studies. 
3. New evidence of MQL lubricant’s ability to control behaviour of the adhesion layers formed between the cutting tool and the cut material’s surface.

Impact 

The project has been well received by the aerospace industry for its ability to translate complex physics into actionable industrial intelligence. By defining how to configure practical machining processes for scCO2 and MQL, the research provides a clear roadmap for high-efficiency production.

Beyond the engineering gains, the technology offers significant operational benefits; machine operators report that the absence of a lubricant residue film simplifies post-process handling and precision measurement. 

This success has now triggered a new wave of collaborative R&D projects between the AMRC and UK aerospace manufacturers.