The use of cutting fluids is technically essential for grinding processes, but is also connected disadvantages such as high costs, environmental impact, and health risks. Alternatives such as minimum quantity lubrication (MQL) offer potential, but they have limited cooling effectiveness and are therefore often combined with additional cooling methods, e.g., cryogenic cooling. Current research is investigating the use of supercritical CO₂ (scCO₂) in combination with MQL. Initial results show advantages such as lower process forces and reduced energy consumption in machining processes with geometrically defined cutting edges. Correspondingly, there is considerable research potential for machining processes with geometrically undefined cutting edges, such as grinding processes, which rely on sufficient cooling performance. However, there is currently a lack of well-founded knowledge about scCO₂ expansion and the relationships between process parameters and process behavior in grinding.
Main goal:
The project aims to develop a sound understanding and practice-oriented knowledge for the use of supercritical CO₂ (scCO₂) in combination with minimum quantity lubrication (MQL) in grinding.
The key objectives in detail are:
Optimization of the scCO₂+MQL nozzle strategy:
By analyzing physical parameters such as jet range, pressure, temperature, and fluid properties, as well as different nozzle configurations, the cooling performance in the grinding zone is to be maximized.
Understanding the grinding process with scCO₂+MQL:
The influence of the scCO₂+MQL strategy on grinding quality, tool wear, and process costs will be investigated. A direct comparison with conventional flood cooling based on emulsion will be conducted in order to quantify the technical and economic advantages of the new approach.
Modeling of application mechanisms:
Regression models will be developed to systematically capture the relationships between process parameters, material properties, and workpiece outcomes. This enables precise prediction of grinding performance under varying conditions and supports targeted process optimization.
Development of knowledge on process parameter–structure relationships:
Based on experimental and model-based analyses, optimization strategies for the efficient use of scCO₂+MQL will be derived. Both the design of grinding processes and the adaptation to different materials and grinding wheels will be considered to generate comprehensive process know-how.
The overarching goal is to establish the foundation for the application of scCO₂+MQL in grinding by transforming experimental investigations into a model-based understanding.