Predicting harmful vibrations in milling and drilling operations
Kaidong Chen defended his PhD thesis with the distinction cum laude at the Department of Mechanical Engineering on April 1.
Many everyday products, such as vehicles, engines, and medical devices are manufactured using milling processes. In addition, drilling technologies are essential for accessing underground resources, advancing fundamental research in Earth geology, and developing sustainable energy solutions such as geothermal energy and carbon storage. However, both milling and drilling face a common technical challenge: unwanted vibrations during operation. A defining feature of cutting processes is that the tool repeatedly interacts with surfaces it has shaped moments earlier. As a result, the current behavior of the process depends on its past actions. Many existing engineering models simplify this effect, which can limit their ability to accurately characterize harmful vibrations under realistic operating conditions. In his PhD research, Kaidong Chen developed a new framework to describe the history鈥慸ependent dynamic behavior of cutting tools in milling and drilling processes.
When self鈥慹xcited vibrations occur during milling, they reduce product quality, shorten tool lifetime, and may even interrupt production. In subsurface drilling, unstable motion can damage expensive equipment and decrease the efficiency of energy or resource extraction. Understanding why these vibrations arise, and how they can be mitigated, is therefore important for enabling safer and more (cost-)efficient industrial processes. Kaidong Chen鈥檚 research focuses on representing how the machined or drilled surface evolves over time and evaluating how this evolving surface influences the forces on the cutting tool. By introducing a mathematical description of the surface shape, the research provides a more detailed view of how chip thickness (depth of cut) develops during milling and drilling operations. This approach allows the process to be analyzed without relying on conventional simplifying assumptions.
When self鈥慹xcited vibrations occur during milling, they reduce product quality, shorten tool lifetime, and may even interrupt production. In subsurface drilling, unstable motion can damage expensive equipment and decrease the efficiency of energy or resource extraction. Understanding why these vibrations arise, and how they can be mitigated, is therefore important for enabling safer and more (cost-)efficient industrial processes. Kaidong Chen鈥檚 research focuses on representing how the machined or drilled surface evolves over time and evaluating how this evolving surface influences the forces on the cutting tool. By introducing a mathematical description of the surface shape, the research provides a more detailed view of how chip thickness (depth of cut) develops during milling and drilling operations. This approach allows the process to be analyzed without relying on conventional simplifying assumptions.
A framework for milling
For milling, the proposed framework combines the evolution of the machined surface with the motion of the tool and machine structure. This makes it possible to study how vibrations develop not only during steady operation but also when the tool first engages the workpiece. Such transient situations are common in practice but are often neglected in traditional models. A more accurate description of these effects improves the prediction of unstable cutting conditions and supports the selection of safer operating parameters, ultimately enhancing product quality.
A framework for drilling
For drilling, the research investigates the lateral motion of deep鈥慸rilling systems, with particular focus on the phenomenon known as bit whirl. Although imbalance is often considered the main cause of this instability, the findings show that even a perfectly balanced drill bit can become unstable. Chen demonstrates that the coupling between the tool鈥搑ock interaction and the flexibility of the drill string can by itself trigger unstable drilling motion. The analysis also shows that the type of whirling motion produced by certain symmetric drill bits can be predicted using a simple indicator that depends only on the geometry of the cutting blade. This insight may help engineers design drill bits that are less susceptible to harmful vibrations.
Practical insights for the future
Overall, the new mathematical models developed in this research make it possible to simulate and predict harmful vibrations in milling and drilling systems with greater accuracy. They also contribute to a deeper understanding of the fundamental mechanisms that cause these vibrations. The results offer practical insights that can support model鈥慴ased strategies to reduce harmful vibrations. These improvements can enhance machining quality and process efficiency, extend tool lifetime, reduce the risk of tool damage, and increase the cost efficiency of drilling operations.
Title of PhD thesis: . Supervisors: Prof. Nathan van de Wouw and Prof. Emmanuel Detournay (University of Minnesota, Twin Cities, USA).