This study is a part of the ongoing project at the Division of Production and Materials Engineering titled “DynPCM: Dynamic Process Condition Monitoring for Brake Disk (BD) production line”.

According to the project description “we live in a world where the industry does not know how to process efficiently newly developed superalloys, an availability of “critical raw materials” used for the production of alloys and tool materials becomes critical, up to 90% of sensors used in machining centers can be unused, information from the processes are not stored or managed inefficiently, microstructure and properties of casted or stamped blanks can significantly vary and information about their properties is unavailable, and, in addition, high part of manual control of product quality. All these lead to inefficient management of the production process, extra costs, and a high percentage of rejected produced parts (and this is a small part of the possible negative consequences).”

This study will be focused on the BD’s machinability issues at the conditions of variable material properties due to the aging.

·      Study of microstructure variation between different batches and different aging time of Brake Disk (BD) workpieces (Experimental part)

·      Machining tests of given BDs with collection data on the process by different sensors (Experimental part)

·      Processing of data and feature extraction for process characterization (for further development of BD’s machinability model) (Computational part)

The work is suitable for 1-2 students with a background in manufacturing systems, moderate knowledge of Matlab/Python. Some knowledges in Machine learning (or a huge motivation to learn ML/AI methods) are preferable. The study will be concluded as a written report of the Project Course or MSc thesis with an oral presentation of the results at LTH, LU.