A Review of the Role of Modeling and Optimization Methods in Machining Ni-Cr Super-Alloys

Ni-Cr alloys are some of the most important materials being utilized in the manufacturing industry. Their unique properties make them attractive for various applications, especially in the aerospace and automobile industries. Since machining these materials is challenging due to their properties, it is necessary to understand their machining processes and how to improve them. As a result, time and again, effort has been made to understand and model the machining of Ni-Cr alloys. In this action, different approaches, i.e., neural networks, fuzzy systems, simulations, etc., have been of great help. At the same time, efforts have been made to optimize the machining processes to find how to obtain the best outputs from the processes. Different methods, such as multi-criteria decision-making, meta-heuristic algorithms, desirability functions, etc., have been utilized in this respect. This work aims to prepare an exhaustive review of the methods used for modeling and optimization of the machining of Ni-Cr alloys. It considers five major machining operations and collects data on how these methods or algorithms have been used to improve the machining and to what extent. The use of newer advanced algorithms in manufacturing processes is on the rise, and this manuscript aims to record the methods used, their effectiveness, and their shortcomings. It also provides an insight into the methods and their compatibility. Suggestions for future work are also discussed at the end of this study.