The synthesis and analysis of generalized schemes of working machines are crucial for optimizing performance, efficiency, and adaptability across various industrial applications. This study presents a systematic approach to developing generalized models that represent the fundamental structural and functional principles of working machines. The proposed methodology integrates advanced morphological techniques, including cluster and set analysis, to construct and evaluate innovative machine configurations. Key performance indicators such as energy efficiency, mechanical reliability, and adaptability to diverse operating conditions are analyzed. The results demonstrate that generalized schemes can significantly enhance the design and functionality of working machines by providing flexible and scalable frameworks. This research contributes to the advancement of machine design by offering a comprehensive methodology for the synthesis and analysis of working machine architectures. This article presents an in-depth examination of advanced morphological analysis as applied to the design and optimization of generalized working machine schemes. By employing a structured approach, engineers can enhance efficiency, adaptability, and performance in various industrial applications. The proposed approach is a powerful tool for finding innovative solutions for creating working machines for machining gas turbine engine blades. Further research can be aimed at extending multiple attributes and options, integration with artificial intelligence methods.