Multi-objective optimization of laser cleaning for TiAlN coating using grey-Taguchi based method

Abstract Cleaning of TiAlN coatings is essential for enabling tool reuse in sustainable manufacturing and aerospace. However, conventional cleaning methods such as mechanical and chemical treatments often cause substrate damage or environmental concerns, while existing laser cleaning studies mainly focus on single-objective optimization and lack simple, industry-oriented cleanliness evaluation methods. This study aims to develop an efficient and practical multi-objective optimization approach for laser cleaning of TiAlN coatings, balancing cleaning quality and processing time. A simulation model using COMSOL Multiphysics was established to analyse the effects of laser parameters (power, pulse width) and process parameters (repetition frequency, scan speed) on the heat-affected zone. Based on the simulation results, a Taguchi orthogonal experimental design was conducted to evaluate cleaning quality and cleaning duration. Cleaning quality was assessed using an image-processing method based on the ratio of dark pixels, while the Grey-Taguchi method was applied to optimize multi-objective cleaning with different weight factors for cleanliness and cleaning time. The research results show that power and pulse width are the most important factors when considering only cleaning quality, achieving a cleanliness level of up to 86%. When prioritizing cleaning quality and considering cleaning time with weight factors of 0.6 for cleanliness and 0.4 for cleaning duration, the results show a cleanliness level of up to 84%, with cleaning duration approximating 2 s. In multi-objective optimization, scan speed is identified as the most influential factor affecting the balance between cleaning quality and efficiency. The proposed Grey-Taguchi-based framework provides a simple, efficient, and industry-applicable approach for optimizing laser cleaning processes. The integration of simulation, image-based evaluation, and multi-objective optimization offers a practical solution for balancing quality and efficiency in industrial coating removal.