Applying a new artificial intelligence algorithm to Optimize technological parameters when polishing K9 optical lens materials by magnetized liquid solution

ABSTRACTIn order to achieve a high-quality superfine surface on K9 glass, a novel algorithm was developed for addressing optimisation challenges in high-precision machining using magnetised liquid solution. This algorithm employs a collective global exploration developed based on AI (Artificial Intelligence) inspiration, which effectively coordinates various nonlinear systems encountered during the machining process. By integrating multiple nonlinear systems and utilising straightforward physical techniques, the goal is to create a powerful artificial intelligence algorithm in optimising nonlinear systems (AIONS). This algorithm aims to achieve the same level of versatility and rapid convergence observed in enhancing surface quality during the burnishing of optical material K9. To demonstrate the effectiveness of the AIONS algorithm, benchmark functions were analysed in conjunction with optimising the K9 optical glass polishing process. Polishing experiments were conducted to determine the ideal technical parameters using the new algorithm and a straight permanent magnetic yoke surface finishing approach. The analysis and experimental results revealed that when polishing K9 optical glass materials with a permanent-magnetic yoke field and employing a magnetised liquid solution (MLS) with technological parameters guided by the AIONS algorithm, exceptionally smooth surface finish with an Ra value of 0.480 nm was achieved, leaving no scratches on the polished surface. The objective of this study is to provide valuable insights into optimising the surface polishing of challenging materials like K9 optical glass and other materials used in the optical industry.KEYWORDS: AIONSK9 optical glassmagnetised liquid solutionpolishingoptimisation Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis research received no specific grant from any funding agency in the public.Notes on contributorsLe Anh DucLe Anh Duc is a Dr. at Hunan University, China. He is currently working at the Training Department, at Hanoi Industrial University. His research interests include Hybrid and Optimized Algorithms, Optimization algorithms in mechanical machining, micro and nano-fabrication, ultra-precision machining, superfine processing, and ultra-high-speed processing.Nguyen Minh QuangNguyen Minh Quang is a Lecturer in the Faculty of Mechanical Engineering at Hanoi University of Industry, Hanoi, Vietnam. His research interests include researching and developing optimization algorithms in precision machining, micro and nano-fabrication, ultra-precision machining, superfine processing, and ultra-high-speed processing.Nguyen Tien TungNguyen Tien Tung is a Lecturer in the Faculty of Mechanical Engineering at Hanoi University of Industry, Hanoi, Vietnam. His research interests include micro and nano-fabrication, ultra-precision machining, and superfine processing.Le Thi Phuong ThanhLe Thi Phuong Thanh is a Lecturer in the Faculty of Mechanical Engineering at Hanoi University of Industry, Hanoi, Vietnam. Her research interests include micro and nano-fabrication, ultra-precision machining, superfine processing, and ultra-high-speed processing.