Sustainable optimization of micro-milling machining parameters considering reliability assessment

• Pengfei Ding ^[1] ; Xianzhen Huang ^[2]
  1. [1] Dalian Maritime University

     Dalian Maritime University

     China

     
  2. [2] School of Mechanical Engineering and Automation, Northeastern University, Shenyang, PR China
• Localización: Mechanics based design of structures and machines, ISSN 1539-7734, Vol. 53, Nº. 2, 2025, págs. 864-901
• Idioma: inglés
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• Resumen

  • Micro-milling is a crucial machining technology used for complex and precise 3D parts and plays a crucial role in modern manufacturing. In this work, to comprehensively evaluate the safety, economic feasibility, and environmental friendliness of the micro-milling processing process, a sustainable optimization framework including reliability assessment is designed. Firstly, modeling and experimental measurements are conducted on sustainability evaluation standards such as tool life, machining process, machining surface quality, material removal rate, machining cost, and carbon emissions. Subsequently, the influence of physical information such as observation/measurement data and processing errors is analyzed, and a Bayesian update method is proposed and integrated with neural networks to precisely inversion the probability distribution of parameters within the optimization cycle under conditions of uncertainty. Finally, combined with the overall sustainability indicators, the multi-objective optimization process is refined through penalty functions and weighting methods, aiming to achieve the best balance between processing performance and sustainability. The simulation and experimental results have verified the superiority of the developed framework, and the present method provides valuable guidance for sustainable micromanufacturing.