Revolutionizing glass molding process: ChatGPT’s role in repairing and recycling lenses

This study investigates the potential of using the large language model developed by OpenAI, ChatGPT, to address the challenges of repairing and recycling substandard molded lenses in the glass molding process. Through experimental data and literature review, six recycling plans generated by ChatGPT were validated: polishing and grinding, reheating and reshaping, repairing with additional glass, annealing, recasting or re-manufacturing, and exhibiting. Finally, each experimental plan was evaluated in terms of economic performance, green performance, and product quality to assess their application value. Notably, annealing achieved the highest improvement in lens surface profile deviation [PV] change rate at 74.4%, and lens surface roughness [Ra] change rate at 72.6%. Compared to producing new lenses through glass molding process, recycling each lens can avoid 2152.85 kJ of energy consumption and 280.07 g of CO₂ emissions. Using ChatGPT to address resource recycling challenges can offer a user-friendly interface, enhance industrial resource utilization, and introduce various new methods for reducing CO₂ emissions.