This paper presents a breakthrough paradigm for optimizing bottle manufacturing that incorporates modern technologies like RFID, cloud-based OTP verification, and ML. Its primary goal is to improve quality control, secure user access, and encourage environmental stewardship throughout the production process. The system begins with RFID authentication, which only allows authorized individuals to operate the machines. Cloud-based OTP verification provides an additional degree of protection, limiting illegal access. Real-time sensor monitoring allows for timely anomaly discovery during manufacturing. ML is critical, to using sensor data to build a model that identifies and forecasts production faults. This continual learning loop increases process efficiency and precision. In the ML model, the manufacturing process begins with raw material handling and progresses to bottle manufacture. Infrared sensors monitor bottle height to ensure compliance with requirements, and rejected bottles are spotted immediately. Quality checks assign each bottle a unique ID and record production timestamps. The emphasis is on waste reduction and recycling, which aligns with ecologically responsible practices. Any waste materials generated during manufacturing are recycled, which helps maintain environmental sustainability. The research proves the suggested framework’s efficiency and sustainability, which results in a secure, real-time monitored, and quality-assured production process. The sophisticated feedback loop and waste reduction techniques demonstrate the dedication to continual improvement and environmental stewardship. This framework provides a solid foundation for the progress of smart manufacturing techniques, promoting the evolution of sustainable and efficient industrial processes. It emphasizes the potential for merging cutting-edge technologies to address quality control, security, and environmental challenges in manufacturing.