Abstract

With an emphasis on machine learning and artificial intelligence (AI), the Internet of Things (IoT), robotics, and data analytics, this research offers a methodical empirical evaluation of cutting-edge technologies in the field of smart manufacturing. The findings indicate notable progress in the abilities of the employees. Employee 2 had an astounding 30% gain in machine learning competence, while Employee 3 demonstrated a 50% growth in robotics proficiency. Production Line Efficiency showed scope for development; Line B showed a 0.7% gain in efficiency, indicating that there is still opportunity for process improvements. Analyzing sensor data highlights the need of ongoing maintenance and monitoring to guarantee optimum machine functioning. Data from quality control indicated that stricter guidelines were required to lower product faults. With implications for increased productivity and quality, this study advances our knowledge of the revolutionary potential of smart manufacturing technologies, including workforce development, technology adoption, and process optimization.

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