Authors: Dr. Priyanka Deshmukh, Mr. Rahul Mehta
Abstract: customization in manufacturing demands flexible, efficient, and precise process planning to accommodate a wide variety of product variants while maintaining low costs and lead times. Artificial intelligence (AI) has emerged as a transformative technology for process planning in Computer Aided Manufacturing (CAM) systems, enabling intelligent decision-making, optimization, and automation tailored for mass customization. This paper explores AI-powered process planning methodologies that integrate machine learning, optimization algorithms, and knowledge-based systems within CAM environments. The study evaluates benefits including improved adaptability, enhanced resource utilization, and reduced planning time. Two detailed tables present AI techniques applied in process planning and a comparative analysis of conventional versus AI-driven planning approaches. Challenges such as data requirements, model interpretability, and system integration are also discussed. The paper concludes with future directions to advance AI-powered process planning for mass customization in CAM
Keyword: Artificial intelligence, Process planning, Computer aided manufacturing, Mass customization, Machine learning, Optimization
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