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This thesis by Sanjay Nambiar explores adaptive automation technologies in the context of customized product development in the manufacturing industry. It delves into various innovative techniques such as Knowledge-Based Engineering (KBE), Multi-Disciplinary Optimization (MDO), and machine learning frameworks to enhance efficiency and flexibility in product design and development. The research establishes automated frameworks for fixture design and gas turbine optimization, integrating methods such as reinforcement learning and digital twin technology. The work aims to bridge the gap between theoretical concepts and practical applications, offering solutions for seamless integration of automation in both structured and unstructured production environments. Intended for professionals and researchers in industrial automation and manufacturing, it provides insights into overcoming challenges and implementing advanced automation technologies.

Automation. --- Manufacturing processes. --- Automation --- Manufacturing processes