Advanced Robotics and Autonomous Systems in Flexible Manufacturing

Abstract

The accelerating demand for product variety, shorter production cycles, andmass customization has rendered traditional rigid manufacturing linesincreasingly inadequate for modern industrial requirements. Flexiblemanufacturing systems (FMS) augmented with advanced robotics andautonomous decision-making capabilities represent a paradigm shift towardadaptive, reconfigurable, and intelligent production environments. This paper presents a comprehensive experimental and simulation-based investigation of a robotic flexible manufacturing cell integrating collaborative robots (cobots), autonomous mobile robots (AMRs), and a digital twin-enabled intelligent scheduling framework for multi-product small-batch manufacturing. The proposed system employs a Universal Robots UR10e 6-axis cobot for assembly operations, a MiR250 AMR for autonomous material transport, and a reinforcement learning-based task scheduler operating on an edge computing platform. The system was validated in a pilot manufacturing cell at Arya College of Engineering and IT, Jaipur, producing three distinct product families with lot sizes ranging from 5 to 50 units. Experimental results demonstrated a 34.6% reduction in changeover time, 28.2% improvement in overall equipment effectiveness (OEE), and 41.3% reduction in work-in-progress inventory compared to a conventional semi-automated production line. The reinforcement learning scheduler achieved 96.8% on-time delivery performance across 240 production orders over a 12-week validation period. The findings confirm that intelligent robotic systems with autonomous scheduling capabilities can enable economically viable high-mix low-volume manufacturing [1], [2].  KEYWORDS: Flexible Manufacturing, Collaborative Robots, AutonomousMobile Robots, Reinforcement Learning, Digital Twin, Smart Manufacturing,Industry 4.0, Production Scheduling, Cobots, Reconfigurable Manufacturing