AI-enhanced manufacturing robotics: A review of applications and trends
1 Andrews Automations, Goole, United Kingdom.
2 Faculty of Engineering, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria.
3 Independent Researcher, UK.
4 Independent Researcher, US.
Review Article
World Journal of Advanced Research and Reviews, 2024, 21(03), 2060–2072
Publication history:
Received on 13 February 2024; revised on 21 March 2024; accepted on 23 March 2024
Abstract:
This review explores the transformative impact of artificial intelligence (AI) on manufacturing robotics, elucidating a comprehensive overview of applications and emerging trends within the realm of smart manufacturing. As industries increasingly embrace Industry 4.0 principles, the integration of AI into manufacturing robots has become pivotal for enhancing efficiency, flexibility, and adaptability. The synergy of AI and manufacturing robotics has resulted in a plethora of applications that redefine traditional manufacturing processes. Machine learning algorithms empower robots with predictive maintenance capabilities, allowing them to anticipate and address equipment issues before they escalate. Computer vision technologies enable robots to perceive and interpret visual information, enhancing their ability to handle complex tasks such as quality inspection and object recognition. AI-driven collaborative robots, or cobots, seamlessly interact with human workers, optimizing workflow and productivity. Furthermore, AI-enhanced robotics play a crucial role in autonomous material handling, logistics, and supply chain management, streamlining operations in diverse manufacturing environments. Recent trends in AI-enhanced manufacturing robotics underscore the dynamic evolution of this field. Edge computing is gaining prominence, allowing robots to process data locally and respond in real-time, minimizing latency and enhancing overall system performance. The advent of reinforcement learning has empowered robots to adapt and optimize their actions based on dynamic manufacturing environments, leading to improved flexibility and adaptability. The integration of digital twins facilitates virtual simulations, enabling manufacturers to model and analyze the behavior of robotic systems before physical implementation. Explainable AI is emerging as a critical trend, ensuring transparency and interpretability in complex decision-making processes of AI-driven robotic systems. The integration of AI into manufacturing robotics represents a paradigm shift, revolutionizing traditional manufacturing practices. This review highlights the myriad applications and trends shaping the landscape of AI-enhanced manufacturing robotics. As industries continue to invest in smart manufacturing technologies, the collaborative synergy of AI and robotics is poised to drive unprecedented advancements in efficiency, quality, and agility within the manufacturing sector.
Keywords:
AI-Enhanced; Manufacturing; Robotics; Applications; Trends
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Copyright information:
Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0