This chapter explores the intersection of artificial intelligence (AI) and blockchain technologies in the realm of industrial robotics. The integration of AI and blockchain has the potential to revolutionize various aspects of the manufacturing sector, from enhancing robotic capabilities to optimizing supply chain management. This chapter delves into the key applications, benefits, challenges, and future prospects of combining AI and blockchain in industrial robotics. Both blockchain and artificial intelligence have generated a lot of excitement in the technology industry for a number of years. AI and blockchain applications for robotics applications thus provides productive, energy-efficient outcome and thus ease the process of automation and maintenance.
TopIntroduction
Industrial robotics has undergone significant advancements in recent years, transforming manufacturing processes across various industries. The integration of Artificial Intelligence (AI) and Block chain technologies into industrial robotics has further revolutionized the field. AI offers the ability to enhance robot perception, decision-making, and adaptability, while Blockchain ensures secure and transparent data management. Understanding the background and potential of these technologies is crucial to appreciate their applications in industrial robotics. The motivation behind exploring the applications of AI and Block chain in industrial robotics stems from several factors as follows.
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Enhanced Efficiency: AI can optimize robot operations, improving productivity and reducing errors.
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Safety Improvements: AI can make robots safer to work alongside humans by enabling them to react to changing environments.
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Data Security: Blockchain can safeguard sensitive data and prevent tampering, critical in manufacturing settings.
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Supply Chain Transparency: Blockchain can provide transparency in the supply chain, ensuring quality control and traceability.
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Industry 4.0 Adoption: As Industry 4.0 becomes more prevalent, the synergy of AI, Block chain, and robotics becomes imperative.
The primary objective of this study is to explore the applications of AI and Blockchain in industrial robotics with a focus on achieving the following goals: Assess the impact of AI on industrial robots in terms of automation,adaptive learning, and predictive maintenance ,Evaluate how Block chain technology can enhance data security, traceability, and trust in robotic applications, Identify real-world use cases where AI and Blockchain have been successfully integrated into industrial robotics, Analyze the potential challenges and limitations of implementing these technologies in industrial settings, Provide insights into the future trends and innovations in AI and Blockchain within the field of industrial robotics.
The topics covered in this chapter mainly focus on fundamentals of AI and Blockchain for the beginners as well as advanced topics like Machine learning for robot perception and object recognition, AI-driven decision-making and autonomous robotic systems, Predictive maintenance and failure detection using AI, Human-robot collaboration and safety improvements through AI, Blockchain in Industrial Robotics: Securing robot control systems and data using Blockchain, Supply chain management and provenance tracking through Blockchain, Ensuring the integrity of robotic process data, Decentralized control and coordination of robotic networks using Block chain. Thus, the integration of AI and Blockchain in industrial robotics holds immense promise for transforming manufacturing and related industries (Turjman F.,2021).This chapter aims to provide a comprehensive understanding of their applications, benefits, and challenges, paving the way for more informed decisions in adopting these technologies for improved industrial automation and efficiency.
TopArtificial Intelligence
Artificial intelligence (AI) technology seeks to imitate human intelligence or offer a logical approach to problem-solving so that it may independently make decisions and carry out activities. The ability of machines to accomplish things cognitively has led to a paradigm-shifting approach in the commercial world (Al-Fuqaha, A.,2019). The concept of AI dates back to ancient times when philosophers and inventors were intrigued by the possibility of creating artificial beings with human-like intelligence. However, the modern development of AI began in the mid-20th century. AI's salient characteristics include the following: Enhancements in data management capabilities, data personalization, data-centric predictive analysis, reduction of development errors, real-time or immediate support, and data mining. Despite all the excitement around AI, a number of significant obstacles prohibit firms from deploying AI widely. These difficulties include:
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The lack of computing or data processing capacity necessary for an AI implementation;
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The lack of talent to work on AI projects; and
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The unreliability of AI outputs.