Revolutionizing the Manufacturing Industry with Industrial Artificial Intelligence
Industrial Artificial Intelligence in Industry 4.0 - Systematic Review, Challenges and Outlook
Industry 4.0 is the term used to describe the fourth industrial revolution, which is characterized by the integration of digital technologies, such as cloud computing, big data, internet of things, and artificial intelligence (AI), into the industrial processes and systems. Industry 4.0 aims to achieve higher levels of efficiency, productivity, quality, and innovation, as well as to create new business models and value propositions.
AI is one of the key enablers of Industry 4.0, as it can provide intelligent solutions for various industrial challenges, such as process optimization, predictive maintenance, quality control, anomaly detection, fault diagnosis, and decision support. AI can also enable new capabilities, such as autonomous systems, human-machine collaboration, and adaptive learning.
However, applying AI in the industrial domain is not a trivial task, as it requires addressing several technical and non-technical challenges, such as data availability and quality, interoperability and standardization, scalability and robustness, explain ability and trustworthiness, security and privacy, ethical and social implications, and human factors.
In this blog post, we present a systematic review of the state-of-the-art research on industrial AI in Industry 4.0. We identify the main application areas, methods, tools, and frameworks that have been proposed and implemented in various industrial sectors. We also discuss the main challenges and limitations that hinder the adoption and deployment of industrial AI solutions. Finally, we provide an outlook on the future directions and opportunities for industrial AI research and development.
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