A review of artificial intelligence applications in manufacturing operations
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Abstract
Abstract Artificial intelligence (AI) and machine learning (ML) can improve manufacturing efficiency, productivity, and sustainability. However, using AI in manufacturing also presents several challenges, including issues with data acquisition and management, human resources, infrastructure, as well as security risks, trust, and implementation challenges. For example, getting the data needed to train AI models can be difficult for rare events or costly for large datasets that need labeling. AI models can also pose security risks when integrated into industrial control systems. In addition, some industry players may be hesitant to use AI due to a lack of trust or understanding of how it works. Despite these…
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200
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- FWCI
- 38.21
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- 100%
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Authors
4Topics & keywords
Topics
Keywords
- Computer science
- Productivity
- Manufacturing
- Quality (philosophy)
- Process (computing)
- Applications of artificial intelligence
- Risk analysis (engineering)
- Automation
UN Sustainable Development Goals
- Industry, innovation and infrastructure
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