"Machine Learning and Artificial Intelligence Applications " discusses strategies for applying machine learning (ML) and artificial intelligence (AI) capabilities to various manufacturing processes, that can help improve manufacturing processes throughout a product’s lifecycle, including monitoring raw material use, optimizing production processes and supply chain logistics, and improving the product delivery and service for end users. Manufacturers can use machine learning libraries to gain valuable insights from data. Developing ML models requires the use of a programming language, such as Python, and an understanding of data analysis. Leveraging ML and AI can also vastly improve the quality of manufactured products.
- Describe machine learning and artificial intelligence
- Distinguish between supervised, unsupervised, and reinforcement machine learning
- Describe how manufacturers can implement machine learning models
- Describe how machine learning can improve raw material quality
- Describe how machine learning and AI enhance product design
- Describe how machine learning and AI enhance process automation
- Describe how machine learning and AI can improve predictive maintenance
- Describe how machine learning and AI can improve quality control processes
- Explain how machine learning and AI can improve supply chain and logistics management
- Describe various ways machine learning and AI can improve safety for manufacturers.
- Recommended for new & experienced leaders and managers preparing for the Industry 4.0.
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