Publisher's Synopsis
Implement Machine Learning best practices at your own manufacturing facility with the most practical guide on the market
In Practical Applications of AI in Manufacturing, Data Scientist Luke Posey delivers a comprehensive and insightful exploration of the practical steps AI practitioners can take to implement data best practices among machine learning, data collection, and visualization in a manufacturing setting. The author offers readers tested and working code with each observation, showing the ways around and over the unique roadblocks and challenges that exist in the manufacturing space.
With a strong focus on real-world strategies and practical techniques, Practical Applications of AI in Manufacturing walks you through the implementation of artificial intelligence in areas like predictive maintenance, robotics, process control, and quality control. You'll learn the full lifecycle of data projects, from collection and cleaning to modeling and monitoring.
The book also includes:
- An introduction to AI in manufacturing, plus common misconceptions and misapplication
- A comprehensive exploration of common problem spaces - vision, audio, process, and more.
- Practical discussions of process control, including how to prevent breakdowns with tuning and linking quality control data to process control data.
- In-depth examinations of predictive maintenance, including the important differences between predictive and preventive maintenance approaches.
Perfect for engineers working in manufacturing, as well as manufacturing executives and managers, Practical Applications of AI in Manufacturing is an indispensable resource for anyone interested in the applications of advanced data practices to manufacturing environments.
