AI and python articles
This two-part, online article, "Artificial intelligence in automation" by Christian Vilsbeck of Phoenix Contact, covers AI, ML and deep learning, and how they can be used in manufacturing. They're two of several articles in the PLCNext Community's business lounge, which also has articles on Python programming, cloud computing and other topics.
ML for brewery control
This one-hour video, "Using ML to improve process control and costs" presented by Adam Spunberg, details a case study at AbinBev's brewery in New Jersey, and shows how its users employed machine learning (ML) to improve process control, and minimize downtime and costs. The brewery and its staff used an ML-based predictive approach to help determine when a failure will occur, and determined the optimum schedule for preventive maintenance.
Wiser water with AI
This two-part, online article, "AI basics for advanced, water-wise utilities" by Emma Weisbord, IWA emerging water leader and digital water consultant, covers AI fundamentals, machine learning and how they can be applied in water applications.
AI for automation video
This three-minute video, "What is AI? For industrial automation," by Walker Reynolds of Intellic Integration, provides a quick and concise explanation of the basic features of artificial intelligence as it relates to industrial automation. It's also accompanied by his 12-minute video, "The future of industrial controls," which puts many AI and other issues in the context of where controls came from and where they're going.
ML for organic synthesis
This five-minute video, "Using machine learning in process manufacturing," shows how ML can be applied to a manufacturing workflow for an organic synthesis process. It details how the process uses Altair Knowledge Studio software for AI and ML combination with Altair Panopticon platform for user-driven monitoring of real-time data.
Quick guide to ML and AI
This webpage, "Machine learning and AI in manufacturing: a quick guide to the fundamentals," shows how to begin selecting the right AI solution to address specific manufacturing challenges by using the "Industrial AI quadrant." It also details how to implement an ML strategy to improve predictive quality and yield, and covers supervised and unsupervised ML, data preparation and benefits. There's also a link to Seebo's larger "Manufacturer’s guide to selecting the right industrial AI solution."
ML tutorial with python
This almost 50-minute video, "Python machine learning tutorial (data science)," introduces ML and its basic tools, shows how to solve a real-world problem, and prepares users to learn more advanced skills.
APC and analytics
This webpage, "Advanced process control and analytics (APCA): new tools revolutionize data analysis, reduce modeling effort," bridges the gap between APC and model-predictive control and the algorithms and AI they're beginning to integrate. The page also links to APC applications in a paper mill, for mine ventilation and for ship fuel consumption. It's at https://new.abb.com/control-systems/features/advanced-process-control-and-analytics-in-industrial-automation
Goals to control AI
In this online article, "Can we control artificial intelligence?" by longtime Control columnist Béla Lipták, he reports the first step in controlling powerful AI is to define its goals.