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AI is transforming manufacturing. But what is hype, and what are meaningful trends?

We share our hands-on knowledge and real-world experiences.

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Introducing the Manufacturing Analytics System

Does your factory collect lots of data that finds no use? It doesn’t have to be like that. EthonAI introduces a new category of manufacturing software: The Manufacturing Analytics System.
Insights
Knowledge
Material Flow Analysis
Products
Root Cause Analysis
Technology
Visual Quality Inspection
The effect of unmeasured root causes in problem-solving

Even with incomplete data, a robust root cause analysis algorithm can find actionable insights to improve your production.
Deploying a Manufacturing Analytics System: On-premises vs. cloud-based solutions

We discuss key aspects to consider when deciding how to deploy a Manufacturing Analytics System.
How modern data analytics enables better decision-making

AI’s potential in decision-making is still underutilized despite impressive advancements in other areas.
A story of why causal AI is necessary for root cause analysis in manufacturing

Explore why causal AI is needed for understanding the underlying cause-and-effect relationships in a production process.
Process Mining: A new take on material flow analysis in manufacturing

Explore how process mining is the new standard for material flow analysis in manufacturing.
What are distributional shifts and why do they matter in industrial applications?

Explore how distributional shifts can deteriorate your ML models’ performance
Industrial anomaly detection: Using only defect-free images to train your inspection model

Why visual inspection should rely on approaches that do not require images of defective products for training.
A photo of a forest, taken from ground level showing tree trunks
A terrible idea: Using Random Forest for root cause analysis in manufacturing

Explore the limitations of Random Forests and the effectiveness of graph-based algorithms for root cause analysis in manufacturing.
Filled beverage bottles on a conveyor belt of a bottling plant
AI is changing how expert knowledge is used in manufacturing

AI is expected to take over an essential role in troubleshooting complex manufacturing problems. To do so effectively, it will need to be fed with all the expert knowledge we can get.