Machine learning in manufacturing, explained properly
Definition-first entries, an annual adoption report, and a use-case library: written for engineers, with every figure attributed and vendor claims labeled.
Start with the fundamentals
What machine learning means on a factory floor: how models learn from process and machine data, the four famil…
FoundationsWhy unsupervised machine learning fits factories: no labeled failures needed, trains on normal production, fin…
ApplicationsMachine-learning approaches to predictive maintenance, the results plants report, and where PdM stops being th…
ApplicationsHow machine learning attacks scrap, quality drift and setpoints: root-cause discovery, predictive quality, gol…
FoundationsWhat generative AI actually does in factories in 2026 (the language layer on top of industrial ML) and where…
FoundationsWhat a manufacturing digital twin actually is, the maturity ladder from data model to simulation, and when the…
The 2026 Adoption Report
Ten numbered, evidence-backed insights (market size, use-case shares, the expertise bottleneck, the deployment profile that survives) with an xlsx data pack carrying every figure and its source. Read it →
Twelve use cases that pay
From scrap root-cause discovery (up to −58%, vendor-reported) to predictive maintenance (€270M/yr at Renault): each linked to the entry explaining the mechanism. Browse the library →
Every number on this site: in one sourced spreadsheet.
The $43.6B market math, use-case shares, adoption barriers and published deployment results, with the source column intact. Ready to paste straight into your business case.