The Specific Ways Industrial Sensor Data Breaks ML Pipelines — and How to Design Around Them

Machine learning engineers coming to industrial AIoT from consumer or enterprise software backgrounds tend to encounter the same category of pipeline failure in their first real industrial deployment. The system trains correctly. The evaluation metrics are solid. The staging environment produces the expected results. And then the production data starts flowing and the pipeline behaves in ways that the design did not account for. The failures have a common structure: they are caused by…