Unlocking AI Potential: The Role of A Modern Data Ecosystem

Описание: Smart manufacturers are realizing that industrial AI is only as powerful as the data you provide it. Real-time industrial process data is at the core of effective predictive modeling, and the quality of this data is essential to achieving reliable outcomes. A well-planned data architecture enables intelligent technology to anticipate production failures and provide meaningful recommendations for improved efficiency. This webinar explores what it truly means to build an AI-ready data ecosystem by uncovering common pitfalls and providing solutions you can use to accelerate your plant’s digital maturity.

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Additional Questions:
Q: How can we mitigate issues with low resolution data, for instance Lab data which is often only hourly or bihourly?
A: I think the biggest thing here is that you might need more data, so rather than a few days, you might need weeks or months to help build your model. Another thing is a local soft sensor might help fill the gaps to see how your data shifts and can predict the test result, so if you have PARCmodel doing some PCA models with those can help a lot as well.

In terms of PARCmodel and soft sensors, the model can give a result on a more regular basis, and it output as a tag. You can then feed that value into the AI. So, it can be used as both a quality tool to help maintain quality between testing, but also for AI use cases, it can help bridge that gap in data. Here is a link to soft sensors for some more information: https://www.dataparc.com/soft-sensors/