Bringing Data Analytics and ML to the Shop Floor for Better Process Performance

Cura, M. - Presenter, Optimistik

Machine Learning tools and algorithms are continuously evolving and provide new opportunities to support and augment the capabilities of staff in the plant. Even though, several challenges need to be overcome to achieve that goal:

- Continuous Data collection from multiple and heterogenous sources to provide the required data streams.

- Data structuration and combination to provide meaningful and reliable process information.

- Integrate business expertise based on process modeling to enrich the information available.

- Provide operational teams and process experts with tools, leveraging on state of the arts Machine Learning algorithms, properly suited to answer specific and recurring time-consuming business cases and usages.

We will go through the different steps required to succeed in this kind of project and share the experience acquired in various process industries (chemicals, food and beverage, metallurgy…).

Although technical solutions can support this process, a proper approach focusing on teams needs and usages, autonomy and agility is required to bring a sustainable and operational solution.


This paper has an Extended Abstract file available; you must purchase the conference proceedings to access it.


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