In last week’s Process Mining Café, Stefanie Rinderle-Ma from the Technical University of Munich showed us how their open source process engine steers production processes. A nice side-effect of their system is that it collects data that can be used for process mining again!

We realized that many standard process mining terms could be misleading in manufacturing. We also talked about the power of domain knowledge, how process mining can leverage sensor data, and realistic expectations for automation.

If you missed the live broadcast or want to re-watch the café, you can now watch the recording here.

Thanks again to Steffi and to all of you for joining us!

Links

Here are the links that we mentioned during the session:

• Open-source process engine CPEE
• Case study at Veco shows 50% cycle time reduction for their production process (see also Joris’ presentation at Process Mining Camp 2015)
• Process mining at Wacker has yielded 17 Million Euros savings per year by reducing 1 hour of process time
• Lufthansa has combined process mining with the Theory of Constraints to optimize their parts repair process
• Open PhD positions in Steffi’s group (apply by January 9th, 2022)

Our running list of potentially ambiguous words ended up at:

• Spaghetti diagrams (it’s the name of a different technique)
• Process (be careful, people might talk about chemical or other non-discrete processes!)
• Instance vs. batch
• Process automation (better use orchestration)
• Robotic process automation (which kinds of robots?)
• …

Contact us via cafe@fluxicon.com if you can think of other examples for misleading terminology, or if you have questions or suggestions for the café, anytime.

Anne Rozinat

Market, customers, and everything else

• anne@fluxicon.com
• annerozinat
• @arozinat

Anne knows how to mine a process like no other. She has conducted a large number of process mining projects with companies such as Philips Healthcare, Océ, ASML, Philips Consumer Lifestyle, and many others.