We dive into Lean manufacturing and discuss whether data analysis is too far away from the physical processes with Joris Keizers, Minh Chau Nguyen, and Klaus Kühnel.
A core aspect of Lean Manufacturing is that you “walk the GEMBA”: Managers physically visit the production lines to look for waste and opportunities in the process. With process mining you analyze the process based on data, at a remove from the actual manufacturing process.
Together with Joris, Minh Chau, and Klaus, we discuss whether this is a problem and — if so — how it can be overcome.
Fluxicon organizes Process Mining Camp since 2012. It's our favorite part of the year. We look back at the talks from the past nine years and categorize them into industries and use cases.
During the first quarter of 2020, the mortgage provisioning lead time was above the stated limit. Daan shows how only the process analyst and the domain expert together can solve the problem.
We discuss process improvement methodologies and best practices for process improvement with Sudhendu Rai and Daan Jabroer.
When you perform an audit with process mining, you need to be methodical in your approach and tame the complexity by focusing on the right questions.
We talk about audit standards, new definitions of materiality, and research on how auditors assign risk to deviations with Mieke Jans, Jasmine Handler, and Andreas Preslmayer.
Process mining complements productivity management in the digitized industry. Domain knowledge is necessary to generate improvement ideas and multi-disciplinary teams are needed to implement the change.
Gary shows how he got from disparate data sources to an end-to-end process visibility. As a process owner, process mining allows him to analyze his process completely by himself, independently from the IT department.
We talk about where to find data and how to make it available for fresh analyses with Carmen Lasa Gómez, Javier García Algarra, and Gary Bonneau.
How can Artificial Intelligence & Machine Learning improve processes? Robotic Process Automation automates and improves individual tasks but it requires a hybrid intelligence to combine data, algorithms, and people.
We discuss explainability research, multi-agent systems, and responsible data science with Manuela Veloso and Wil van der Aalst.
© 2024 by Fluxicon BV, all rights reserved.
You can read our privacy policy here.
Page created in 14.7 ms.
