Process mining in production at the door factory

Supporting production and identifying potential with process transparency & real-time information

Process mining was used to create a digital image of the entire production process and thus generate transparency about the process sequences. The real-time analyses generated – including in the areas of system performance, master data, rejects and idle times – were used to identify weak points and highlight the potential for optimization.

Thanks to Rothbaum’s process mining and operations expertise, we quickly created the process transparency that helps us to optimize waiting and throughput times.”
Harald Valentin, Head of Production Planning

Prüm door works

Prüm Türenwerke GmbH, as part of the Swiss Arbonia AG, is a manufacturer of interior doors and door frames.
840 employees generate sales of over 150 million euros.
Up to 25 thousand doors are manufactured and packaged each week in its production facility in Weinsheim.

Services

Development of a process mining pilot in the production environment
Tailor-made analyses to increase transparency and tap optimization potential
Demonstration of fields of application for EMS functionalities in terms of automation and alerting

Results

Creation of production performance dashboards and master data synchronization
Analysis of delivery and transport times with development of a use case for automatic prioritization of time-critical orders
Scrap monitoring to prepare for automatic scrap increase detection in order to identify machine problems at an early stage

Occurrence and timing of loss reports. By monitoring the scrap per system, even the smallest increases can be detected in future and action taken at an early stage to proactively prevent scrap. — By monitoring the scrap per system, even the smallest increases can be detected in future and action taken at an early stage to proactively prevent scrap.

Project description: Process transparency for Prüm Türwerke

Prüm operates a very complex, multi-stage production process in order to meet the requirements of product diversity. Although the processing steps on the machines are largely automated, all other steps are carried out manually. The idle and transport times significantly exceed the pure processing times. Prüm stores the feedback data from the machines in its own system in order to answer queries and carry out analyses. Due to the high level of complexity, classic analysis options are limited. The possible applications of process mining should therefore be investigated in a pilot project.

Procedure

Rothbaum created a Celonis data model in close collaboration with experts from production. In joint walkthroughs, weak points in the process were identified and use cases developed. Finally, the results were summarized. Based on these, the decision was made to introduce the software.

Results

Despite major data challenges, together we succeeded in creating a valid digital image of the production process. Based on this data model, it was possible to develop analyses in the areas of system performance, target/actual path comparison and the review of replenishment times. These analyses form the basis for answering the most important recurring questions quickly and effectively.

In the further course of the project, new findings with enormous potential were generated with the loss analysis per system and a delivery time analysis. This can be used in the future, for example, to reduce the idle times of time-critical orders determined in real time by means of rule- or AI-based prioritization – and thus better meet delivery deadlines.

Rothbaum-Success-Story-Pruem-Tuerenwerk-Process-Mining

Portrait of Clemens Wolf, Manager at Rothbaum.

Dr. Clemens Wolf

Head of Digital Operations

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