To prevent spam users, you can only post on this forum after registration, which is by invitation. If you want to post on the forum, please send me a mail (h DOT m DOT w DOT verbeek AT tue DOT nl) and I'll send you an invitation in return for an account.

Data Ingestion and Analysis Strategies for Process Mining in Warehousing

Hello everyone, I am thinking about starting a process mining project on a warehouse operations management application.

The application is multi-warehouse, and each warehouse can have different companies operating within the same physical installation.

In it, we have modeled processes and operations. A process is defined by a sequence of operations.

With the current functionality, we are already generating start and end events for processes, as well as state transition events.

For the operations, we also generate events for each state transition of the same.

We have two Kafka topics where events from both entities are published, where we have a message with metadata and in the body a JSON with information such as process ID, operation ID, event name, client, quantities, references, origin, destination.

I believe we have good quality information to apply process mining. I have two questions:

I understand that to ingest data into a tool like ProM, I would need to build a piece of software to consume the Kafka events and convert them to XES files. am I right or does exist some plugin to consume from kafka and convert to XES ?

Once the data is processed, within ProM, can I analyze the data using different dimensions, for example, to analyze different warehouses separately, or different clients within the same warehouse, or different references? Or, on the contrary, should I separate the data before ingestion?

thanks in advance for your help

Sign In or Register to comment.