Experience:
Bachelor- / Masterthesis
Accelerating business to improve the lives of people. This is our purpose statement and encapsulates what we enthusiastically do every day. We integrate our customers IT systems to make sure that the right data is at the right place at the right time when they digitalize their processes. Companies need their systems to talk to each other to ensure that cars roll off the factory line, that everyone receives their payments on time, and that you can buy what you need from a supermarket.
Our success story began in, when we helped the German automotive industry to digitalize their paper-based supply chains. Today, SEEBURGER is a leading global B2B software provider with more than 1, #businessaccelerators in 15 countries worldwide and over 10, satisfied customers that rely on our innovative solutions.
Bachelor Thesis / Master Thesis
Process Mining Demonstration System
Motivation
Process Mining is used for the visualization and analysis of business processes and is based on the analysis of event logs. These contain information about the relationship and chronology of individual process steps of an IT system. Process Mining could be a valuable extension for the monitoring of the SEEBURGER BIS Integration Suite in the future. In this thesis, a technology demonstration system is to be created and evaluated on the basis of the pm4py framework from the Frauenhofer Institute.
Objectives
1. Evaluation basis for further investments in the topic of Process Mining at SEEBURGER AG
2. Evaluation of the benefits of process mining for business integration use cases
3. Evaluation of the maturity level of available methods and software components
4. Basics for the evaluation of the effort for the implementation of a
5. Process Mining extension for SEEBURGER BIS Monitoring
Tasks
1. Theoretical Part
6. Presentation of the basic functionality of a process mining system
7. Market overview of open source components and commercial systems
8. Use Cases in the area of Business Integration
9. Selection of suitable analysis and visualization methods
10. Analysis of the SEEBURGER Business Integration Suite with respect to necessary extensions for data generation, analysis and visualization
2. Practical Part
11. Development of a prototype based on the pm4py framework
12. Provision/generation of representative data (event log)
13. Implementation of suitable analysis methods
14. Implementation of the required visualization components
15. Demonstration of selected use cases
Prerequisites
16. Python
17. Java
Advantageous
18. Petri Nets
19. Mining Algorithms
20. Statistical Methods
Location: Bretten and/or Karlsruhe