Syllabus

Title
1270 Process Implementation
Instructors
Dina Sayed Bayomie Sobh, M.Sc.
Contact details
  • Type
    PI
  • Weekly hours
    2
  • Language of instruction
    Englisch
Registration
09/04/18 to 11/24/18
Registration via LPIS
Notes to the course
Subject(s) Bachelor Programs
Dates
Day Date Time Room
Tuesday 11/27/18 12:00 PM - 02:30 PM TC.3.06
Thursday 11/29/18 02:00 PM - 04:30 PM D4.0.039
Tuesday 12/04/18 09:00 AM - 11:30 AM EA.5.034
Thursday 12/06/18 09:00 AM - 11:30 AM TC.5.12
Tuesday 12/11/18 09:00 AM - 11:30 AM TC.5.12
Thursday 12/13/18 02:00 PM - 04:30 PM D2.0.326
Tuesday 12/18/18 02:00 PM - 04:30 PM D2.0.374
Thursday 12/20/18 09:00 AM - 11:30 AM TC.5.12
Thursday 01/10/19 09:00 AM - 11:30 AM TC.0.02 Red Bull

Contents

The course covers the main concepts spanning over the topics of business process automation and process mining. The treated arguments pertain: the characteristics and functionalities of Business Process Management Systems (BPMSs); the implementation, deployment and execution of business process models on BPMSs; the formal notions and fundamental properties of the executable semantics of models grounded in Petri nets; the fundamental algorithms of process mining, with a particular focus on the automated discovery of processes out of event logs.

Learning outcomes

Successful students will be able to put business process models into action by their enactment through IT systems. Furthermore, they will understand the mechanisms that allow the machine-based discovery of process models out of recorded process executions. 

Attendance requirements

According to the examination regulation full attendance is intended for a PI.

Teaching/learning method(s)

The course is designed as a mixture of lecture with accompanying project assignments.

Both theoretical contents and hands-on sessions will be held. Tools used in the course will include the Bonita Business Process Management System (https://www.bonitasoft.com/), the WoPeD workflow and Petri net modeler and analyzer (http://woped.dhbw-karlsruhe.de/woped/), the ProM process mining toolkit (http://www.promtools.org), and Celonis process mining platform (https://www.celonis.com/).

A Virtual Machine based on the VirtualBox platform (https://www.virtualbox.org/) will be distributed with all the necessary software pre-installed.

Assessment

The final grade is assigned on the basis of the following proportions:
60% - written exam
20% - group assignment on process implementation
20% - group assignment on process mining

Prerequisites for participation and waiting lists

Participants are expected to be familiar with the content of the course Business Process Management. Generally, it is assumed that the concepts described in Dumas et al.: Fundamentals of Business Process Management, 2nd edition, Springer 2018, are understood.

Readings

1 Author: Marlon Dumas, Marcello La Rosa, Jan Mendling, Hajo A. Reijers
Title:

Fundamentals of Business Process Management


Publisher: Springer
Edition: 2nd
Remarks: http://fundamentals-of-bpm.org/
Year: 2018
2 Author: Wil M.P. van der Aalst
Title:

Process Mining - Data Science in Action


Publisher: Springer
Edition: 2nd
Year: 2016

Recommended previous knowledge and skills

It is required that the “Process Innovation” course has been already regularly attended and that the following notions are already acquired:

  • Business Process Management (BPM), its initiative, goals, and life-cycle;
  • Business process identification, discovery, analysis, and re-design phases;
  • Business process modeling using BPMN.

Basic notions of set theory are recommended.

Availability of lecturer(s)

Please contact the lecturer via e-mail to fix an appointment.

Last edited: 2018-06-25



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