Inhalt

Abstract:

Enterprise Resource Planning systems (ERP systems) are part of the basic infrastructure of both medium-sized enterprises and globally operating corporations. In the corporate environment, they serve as the central application systems for managing business processes. As the central control unit and “memory” of a company, ERP systems support operational workflows and perform integration tasks across all departments – from sales and procurement to production and accounting.
Technological developments over the past decade have created new automation and application possibilities for ERP systems in companies. At the same time, these innovations impose changing requirements on users. The Internet of Things (IoT) enables the use of sensor data for decisions and transactions. To achieve this, data must be collected, transmitted, and transformed. Methods of Artificial Intelligence (AI) can assist users in maintaining data within ERP systems or fully automate these tasks. The user’s role shifts from data maintenance to workflow creation and supervision.
This CLASSIC vhb course addresses this changing competency profile and the corresponding demand for qualified professionals in this field, focusing on central enterprise application systems (ERP systems). Accompanied by theoretical foundations, the course provides participants with a learning environment that allows them to deepen their knowledge independently and consolidate theoretical concepts through practical experience. In the subsequent case studies on the Internet of Things and Artificial Intelligence, participants have the opportunity to explore current topics in the context of digital transformation in business environments.
The IoT case study demonstrates the technical foundations required in a production environment to digitally connect machines and materials with enterprise application systems without media discontinuity. With an IoT infrastructure, planning-relevant machine data such as machine running times, downtime, and scrap rates can be automatically reported directly from the shop floor to ERP systems. Using up-to-date and accurate data points, business processes can be improved. In the case study, Microsoft Azure and a Raspberry Pi simulator are used as core components to understand the basic architecture of IoT solutions and to demonstrate how this data can be integrated into an ERP system.
The case studies on Artificial Intelligence provide students with an initial insight into the possibilities of AI in connection with ERP systems. In this context, machine learning models are used for document and object recognition. The extracted data is transformed and used to trigger actions within the ERP system. In this way, students create an automated pipeline from a document or image to the ERP system.
The course does not require specific IT or programming skills. However, it follows a constructivist approach and requires working with standard software tools, which are fully provided within the course.

Gliederung:

• ERP Systems
• Case Study: Internet of Things
• Case Studies: Artificial Intelligence
  
  

Detaillierter Inhalt:

Assessment:
Term paper consisting of a practical project:

• In the ERP system (25%)
• On the Internet of Things case study (25%)
• On an Artificial Intelligence case study (25%)
• As well as tests on theoretical foundations (25%) linked to practical application

Access to the ERP system is provided via VPN software and login credentials. Participants must install the VPN software on the computers provided.
Further information about the assessment can be found in the course environment.

Lern-/Qualifikationsziele:

After successful completion of the module, learners will be able to:

• Identify structural characteristics and functionalities of ERP systems and compare individual ERP systems based on these criteria.
• Apply ERP systems for business process execution.
• Assign digital task carriers purposefully to business tasks.
•  Describe and exemplarily implement a basic architecture for integrating sensor data into an ERP system in the context of the Internet of Things.
• Describe and exemplarily implement a basic architecture for integrating Artificial Intelligence into ERP systems.

Lehrveranstaltungstyp:

Virtuelle Vorlesung

Interaktionsformen mit Betreuer/in:

Kooperation Lerner/Betreuer bei der Aufgabenbearbeitung, Video-/Webkonferenz, E-Mail

Interaktionsformen mit Mitlernenden:

Video-/Webkonferenz, Gemeinsame Aufgabenbearbeitung, E-Mail, Forum

Kursdemo:

zur Kursdemo

Nutzung

Kurs ist konzipiert für:

University of Applied Sciences Würzburg-Schweinfurt:

• Bachelor Wirtschaftsingenieurwesen
• Bachelor Business and Engineering

University of Bamberg:

• Bachelor BWL
  
  

Formale Voraussetzungen:

Enrolling in the course via the CLASSIC vhb portal of the Virtuelle Hochschule Bayern (vhb)

Erforderliche Vorkenntnisse:

none

Hinweise zur Nutzung:

Other/external users (subject to payment) can only use the course with restrictions. Questions will be answered by the course supervisor (Johannes Beckert) and the course provider (Prof. Dr. Dobhan).

Kursumsetzung (verwendete Medien):

-

Erforderliche Technik:

-

Nutzungsentgelte:

für andere Personen als (reguläre) Studenten der vhb Trägerhochschulen nach Maßgabe der Benutzungs- und Entgeltordnung der vhb

Rechte hinsichtlich des Kursmaterials:

-

Verantwortlich

Anbieterhochschule:

TH Würzburg-Schweinfurt (THWS)

Anbieter:

Prof. Dr. Alexander Dobhan

Johannes Beckert

Autoren:

Karl-Heinz Gerholz

Alexander Dobhan

Johannes Beckert

Betreuer:

Johannes Beckert

Prüfung

Course examination

Art der Prüfung:

Studienarbeit

Bemerkung:

Practical elaboration in the system (50 %) & case studies (50 %) (more information in the course)

Prüfer:

Prof. Dr.  Alexander Dobhan

Prüfungsanmeldung erforderlich:

ja

Anmeldeverfahren:

Further information about the exam registration will be published inside the course.

Prüfungsanmeldefrist:

–

Prüfungsabmeldefrist:

–

Kapazität:

–

Prüfungsdatum:

–

Prüfungszeitraum:

–

Prüfungsdauer:

–

Prüfungsort:

–

Zuständiges Prüfungsamt:

–

Zugelassene Hilfsmittel:

Examination office of the students' home university

Formale Voraussetzungen für die Prüfungsteilnahme:

Enrolling in the course via the vhb and registration for the exam

Inhaltliche Voraussetzungen für die Prüfungsteilnahme:

Course content

Zertifikat:

Ja (Certificate (graded))

Anerkennung:

–