Inhalt

[ 479PTAMSPM24 ] KV Smart Production Management

Versionsauswahl
Workload Education level Study areas Responsible person Hours per week Coordinating university
3 ECTS M2 - Master's programme 2. year (*)Kunststofftechnik Jürgen Miethlinger 2 hpw Johannes Kepler University Linz
Detailed information
Original study plan Master's programme Polymer Engineering and Science (PES) 2025W
Learning Outcomes
Competences
students are able to assess and optimize the overall production efficiency of an entire polymer processing site, considering the individual units and workflows altogether. This includes the evaluation of key performance indicators for product quality and process capability, economic considerations, as well as production management.
Skills Knowledge
Apply statistical methods for product quality and process capability analysis using real industrial production data (k3)

Analyze and evaluate the overall equipment effectiveness (OOE) (k4, k5)

Apply the six big losses method to identify reasons for reduced OOE using real industrial production data (k4)

Methods to optimize entire production sites for polymer processing

Digitalization concepts for smart production management

Target system of industrial production

Key performance indicators for product quality and process capability

Key performance indicators for production management

Selected examples of smart manufacturing components

Criteria for evaluation Final project report and written examination
Methods Lectures about selected topics based on industry experience; project work and presentations
Language English
Study material Basic knowledge of Software Minitab is strongly recommended. This can be grasped in courses "Optimization Methods in Polymer Processing" or "KV Angewandte Statistik fuer IngenieurInnen (only German).
Changing subject? No
Further information The course provides an insight into production optimization and management, taking digitalization concepts into account. This couse is held by an experienced industry expert.
On-site course
Maximum number of participants 35
Assignment procedure Assignment according to priority