Development of a microservice infrastructure for continuous, AI-based process optimisation via an assistance system in injection moulding

The aim of your work is to co-develop a system for process optimisation of the injection moulding process based on artificial intelligence methods.

Process optimisation with Python services based on existing infrastructure | Picture: IKV

Subject of thesis:
The plastic injection moulding process is a complex primary moulding process with a large number of influencing factors, e. g. the machine, the mould or the material. The best way to react to increasing scrap during production is to optimise the setting parameters. Experienced process engineers can thus ensure high production stability in most cases. However, effective and efficient process adjustment depends on many years of professional experience and understanding of the relationships between setting parameters and specific quality variables of the component and process.

The work is related to this research project:
The "Internet of Production" (IoP) cluster of excellence at RWTH Aachen University is an interdisciplinary research project in cooperation with 24 institutes and chairs. Within this framework, the IKV Aachen is researching model-based process optimisation, e. g. of injection moulding, to increase process and component qualities. Among other things, a shorter process preparation time for production or an optimisation of the process during production is targeted in the project.

Objective:
The result of your work is to develop an implemented prototype system for process optimisation of a running injection moulding process via an assistance system based on an existing infrastructure for data acquisition and the use of AI methods, e. g. artificial neural networks.

Your assignment:

For a bachelor thesis you will work on the following tasks:

  • Detailed development of a workflow for human-machine-machine interaction in process optimisation
  • Research, selection and evaluation of infrastructure models
  • Definition of required data transfer objects (DTOS) and interfaces
  • Development of an implementation plan

For a master thesis you will work on the following tasks:

  • Detailed development of a workflow for human-machine-machine interaction in process optimisation
  • Research, selection and evaluation of infrastructure models
  • Definition of required data transfer objects (DTOS) and interfaces
  • Development of an implementation plan
  • Prototypical realisation of the implementation plan and functional validation of the system in the injection moulding pilot plant

Your profile:

  • Technical or technical-scientific studies
  • (Good) understanding of plastic injection moulding available at best
  • Interest in at least one of the topics mentioned: Process optimisation, programming, Python, quality management, plastics processing, artificial intelligence, Industry 4.0
  • Independent and responsible work in addition to supervision
  • Reliability and interest in cross-process contexts
  • Very good written and spoken German and/or English skills

That sounds like you? Does the thesis topic fit exactly or do you even have your own ideas? Of course you can help to shape the exact topic! Please feel free to contact me to arrange a meeting.

Your contact person:
Yannik Lockner, M. Sc. RWTH
Phone: +49 241 80-96264
E-mail: yannik.lockner@ikv.rwth-aachen.de