SelVliesPro - Development of self-learning production systems/ process control systems regarding a continous production line for processing (recycled) high-performance fibres

Problem setting

The processing of recycled high-performance fibres into organo sheets based on nonwovens is an response to the increasingly pressing question of the use of carbon fibre waste, especially when considering the imminent classification of carbon fibre-reinforced plastics (CFRP) as "hazardous waste" and the associated ban on landfill.

The recycling of carbon fibers on the level of high-performance materials can only be established in the real economy with closed technological process chains, high reproducibility and economic efficiency. Particularly high requirements arise when used in the automotive and aviation industries. For this purpose, it is important to optimize and design the processes for industrial use.

Objective & Approach

Therefore, the SelVliesPro project is pursuing the integration of a big data approach into an existing production line for processing recycled high-performance fibres. Data mining methods are used to perform an analysis of the data recorded by the big data approach and reflect the analysis results back to the production line. Thus, the scientific and technical goal is to establish a cyber-physical production system.

Cyber-physical systems are a core element of Industry 4.0 and describe the dynamic networking of the physical world, i. e. the specific production plant, and a virtual (cyber) image based on suitable models. With the help of the cyber-physical system, machine, operating or environmental data with sufficient temporal and spatial resolution are collected and continuously fed into a virtual model to calculate optimized strategies using innovative simulation approaches and data analytics. This data is made available to employees of different target groups in a suitable form for decision support or directly integrated into an automated plant control system.


  • STFI: Sächsisches Textilforschungsinstitut e.V.

  • Institute of Machine Tools and Production Technology (IWF), TU Braunschweig

  • Hochschule Hof

  • MSA Deutschland GmbH


Industry 4.0, cyber-physical systems, self-learning manufacturing systems


02/2018 until 01/2021


Marc-André Filz


Federal Ministry of Education and Research (BMBF)


  last changed 16.01.2018
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