imPACts

Industrial Methods for Process Analytical Chemistry

Motivation

Regardless of whether you are producing drugs, petroleum products or beer: in chemical and biochemical processes in industry, you always want to know as precisely as possible what is going on in the reactors. Often this means interrupting the process, taking a sample and analyzing it in the laboratory, which is very cumbersome in many cases. In addition to accuracy, speed also plays a decisive role. However, the result of the sample taken is often only obtained after hours. If this then indicates deficiencies, it means that in the worst case the entire production is unusable.

Exactly here, process analytics is used: immediate, regulatory intervention in the process enables shorter process times and the saving of raw materials and energy. In addition, rejects and waste can be reduced and - by eliminating the need for hazardous sampling - health and environmental hazards can also be avoided. And last but not least, this ensures optimum product quality at all times.

Process analytics thus contributes to a wide range of cost savings for companies and thus to securing competitiveness at the industrial location of Austria!

Research Topcis

  • Generating knowledge about chemical production processes through novel analytics, multivariate data analysis, fluid dynamic simulations and mechanistic modelling.
  • Development of advanced optical and MEMS based sensor systems for ultra-sensitive, fast and spatially resolved measurement of chemical and physical properties of the sample.
  • Transfer of the methodological approaches to industrial partners for application in different - but similar - production processes.

Goals/Mission

  • Applicable process analytics for industrial production in various industries
  • New measurement technology for optimum information retrieval from processes
  • Analysis at elementary and molecular level
  • Description of the condition with mathematical models
  • Usability of mathematical models in industry (Computational Model Life-Cycle Management - CMLCM)
  • Tools for improved process understanding
  • Knowledge discovery and transfer to industry
  • Process optimization through modern analytical methods

Project Data

Duration: 01.09.2014 - 31.08.2018
Budget: 6,7 Mio. € (thereof 3,7 Mio € company contributions and 3 Mio. € funding contribution)
Partners:

Scientific Partner:

  • RECENDT GmbH (Coordinator)
  • Software Competence Center Hagenberg
  • Fuzzy Logic Laboratory Linz / Hagenberg
  • JKU - Institute of Applied Physics
  • JKU - Institute for Microelectronics and Microsensors
  • Wood - Kompetenzzentrum Holz
  • TU Vienna - Institute of Process Engineering, Environmental Technology and Technical Biosciences
  • TU Vienna - Institute of Chemical Technologies and Analytics

Company Partners:

  • Brau Union Österreich AG
  • DPx Fine Chemicals Austria
  • EXPUTEC GmbH
  • Kelheim Fibres GmbH
  • Keysight Technologies GmbH
  • Kraiburg Austria GmbH & Co. KG
  • Lenzing AG
  • Metadynea Austria GmbH
  • OMV
  • Sandoz GmbH
  • voestalpine Stahl GmbH

Funding partner: FFG, COMET, K-Projects - 5th Call

Project Website

https://www.k-pac.at/en

Contact

Bernhard Freudenthaler

Freudenthaler Bernhard

Area Manager Data Science
Phone: +43 50 343 850

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