East Netherlands
AI-based Process Control c/o ARMAC bv
(Geert Postma @ Radboud University)
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AI based predictive maintenance by Royal Eijkelkamp BV & Radbound University
NEED for AI:
It emerged the need a sustainable process control, development and upscaling, in combination with modern sensor based technology, such as NIR sensors. In particular:
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improved process control including fault detection
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process analysis and weaknesses detection
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process optimization in view of sustainability
AI REGIO SOLUTION:
The solution will integrate machine learning and AI routines, possibly in combination with FIWARE or APACHE, in the test facility for process development and upscaling (S/park, Deventer), in order to promote the added value of these machine learning and AI routines in combination with all kinds of sensors for better and more sustainable process control for users of the test facility (SME’s), as well as, for the owners of the test facility.
EXPECTED BENEFITS:
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energy consumption reduction
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more efficient use of feedstock and less waste production
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experience with AI technology in process monitoring for the users of the test facility, as well as the owners
AI-based Process Control c/o ARMAC bv (Geert Postma @ Radboud University)
The experiment is related to the development of a sustainable optimized process control in combination with LCA in the chemistry sector. S/park, Deventer is a test facility for process development and upscaling of the East NL region for SME’s. This test facility is equipped with some basic process monitoring and control technology (sensors, software, etc.).
NEED for AI:
Need of improved process control and industrial automation software by inclusion of:
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machine learning and AI based process monitoring routines
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process analysis and weaknesses detection routines
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routines for Process optimization in view of sustainability
AI REGIO SOLUTION:
The solution will integrate machine learning and AI routines in operational process control and industrial automation software, for improved process monitoring, in order to promote the added value of these machine learning and AI routines in combination with all kinds of sensors for better and more sustainable process control.
EXPECTED BENEFITS:
Improve process monitoring and process efficiency.
AI-based Process Control c/o S/PARK DEVENTER & Radbound University
The experiment is related to the Implementation of machine learning and AI routine-based process control and process analysis software (in view of process sustainability) in operational process control and industrial automation software of ARMAC bv, in order to promote the added value of these machine learning and AI routines for the company and its clients in the region.