2011
DOI: 10.1002/masy.201000064
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Industrial Polymerization Monitoring

Abstract: Summary: Monitoring and control of polymerization reactions is essential for high process safety, high product quality and competitive production costs. Ideally the entire process chain is regarded, starting with raw material analysis and the polymerization reaction up to the measurement of polymer‐ and application‐ properties. Process data like temperatures and pressures can be used to monitor reaction trajectories in a cost effective way, e.g. using calorimetric evaluations. Additional sensors can provide ch… Show more

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Cited by 7 publications
(4 citation statements)
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“…To that goal spectroscopic techniques have been widely recognized as relevant tools . Raman spectroscopy had already been reported for monitoring AA polymerization in aqueous solution . Taking into account that Raman spectroscopy was convenient for both investigated processes, we selected this technique for in situ monitoring of polymerization during demonstration experiments.…”
Section: Resultsmentioning
confidence: 99%
“…To that goal spectroscopic techniques have been widely recognized as relevant tools . Raman spectroscopy had already been reported for monitoring AA polymerization in aqueous solution . Taking into account that Raman spectroscopy was convenient for both investigated processes, we selected this technique for in situ monitoring of polymerization during demonstration experiments.…”
Section: Resultsmentioning
confidence: 99%
“…Consequently, it is of primary importance to develop experimental techniques for in situ monitoring of polymerization reactions both at lab‐scale and at pilot‐scale so as to ensure appropriate knowledge about reaction kinetics in experimental conditions as close as possible to industrial installations. Spectroscopic techniques have a great potential in that context because they allow fast data acquisition as well as coupling with other experimental measurements like mechanical or rheological properties . We have recently demonstrated that Raman spectroscopy was an efficient tool for in situ monitoring of free radical polymerization of acrylic acid in aqueous solution that could be coupled with rheological measurements in order to get further insights about relations between monomer conversion and viscosity .…”
Section: Introductionmentioning
confidence: 99%
“…This requires implementation of real-time model-based predictive control, which, in recent years, has received a significant boost through progress in computing, modeling, sensor technologies, and chemoinformatics. 1 3 However, significant challenges remain in implementing model-based predictive controllers, especially in situations when product quality and/or process parameters are difficult to observe directly and require soft sensors in addition to hard sensors. Here, we define a soft sensor as a model that receives hard sensor measurements and computes parameter(s) enabling the determination of process state variables.…”
Section: Introductionmentioning
confidence: 99%
“…Understanding process behavior, implemented in a robust model, enables the maximum and safe utilization of the heating/cooling capacity of plants, and sensing and characterizing product quality during the manufacturing process enables real-time optimization of process parameters that maximize quality and throughput simultaneously. This requires implementation of real-time model-based predictive control, which, in recent years, has received a significant boost through progress in computing, modeling, sensor technologies, and chemoinformatics. However, significant challenges remain in implementing model-based predictive controllers, especially in situations when product quality and/or process parameters are difficult to observe directly and require soft sensors in addition to hard sensors. Here, we define a soft sensor as a model that receives hard sensor measurements and computes parameter(s) enabling the determination of process state variables.…”
Section: Introductionmentioning
confidence: 99%