Case study – Development of a predictive rheology method for misting defects in roller coating

Sector: Printing

Customer type: Group

Service contact: R&D

The Customer encounters difficulties during pilot tests in coating in roll-coating and called on RHEONIS to develop a predictive instrumental approach to the undesirable phenomenon of misting and thus make its formulation process more reliable.

Technique, science and statistics for predictive approaches

In response to this request, RHEONIS implements its knowledge of thermomechanical processes, its scientific and statistical methods and instrumental tools for the study of the properties ofapplication specific.

The stages of the study were therefore as follows:

  1. Site visit and process analysis
  2. Adaptation of instrumental protocols in physical measurement and rheometry
  3. Instrumental study of behavior of customer samples
  4. Exploitation of measurement data and statistical analysis for extraction of discriminating parameters with regard to the misting trend observed by the Client
  5. Conclusions on trends in the appearance of the phenomenon and determination of preliminary windows of acceptability
  6. Operational recommendations for the internalization of methods

Intervention System Gauge

Product & Ingredient 40%
Process & Application 20%
Measurement & Instrumentation 80%
Methods for Industry 60%

A predictive instrumental approach to make the formulation more reliable and to rationalize the pilot tests

The study provided the Client with an instrumental approach based on the measurement of two physical parameters and making it possible to anticipate the risk of misting during pilot application of roll-coating. The approach is parameterized on the Client's observations on a limited sampling and the Client was then able to deploy a systematic approach to refine the windows of acceptability and complete the maps of the influencing factors.

The advantages of predictive approaches

Formulation screening

Limitation of pilot tests

Elucidation of fault/performance influencing factors

Transferable to quality

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Last Updated on April 7, 2022 by Vincent Billot