Nouvelles approches de mise en œuvre de la spectroscopie NIR et Raman pour le suivi de la qualité des produits industriels en ligne ou at-line

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1 Nouvelles approches de mise en œuvre de la spectroscopie NIR et Raman pour le suivi de la qualité des produits industriels en ligne ou at-line INDustrial Analyser Technologies SRS, Raman, UV VIS NIR Dr.F Chauchard

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3 CONTINUOUS MANUFACTURING

4 Challenge for Spectroscopy in Industry 4.0 Sample Clear to turbid Solid, powder Properties Chemical physical Production tool Different kind: reaction, mixing, compaction or filling etc Operator not specialist in optics or spectroscopy Data analysis/ recording Better understanding of simulation Close loop Automation (PLC) complience

5 Multipoint and SRS spectroscopy for complex liquid

6 Example of common problem Liquid Solid Liquid+solid creaming Unmixing / sedimentation floculation Unmixing/ coalescence Clog /agglomerates sedimentation

7 Correct product Liquid Solid Liquid+solid If miscible Full dissolution EMULSION : Oil in water (e.g. mayonnaise) Homogeneous repartition without attrition Water in oil (Margarine) Particles in suspension

8 Existing techniques (Mixing) Analysis of mixing and blending : Mainly simulation (eg DynoChem) for selecting : Baffles Blades Speed (rotation) Shape of the Reactor Usually only single point sensor are available Needs : Process Dev. : Generate more knowledge on physical and chemical change. Production : Ensure efficient Scale up and validate optimal mixing time and quality, validate transfer time with continuous processes 8

9 Hyperspectral Imaging / Push Broom HYPERSPECTRAL = CAMERA + SPECTROMETER Each pixel measures a spectrum (Vis/NIR) A standard camera would have generated an image based on shape analysis of pixels Mathematical model Based on the model differences can be attributed to a class (road, forest, field, building..) 9 Hyperion,Nasa project for target identification

10 INDUSTRIAL Solution : INDATECH Multipoint Imaging system Hyperspectral camera is used to image from optical fibers The fibers perform the analysis in the production environment All measurements are made at the same time (30 to 100) Visible - NIR Range : provides the chemical information due to light absorption Sampling 1 Sampling 2 Sampling 3 10

11 The theory Absorption of light Scattering of light depends upon the chemical composition has been modeled by Beer-Lambert,.. depends on encountered particles size and shape has been modeled by Mie changes for each photon Irradiation by a reference light Transmitted light Irradiation by a reference light Transmitted light Reflected light Concentration variations

12 Spatially Resolved Spectrometry When liquids and solids are complex in nature, both principles can be applied. This situation was described by Patterson in 1989: exp Thus, spectra depends on position, time, absorption, diffusion and boundary conditions Example for liquids front view To resolve this, multi-point measurement is necessary. It is called spatially resolved spectrometry (SRS). sectional view Example for solids 12

13 Setup : 10 optical probes at different depths around the mixer Calibration mix : [0; ]% API SNV preprocessing for prediction of API Calibration with Unscrambler R 2 =0.99 RMSE=1.5% Otto Scheibelhofer, Nikolaus Balak, Patrick R. Wahl, Daniel M. Koller, Benjamin J. Glasser,2 and Johannes. G. Khinast1,3,4 Monitoring Blending of Pharmaceutical Powders with Multipoint NIR Spectroscopy,2012

14 Determining Blending Dynamics, End Point, and Homogeneity Blend OK OK but an overshoot appears - over mixed Blend OK At the corner of the vessel (position 3) API concentration is lower - In one experiment the API gets stuck in the corner!

15 Mixing dynamics Initial unmixed state on the left ASA accumulate at position 5-7 After some time ASA crystals are transported towards the top

16 Interest for Validation of CFD Modelling Predictions eg DynoChem As part of QbD, CFD is often used for process design to optimise reactor shape, impeller type, stirring speed etc) and also for scale-up performance. for example - Suspended Particles in a Stirred Tank

17 Raman spectroscopy for chemistery

18 How it works? Based on light scattering But an inelastic one. Provides a fingerprint of the whole material Rayleigh Scattering : The wavelength is not modified (elastic) Raman Scattering : Wavelength is modified (removal of a energy quantum : inelastic )

19 How it works? RE1 Based on light scattering But an inelastic one. Stokes and anti-stokes ( emission and absorption) Rayleigh Scattering : The wavelength is not modified (elastic) Virtual level of energy Excited state Raman Scattering : Wavelength is modified (removal of a energy quantum : inelastic ) Energy fondamental level Phonon Stokes effect Two states =Two peaks Large band = large peak

20 Diapositive 19 RE1 Is this photon?!?! Richard Escott; 26/04/2017

21 Information contained in emission Raman signals are recorded in cm-1 The formula to obtain this wavelength shift is: 20

22 Belgium project between different entities D. Brouckaert, T. De Beer J.S Uyttersprot, W. Broeckx Posters presented at APCAT 2015, 2016 Articles in ACA : Development and validation of an at-line fast and non-destructive Raman spectroscopic method for the quantification of multiple components in liquid detergent compositions Calibration transfer of a Raman spectroscopic quantification method from at-line to in-line assessment of liquid detergent compositions

23 At-line measurements Objective : To develop a method with the ability to quickly analyse the product through a plastic vial. Steps 1. Identifying the products to decide which model must be used > SIMCA Modelling 2. Develop a model to predict the concentration of each component > PLS modelling Sample preparation For each class a central composite design was used in order to obtain data at different concentrations 22

24 At-line measurements Tool : 785nm Laser Indatech Deep coold JY sensor Raman probe with a specific vial analyser concept Lab production 23

25 Results Perfect discrimination Excellent prediction 24

26 Challenge 2 : Transfer and in-line Objectives : To perform predictions directly in-line Provide a feedback loop Approach: Perform direct prediction in-line Transfer the model obtained in the lab Perform experiments to optimise transfer Provide feedback loop Use OPC-UA to communicate with software such SyntQ or Sipat, Process Pulse II 25

27 At-line and in-line measurements At-line in the lab In-line in pipe In-line in reactor 26

28 In-line measurement 27

29 Conclusions Raman spectroscopy provided successful results for identification and prediction The at-line system was successfully used in production and generated a very positive approach from the operator. An in-line system could be successfully deployed thanks to the knowledge and experience gained from the at-line analysis. Safety was carefully studied and designed with the production staff. 28

30 General Conclusion Different applications need different solution SRS and Multipoint measurements: Provide better knowledge of complex liquid Provide a solution for large batch and continuous process. Enable physical and chemical attribute Can monitor stability of emuslion or sedimentation Raman Spectroscopy: Scale up possible from alb to production Provide high sensitivity for low concentration of product Less sensitive to water than NIR

31 Thanks for your attention SRS VIS and NIR Raman Analyser UV/ VIS analyser High turbidity and color analyser Hyperspectral imaging