From Color to Chemometrics

Transcription

1 From Color to Chemometrics Strategies to determine coating thickness and quality Preliminary Version AIMCAL Web Coating & Handling Conference Chris Hellwig

2 Agenda 1 About us 2 Process and Quality Control 3 Color as Quality Criterion 4 Color as Thickness Indicator 5 Chemometrie as Thickness Indicator 6 Conclusion 2

3 ZEISS Business Groups Industrial Metrology Microscopy Medical Technology 4.51 Billion EUR Revenue 369 Million EUR (EBIT) ~25,000 Employees (worldwide) Semiconductor Manufacturing Technology Financial Highlights of the ZEISS Group Carl Zeiss Jena GmbH Vision Care Update 30 September 2015 Consumer Optics Carl Zeiss Spectroscopy GmbH Subsidiary of Carl Zeiss Jena GmbH 3

4 Agenda About us Process and Quality Control Color as Quality Criterion Color as Thickness Indicator Chemometrie as Thickness Indicator Conclusion 4

5 Quality and process control Measured value - Full transmission spectra - Full reflectance spectra Calculated / derived values - Color metrics (e.g. L*,a*, b*) - Spectral results (e.g. min/max) - Layer thickness - Chemometrics (Layer content analyses, derived layer thickness) 5

6 Review: AIMCAL 2014 Not precise and not accurate Accurate, but not precise Precise, but not accurate Precise and accurate Process control capable Quality control capable Tolerances influenced by: - Measurement System - Reference Method - Calibration Standards - Process Conditions Source: wikipedia.org 6

7 Use Cases of a Process / Quality Control System 3 scenarios when using a process control software: Commisioning, product developement and improvement Where do we generally need precision, where accuracy? precision accuracy 7

8 Absolute Measurements Traditional way to calibrate spectral measurements Use of certified calibration standard (mirror, white standard) Absolute Measurements No need of certified standards Internal calibration by switching between calibration and measurement (enables absolute measurements even with the sample in measurement position) 8

9 Methods to evaluate Coating Thickness Peak method: The layer thickness is derived from the maxima and minima of the interference spectrum White light interference The layer thickness is calculated from the periodicity of the interference spectrum Color as a thickness indicator Color changes with the layer thickness Model based approaches A layer stack is described by formulas (the model), the result is compared with measurement results, parameters of the model like thickness are varied as long as they fit the measurement results Chemometric models Chemometric prediction models provide thickness informrmation complexity Interference spectrum Poly-crystalline silicon layers on silicon oxide W.Theiss Hard- and Software 9

10 Agenda About us Process and Quality Control Color as Quality Criterion Color as Thickness Indicator Chemometrie as Thickness Indicator Conclusion 10

11 Color as Quality Criterion: Basics If color appearance itself is a quality criterion it can be measured directly: - ISO / CIE standardized setup for accurate measurements (comparable with standards, inter-instrument agreement) - full spectrum sensor requested by ISO / CIE organization to overcome metamerism issues 11

12 Agenda About us Process and Quality Control Color as Quality Criterion Color as Thickness Indicator Chemometrie as Thickness Indicator Conclusion 12

13 Color as Thickness Indicator: Preparation For simple layer designs a correlation of the thickness and a color value may exist and this correlation needs to be found. This theoretical calculation can be performed prior to any real measurement (using modelling software) The data show a good correlation between thickness and the b* value for this specific layer. For process control a 3 rd order polynomial based on the data was used to calculate the coating thicknesses from the measured b* values. On six ZnO coated glass panes (S1 S6) the b* values were measured and the predicted thickness results are shown 13

14 Color as Thickness Indicator: Result The example shown demonstrates the tuning of the coating process to bring the layer to specified thickness. x Cross section plots of coating thickness variation x 14

15 Agenda About us Process and Quality Control Color as Quality Criterion Color as Thickness Indicator Chemometrie as Thickness Indicator Conclusion 15

16 Determination of Grammage on Paper: Preparation The paper samples were measured on a 45 :0 diffuse reflectance probe connected to an NIR spectrometer with a spectral range of nm. The setup was calibrated with a diffuse reference material. The paper samples grammage values ranged from 0.19 to 4.14 g/m². Each of the 13 samples was measured at three spots. The spectra of the samples with a grammage of 0.19, 1.80, and 4.14 g/m² were used to develop a calibration function 16

17 Agenda About us Process and Quality Control Color as Quality Criterion Color as Thickness Indicator Chemometrie as Thickness Indicator Conclusion 17

18 The Importance of Accuracy Color as thickness indicator: Photometric accuracy is important for this method Chemometric prediction: Will work with non-accurate (but precise) systems as well: BUT: The developed methods will only work on the system they are developed with No scaling possible In case an instrument or parts of the system needs to be changed, the method needs to be adopted Peak method: Only wavelength accuracy needed White light interference: Only wavelength pitch accuracy needed 18

19 The Freedom of Choice Different methods of thickness evaluation Choose the simplest possible method to obtain thickness information (peak method,, color, model based, chomometrics) Example: Silicone on paper and PET substrates Substrate Paper Silicone Thickness 20 nm < 100 nm 150 nm nm 0.5 µm - 3 µm Method Chemometric Chemometric on request (but Result Thickness Thickness 'questionable') Instrument NIR 2.2 µm NIR 2.2 µm PET Method spectra eval Modell based FFT on request (but Result YES vs NO Thickness Thickness 'questionable') Instrument VIS / Trans VIS / T or R VIS (NIR) / T or R Chemometric: We need a bunch of samples, thickness evaluation for set of test samples with comparision method; additional (embedded) software necessary Modell based: We need optical parameters of substrate and material(s) and some samples with known properties for check; additional (embedded) software necessary FFT: Wee need optical parameters of coating material, only 1 sample to check performance 19

20 Complete Quality and Process Control The final product quality is defined as a combination of many features like color appearance or coating thickness. Since inline spectrometers measure the full spectrum these quality-related parameters can be evaluated in one single step. Broadband inline spectrometer systems allow chemometric prediction in the NIR range as well as color evaluation, even within a single measurement system. + = Result 20

21 General Conclusion It is shown that inline spectrometers and combined analysis of the results are versatile and stable process-capable measurement systems to commission new production lines develop new coating products keep a production line stable ensure the final product quality The data provided by such instruments can be used for direct monitoring of the production process. as an input for automated control loops 21

22 Contact Chris Hellwig Product Manager ThinFilm Phone:

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