Solutions for the Hollow and Float Glass Industry

Transcription

1 Solutions for the Hollow and Float Glass Industry > Residual Stress Measurement > Glass Color Measurement > Batch & Glass Property Calculation Overview Presentation, March 2015 copyright ilis gmbh, all rights reserved ilis gmbh Konrad-Zuse-Str. 22 D Erlangen +49 (9131)

2 2 Presentation Outline Company introduction and product overview Cost reduction by optimizing the annealing process and avoiding breakage Cost reduction by stabilizing glass color and accelerating color changes Cost reduction by stabilizing the glass chemistry and minimizing raw material costs and energy consumption

3 3 ilis gmbh Products and services for the glass and optics industry Founded 1998, based in Erlangen, Germany Export rate: approx. 60% Main activities and products: Measurement of the glass color: Chroma software package Batch calculation and glass property prediction: BatchMaker software package Measurement of stress birefringence StrainMatic imaging polarimeter systems StrainScope real-time polarimeter systems

4 4 References (among others)

5 5 Chroma Color Measurement (not only) for the Glass Industry Helmholtz values (Chromaticity Diagram), CIELAB values etc. UV transmission, solar transmission (EN 410/ISO 9050) Spectral redox determination (Fe 2+ /Fe 3+ ratio) Custom calculations Integrated data management and trend analysis Direct control of many spectrometer models Workflow-oriented user interface

6 6 BatchMaker Batch Calculation and Glass Property Prediction Easy and fast calculation and correction of batch recipes Convenient management and editing of chemical components, raw materials and analyses Consideration of melting losses due to evaporation or saturation processes Calculation of major batch and glass properties Configurable reports, integrated raw material usage and glass property calculator Modern Windows user interface with integrated database

7 7 StrainMatic Automatic Polarimeter Systems for Objective Measurement of Residual Stresses in Glass Automatic determination and color-coded presentation of the stress distribution Objective and reliable results Calculation of polarization angle, temper number (ASTM C148), optical retardation (nm) and stress (MPa) Cord stress measurement (ASTM C978) Definition of limit values for good/bad evaluation Automatic filing of all parameters and results Various models for different application areas

8 8 StrainScope Stress Measurement in Real Time Measurement and display of the stress distribution in real time (up to 20 Hz) Fast acquisition of moving objects possible Applications: Digital Polariscope 100% testing in production

9 9 Residual Stress Measurement with StrainScope Motivation Basic Principle of Stress Measurement Automatic versus Manual Measurement Optimization of the Annealing Process

10 10 Motivation The strength of glass and plastic products and their ability to be processed is influenced strongly by mechanical stresses. Even minor residual stresses can negatively influence the function of optical materials and components. If at all residual stresses are often still determined using ordinary polariscopes or polarimeters: Imprecise and subjective method No documentation of results Whereas modern imaging methods allow an automatic and fast measurement with high resolution. The measurement in real time enables the monitoring and control of production processes and a 100% inspection of the production.

11 11 Fundamentals of Photoelasticity Refractive index? Birefringence? Polarized light? Optical isotropic? Temper number? Polarimeter? Polariscope? Quarter-wave plate? Optical retardation? Polarization angle?

12 12 Stress Birefringence The velocity of light in a material depends on the particle density. The refractive index is the ratio of the velocity of light in vacuum to that in the material, n=c/v Mechanical stress leads to deformation of the material structure and changes the velocity of light (and the refractive index) in different directions => stress birefringence

13 13 Linear, Circular, Elliptical Polarization Relationship between ellipticity and optical retardation

14 14 Polarization Angle When examining a sample under two crossed polarizers, stresses appear as bright areas within the normally dark field of view. The polarization angle describes the ellipticity of the departing light and therefore is a measure of the birefringence and thus the stress in the material. The polarization angle can be measured by turning the second polarizer (named analyzer) until a bright spot becomes dark.

15 15 Polarimeter Setup

16 16 Units of Measurement The optical retardation R in nm can be calculated from the polarization angle using a simple formula: R = / 180 For describing the state of residual stress in container glass, ASTM C defines the unit of apparent temper number, referring to the nominal retardation of a Strain Disk standard (which was originally used for visual comparison): T A = R / 22.8 nm Taking the thickness d into consideration, the apparent temper number can be converted into a so-called real temper number: T R = T A (4.06 mm / d) = (R / 22.8 nm) (4.06 mm / d)

17 17 Conventional Measurement Polarimeters allow to measure the stress at a specific point using the described Sénarmont principle. Polariscopes visualize stresses by interference colors. Neutral areas appear in magenta and areas with stress in blue and yellow. Polariscopes allow a quick assessment of the stress level, but no exact measurement.

18 18 Automatic Measurement with StrainScope Realtime Polarimeters Rotating analyzer replaced by a polarization camera that delivers multiple images with different polarization states. Measurement and evaluation with 20 Hz frame rate. measuring head with special camera and lens sample StrainScope S3/180 Diffuse illumination (LED array) Matrix camera (600 x 450 px) with fixed focal length lens Field of view: max. 150 x 112 mm Measuring range: -280 to 280 nm light box with illumination and polarizer Measurement resolution: < 1 nm Especially suited for non-destructive testing of glass bottles (camera looks through the bottle neck)

19 19 Measuring Principle Determination of the polarization angle for each pixel using a special camera Calculation of optical retardation (nm) or Temper Number Color-coded display of the measured values (e.g. 0 nm = blue, 32 nm = red) 10 (32 nm) 5 (16 nm) 0 (0 nm)

20 20 StrainScope User Interface Real-time stress image Gray-scale image Measurement settings Result (max value)

21 21 StrainScope Archive View Selected measurement List of all measurements Filter settings

22 22 Reproducibility (Gage R&R Analysis) Systematic analysis of the Repeatability & Reproducibility of a conventional polarimeter (manually operated) and a StrainScope. Measurement of 12 bottles (GDB 0.75l) and 8 food jars (0.5l). Each sample was measured three times by three trained operators (i.e. 12 x 3 x 3 = 108 and 8 x 3 x 3 = 72 individual measurements, respectively). Results (Total Gage R&R value): Gage Bottles Food jars Polarimeter 31.8% 60.9% StrainScope 10.9% 11.7% Gage R&R value <10%: excellent <20%: good <30%: sufficient >30%: inacceptable

23 23 Gage R&R Results (Manual Polarimeter)

24 24 Gage R&R Results (StrainScope)

25 25 Stress Annealing Process During the forming process the container is cooled rapidly. Since glass is a poor heat conductor, the glass cools down unevenly which creates strong inner stresses (especially in the base region). In the annealing lehr, the stress is relieved as far as possible by reheating the container to the so-called annealing point (approx C) and holding it at this temperature for a certain time. Thereafter, the container is cooled down slowly to room temperature without creating new stresses.

26 26 Residual Stress Measurement Residual stress level depends on the position in the annealing lehr and on the position in the IS machine. left side conveyor center right side 3,5 1,90 3 2,5 2 1,5 1 0,5 apparent temper number 1,70 1,50 1,30 1,10 0,90 0 Left Center Right 0,70 Section 12 Front Section 1 Rear Section 12 Rear Section 1 Front 0, mould number minimum maximum average

27 27 Annealing Optimization Each produced article has its own individual optimal cooling demand, based on production speed, article weight and wall thickness distribution. In many cases the annealing lehr settings are not optimal in respect to the energy usage, i.e. residual stresses are lower than acceptable Energy saving potential In order to find ideal settings, the annealing process has to be monitored with reliable measuring gages (no control without measuring). By using SPC methods the cooling curve can be optimized without negative effect on the quality. In several projects, up to 50% energy saving could be realized.

28 28 Stress Measurement - Summary The manual measurement of residual stresses using conventional Polariscopes or Polarimeters is subjective and operator-dependent The StrainScope automates the measurement and delivers a reproducible, operator-independent value Results obtained with the StrainScope can be documented and automatically transferred to quality control systems The high measuring resolution makes it possible to use the obtained data for process optimizations, such as minimizing the energy consumption of the annealing lehr

29 29 Color Measurement with Chroma Motivation Basic Principle of Color Measurement Color measurement with Chroma Trend analysis to accelerate color changes

30 30 Motivation Color is a human perception and strongly dependent on the observer Color is therefore measured in an objective way and determined according to international standards (e.g. ISO 11664) The software provided with the spectrophotometer is general purpose and mainly intended for the chemical industry Chroma combines the measurement of the spectrum (direct control of the spectrophotometer), the color evaluation and the data storage in a single, workflow-oriented software

31 31 Example for Color Misperception Is field A brighter or darker than field B?

32 32 Example for Color Misperception Is field A brighter or darker And than now? field B?

33 33 Color Measurement Color measurement is the determination of the tristimulus values (X, Y, Z) for a given color stimulus () Methods of measurement: Equality method (see color comparison) Three-sensor method (direct determination of color values) Spectral method (measurement of the color stimulus) Metrology (spectral method): Scanning spectrophotometers Simultaneous spectrometers (multi-channel spectrometers)

34 34 Process of a Measurement Acquisition of the raw spectrum Correction of the raw data Boundary surface reflectance Absorbance of the immersion liquid Conversion to standard thickness Calculation of the color effect Helmholtz values (Chromaticity diagram) CIELAB color values (L * a * b * color space) Calculation of special parameters Fe 2+ and Fe 3+ concentrations acc. to the law of Lambert-Beer Redox state acc. to Bamford/Hudson Radiation, light and UV transmittance (ISO 9050 / EN 410)

35 35 Spectrophotometer Assembly (Double-Beam)

36 36 Measurement in Air air sample air o 2 1 n o 1 o R n n 1 1 2, R glass 4%

37 37 Measurement in Air Corrections 1. Measured spectrum at e.g. 5 mm thickness 2. Correction of boundary surface reflectance (e.g. 8%) 3. Conversion to e.g. 10 mm layer thickness 4. Adding the boundary surface reflectance (e.g. 8%, optional)

38 38 Measurement in Immersion Cell with index-matching liquid Cell with index-matching liquid and glass sample

39 39 Measurement in Immersion - Corrections 1. Measured spectrum at e.g. 5 mm thickness 2. Correction of the absorbance caused by immersion oil 3. Conversion to e.g. 10 mm layer thickness 4. Adding the boundary surface reflectance (e.g. 8%, optional)

40 40 Color Determination Tristimulus values, Chromaticity coordinates Tristimulus values X, Y, Z Chromaticity coordinates x, y, z Chromaticity diagram, Helmholtz values (DIN 5033) Dominant wavelength dom Saturation S Brightness A L * a * b * color space, CIELAB values (CIE 1976) Lightness L * Position on the green/red axis a * Position on the blue/yellow axis b * Color distance E * ab, C * ab, h * ab Specific/simplified color systems (e.g. Heineken)

41 41 Tristimulus Values & Chromaticity Coordinates Tristimulus values X, Y, Z For transmission: Chromaticity coordinates x, y, z i i i u u i i i i i i i i i y d y k z k d z k Z y k d y k Y x k d x k X ) ( ) ( 100 ) ( ) ( 100 ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( y x Z Y X Z z Z Y X Y y Z Y X X x 1,, i i i i i i i i i i i i i i i u y S k z S k Z y S k Y x S k X S S ) ( ) ( 100 ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ), ( ) ( ) ( color stimulus function S radiation function of the light source spectral transmittance u stimulus function of the achromatic stimulus k scaling factor

42 42 Determination of the Tristimulus Values Determination of the Tristimulus Values 1,00 0,80 0,60 Measured transmittance spectrum Spectral radiation function of D65 light source 0,40 0,20 Transmittance spectrum multiplied with D65 radiation function 0,00 Tristimulus curves Wavelength λ [nm] x(λ) y(λ) z(λ) S(λ) t(λ) t(λ)s(λ)

43 43 Determination of the Tristimulus Value X Tristimulus Value X 1,00 0,80 X k ( ) x( ) d 0,60 0,40 0,20 0, Wavelength λ [nm] t(λ)s(λ)x(λ) x(λ) y(λ) z(λ) t(λ)s(λ)

44 44 Determination of the Tristimulus Value Y Tristimulus Value Y 1,00 0,80 Y k ( ) y( ) d 0,60 0,40 0,20 0, Wavelength λ [nm] t(λ)s(λ)y(λ) x(λ) y(λ) z(λ) t(λ)s(λ)

45 45 Determination of the Tristimulus Value Z Tristimulus Value Z 1,00 0,80 0,60 Z k ( ) z( ) d 0,40 0,20 0, Wavelength λ [nm] t(λ)s(λ)z(λ) x(λ) y(λ) z(λ) t(λ)s(λ)

46 46 Determination of the Helmholtz values Dominant wavelength d d Intersection of line EF with the spectral curve Color saturation S S EF EP ( x ( x F P x x E E ) ) 2 2 ( y ( y F P y y E E ) ) 2 2 Brightness value A A Y

47 47 Helmholtz Values - Illustration Parameters: Tristimulus values X, Y, Z Chromaticity coordinates x, y, z Dominant wavelength dom Saturation S Brightness A (=Y)

48 48 CIE-LAB System 1976 X, Y, Z tristimulus values X 0,Y 0,Z 0 tristimulus values of the colorless object a* > 0: reddish a* < 0: greenish b* > 0: yellowish b* < 0: bluish für für 29 6 für für 29 6 für für Z Z Z Z Z Z Z Z Z Y Y Y Y Y Y Y Y Y X X X X X X X X X Z Y b Y X a Y L

49 49 Color Distance Formula In a perception-based color space the geometric distances are directly proportional to the sensed color distances Color distance formula: E ab < 1 no sensible color difference E ab L a b L a b L 2 a b L a b 1 1 E ab < 2 almost no difference, only visible with a trained eye E ab < 3,5 medium difference, visible with an untrained eye E ab < 5 Significant difference E ab > 5 Strong difference

50 50 CIE-LAB Color Plane Parameters: Tristimulus values X, Y, Z Brightness L * Green/red ratio a * Blue/yellow ratio b * Color distance E * ab Chroma C * ab Chroma angle h ab

51 51 Fe 2+ and Fe 3+ Concentrations Lambert-Beer law: ( ) ( ) e o ( ) cd c lg( ) ( ) d Absolute concentrations of Fe 2+ and Fe 3+ : 0 c d original intensity transmitted intensity transmitted fraction wavelength molar extinction coefficient concentration sample thickness c Fe 2 lg(1000 nm) 2 (1000 nm) d Fe c Fe 3 lg(380 nm) 3 (380 nm) d Fe Attention: The molar extinction coefficients are strongly dependent on the glass composition, especially the alkali content. The Fe 3+ value is strongly influenced by measuring errors and has to be used with care.

52 52 Redox State acc. to Bamford/Hudson Fe 2+ /Fe 3+ ratio as to the formula of Bamford/Hudson: Fe Fe log (1050nm) 0,133 1 log (380nm) log (1050nm) 0,133 log (380nm) Relative fractions of the total iron: % Fe % Fe ( Fe ( Fe 100 % Fe 2 2 Fe 3 Fe ) 3 ) Attention: This works only with flint glass und to a certain extent for green glass! Especially with amber glass the wavelengths are influenced by other absorption bands.

53 53 Trend Analysis Graphical trend analysis makes it possible to accelerate color changes by increasing the coloring oxides stepwise to reach the new level as quickly as possible.

54 54 Color Measurement - Summary The color is not a physical property, but a human sensation and can only be controlled when measured with an objective measuring instrument The workflow-orientated user interface of Chroma simplifies the color measurement process as effectively as possible Measuring the glass color in a regular interval (e.g. once per shift) makes it possible to stabilize the color and react quickly in case of color deviations Statistical monitoring the trend of the color values makes it possible to shorten the time for color changes significantly, resulting in improved pack-to-melt ratio

55 55 Batch Calculation with BatchMaker Motivation Basic Principle of Batch Calculation Reliable Prediction of Glass Properties Raw Material Cost Optimization

56 56 Motivation The raw material costs have a decisive share of the production costs A constant glass composition is a prerequisite for steady melting and glass properties The objective of batch calculation is: Compliance with a defined chemical glass composition at minimum raw material costs In face of constantly rising raw material and energy prices, batch calculation is of great economic importance BatchMaker is a standard software for calculating batches and glass properties and offers substantial saving potentials

57 57 Batch Calculation Workflow Calculation of raw material weights for a given glass composition Batch recipe Glass Recipe Nominal composition Carrier raw materials Fixed additives Raw Material & Cullet Analyses Chemical compositions Humidities & prices Synthesis: Calculation of the (theoretical) glass composition for a given batch The trouble-free operation of any glass works begins in a thorough knowledge of both the chemical and physical properties of the batch materials (Taylor, 1975) Batch Plant Batch Recipe Raw material weights Glass synthesis Glass properties Batch costs Laboratory Data Management System

58 58 Principle of Calculation (simplified) Raw material analyses and desired glass synthesis: Oxide Glass sand Feldspar Dolomite Limestone Soda Synthesis SiO % 69.0% 72.0% Al 2 O 3 0.5% 18.0% 1.5% CaO 2.0% 31.0% 50.0% 9.0% MgO 21.0% 5.0% 3.0% Na 2 O 5.0% 58.5% 14.5% Corresponding linear equation system: SiO 2 : x x x x x 5 = 72.0 Al 2 O 3 : x x x x x 5 = 1.5 CaO: x x x x x 5 = 9.0 MgO: x x x x x 5 = 3.0 Na 2 O: x x x x x 5 = 14.5

59 59 Principle of Calculation (cont.) Representation as extended coefficient matrix: After Gauss elimination method and normalization to 100 kg of glass sand: Glass sand: = 100 kg Feldspar: kg Dolomite: kg Limestone: kg Soda: kg

60 60 Glass Synthesis Calculation of the theoretical glass composition from the determined raw material weights and the corresponding raw material analyses: Glass sand Feldspar Dolomite Limestone Soda 100 kg 9.51 kg kg kg kg Oxide Percentage SiO % 69.0% Al 2 O 3 0.5% 18.0% CaO 2.0% 31.0% 50.0% MgO 21.0% 5.0% Na 2 O 5.0% 58.5% SiO 2 72,0% Al 2 O 3 1,5% CaO 9,0% MgO 3,0% Na 2 O 14,5% SiO 2 : kg kg kg kg kg = kg Al 2 O 3 : kg kg kg kg kg = 2.21 kg CaO: kg kg kg kg kg = kg MgO: kg kg kg kg kg = 4.42 kg Na 2 O: kg kg kg kg kg = kg % Sum = kg

61 61 Workflow in BatchMaker Edit Configuration Data Definition of used raw materials and cullet (master data) Input of chemical analyses for all ingredients Create/Edit Glass Recipe Definition of the nominal chemical composition Selection of carrier raw material to be used Calculate Batch Recipe (Automatic) calculation of raw material weights Calculation of glass synthesis and comparison with nominal analysis Prediction of important melt and glass properties (redox number, thermal expansion, density, viscosity, etc.)

62 62 Raw Material Analyses & Prices List of userdefined raw materials Available oxides and elements chemical composition (here of Dolomite, as selected above)

63 63 Glass Recipe Desired glass composition (synthesis) Available oxide and elements Main oxide carriers, e.g. Feldspar for Al 2 O 3 Available raw materials

64 64 Calculated Batch Recipe Oxide analysis, here of foreign cullet Calculated weights

65 65 Batch Recipe - Glass Synthesis Chem. composition calculated from initial weights Nominal values as defined in the glass recipe Differences to nominal values

66 66 Batch Recipe - Glass Properties Viscosity curve Viscosity fixed points Glass properties Exceeded application limits

67 67 Glass Property Calculator Calculated glass properties Chemical compositions of different glasses Switchover between wt% and mol% exceeded application limits

68 68 Viscosity Curves and Fixed Points Values at cursor position Viscosity fixed points Viscosity curves

69 69 Batch Costs Optimization Example 1: Reducing soda consumption Example 2: Substituting raw materials Example 3: Stabilizing total alkali content Example 4: Stabilizing total iron content Example 5: Using waste raw materials

70 70 Batch Costs Optimization: Example 1 Reduction of Na 2 O by 1% and 0.1% for a 300 ton/day furnace: Oxide Main raw material Price per ton Glass #1 Glass #2 Glass #3 SiO 2 Glass sand 30 72% 72.5% 72.6% Na 2 O Soda % 13.0% 12.9% CaO Limestone 15 10% 10.5% 10.5% Al 2 O3 Feldspar % 1.5% 1.5% MgO Dolomite % 2.5% 2.5% Batch costs per ton , Batch costs per day 23,352 22,390 22,296 Batch costs per year 8,523,739 8,172,270 8,138,011 Savings per year 351,469 34,259 BatchMaker license costs: 3000 per year Return of Investment (13% 12.9% Na 2 O): 1 month

71 71 Batch Costs Optimization: Example 2 Substitution of feldspar with phonolite as main carrier for Al 2 O 3 : Oxide Main raw material Price per ton Return of Investment in BatchMaker : 4 days Glass #3 Glass #4 SiO 2 Glass sand % (72.22%) Na 2 O Soda % 12.9% K 2 O (Phonolite) (0,25%) CaO Limestone % 10.5% Al 2 O 3 Feldspar % Phonolite % MgO Dolomite % 2.5% Fe 2 O 3 (Phonolite) (0.13%) Batch costs per ton Batch costs per day 22,296 21,474 Batch costs per year 8,138,011 7,838,145 Savings per year 299,866

72 72 Batch Costs Optimization: Example % total alkali content (R 2 O=Na 2 O+K 2 O) instead of 12.9% Na 2 O: Oxide Main raw material Price per ton Return of Investment in BatchMaker : 2 weeks Glass #4 Glass #5 SiO 2 Glass sand 30 (72.22%) (72.47%) Na 2 O Soda % (12.64%) K 2 O (Phonolite) (0.25%) (0.26%) R 2 O Soda (13.15%) 12,9% CaO Limestone % 10.5% Al 2 O 3 Phonolite % 1.5% MgO Dolomite % 2.5% Fe 2 O 3 (Phonolite) (0.13%) (0.13%) Batch costs per ton Batch costs per day 21,474 21,235 Batch costs per year 7,838,145 7,750,724 Savings per year 87,421

73 73 Batch Costs Optimization: Example 4 Keeping Fe 2 O 3 at a fixed level of 0.1%, using standard-quality glass sand as a carrier raw material (for a 300 ton/day furnace): Oxide Main raw material Price per ton Return of Investment in BatchMaker : 1 month Glass #6 Glass #7 SiO 2 Glass sand (low iron) 40 (72.12%) (72.12%) R 2 O Soda % 13% CaO Limestone % 10.5% Al 2 O 3 Feldspar % 1.5% MgO Dolomite % 2.5% % Fe 2 O 3 Glass sand 30 (0.093%) 0.100% Others (0.37%) (0.28%) Batch costs per ton Batch costs per day 21,522 21,417 Batch costs per year 7,855,453 7,817,227 Savings per year 38,226

74 74 Batch Costs Optimization: Example 5 Using ESP dust as a raw material (1.5 ton/day) without changing the glass composition: Oxide Main raw material Price per ton Glass #7 Glass #8 SiO 2 Glass sand (low iron) 40 (72.12%) (72.12%) R 2 O Soda % 13% CaO Limestone % 10.5% Al 2 O 3 Feldspar % 1.5% MgO Dolomite % 2.5% Fe 2 O 3 Glass sand % 0.100% Others (0.37%) (0.37%) Batch costs per ton Batch costs per day 21,417 21,324 Batch costs per year 7,817,227 7,783,406 Savings per year 33,821 Return of Investment in BatchMaker : 1 month

75 75 Batch Calculation - Summary In many cases the raw material costs can be reduced significantly Prerequisite for the cost optimization are reliable tools for batch calculation and prediction of glass properties BatchMaker Professional and BatchMaker Enterprise allow the simple and fast calculation of batch recipes and glass properties

76 76 Thank You for Your Attention! Questions?