montana presentation
DESCRIPTION
Presentation to the Center for Biofilm Engineering, July 2009TRANSCRIPT
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Fouling & Cleaning Science: Direct Detection of Biofilms and CIP-Related Problems in
Liquid Process Systems
Mark Fornalik Industrial Biofouling Science, LLC
www.industrialbiofouling.com
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Introduction: Process Cleaning Science
There is a science around determining if your industrial process is truly clean, and the tools for this determination include microscopy as well as FTIR. Both are complimentary to the traditional microbiology methods.
This talk introduces fouling cell technology and how to understand the sequence, chemistry and kinetics of fouling events on the interior surfaces of pipes, tanks and liquid-handling processes.
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Process Contamination:Impact to The Bottom Line
• Poor product quality• Random quality incidents• Time spent sorting good product from bad• Wasted materials (raw and finished)• Sub-optimized process cleaning = process
downtime• Erosion of customer base
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Cost of Process Contamination
• In a Fortune 500 chemicals company, the fouling cell approach:– Found and eliminated the root causes for $20M in
product waste (note: most of this was biofilm related)– Identified manufacturing sites with best cleaning
practices– Reduced the cost of commercialization, by identifying
cleaning problems – and proper cleaning procedures - in the product development cycle
– Enabled more robust process health
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Transfer Line Contamination
Manufacturing Problems:• Cross contamination between
product types• Physical waste – spots,
streaks, particles, filter plugging, viscosity changes
• Chemical waste – chemical contamination of final product
• Increased brand change time• Loss of product flow• Increased production runs to
allow for waste
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Insoluble Wall Fouling• Fouling: The unwanted formation of insoluble
residues on engineering materials in contact with flowing solutions
• Fouling is what is left on wall surface after even a proper water flush clean
• Chemical cleaning must be designed to address water-insoluble wall fouling
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• Organic • Inorganic• Biological (bacteria, fungi, algae - BIOFILMS)• Particulate (corrosion)• Crystallization/Scale (boilers, heat exchangers)• Combination (any two or more of the above)
Insoluble Wall Fouling Types*
* T.R. Bott, * T.R. Bott, Fouling of Heat ExchangersFouling of Heat Exchangers, Elsevier (1995), Elsevier (1995)
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The goal of cleaning is to return the system to the induction periodlevel of fouling
Fouling Rate
time
foul
ing
mas
s physicalproblems
chemicalproblems
induction period
secondary fouling
steady state
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Fouling Cell Technology:• Analyze fouling film while in place on substrate• FTIR for non-destructive chemical characterization (organics)• Epifluorescence microscopy determines if organics are biofilm
Fouling Cell Technology: Direct Detection of Biofilms & CIP Efficacy
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Process Cleaning: A Structured Approach
System Design
Water Flush Optimization
Chemical Clean Optimization
Biofilm Control
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Insufficient water flush leaves product behind in pipe; optimized water flush reaches “plateau” more quickly for
faster cleaning times
Water Flush Cleaning
0 .0 0 0 1
0 .0 0 1
0 .0 1
0 .1
1
1 0
1 0 0
1 0 0 0
0 5 1 0 1 5 2 0 2 5 3 0 3 5
T im e (m in u te s )
Per
cent
of D
ye in
the
Flus
h S
olut
ion
M a g e n ta Y e llo wC y a n
Old process water flush end point
Water flush “plateau “
Water Flush Cleaning: A Two-Step Process
1. Product displacement – governed by hydrodynamics
2. Wall cleaning – governed by kinetics
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Powerflush (Two-Phase Flow)Cleaning
Cleaning efficiency varies as a function of the ratio of air flow to water flow
Efficient flow ratio Water-rich flow ratio
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Direct Measure of Powerflush Cleaning Efficiency
-0.0010-0.0005
0.0000
0.0005
0.0010
0.0015
0.0020
0.0025
0.0030
0.0035
0.0040
0.0045
0.0050
0.0055
0.0060
0.0065
0.0070
0.0075 0.0080
Abs
orba
nce
1000 1500 2000 2500 3000 3500 Wavenumbers (cm-1)
-0.0010-0.0005
0.0000
0.0005
0.0010
0.0015
0.0020
0.0025
0.0030
0.0035
0.0040
0.0045
0.0050
0.0055
0.0060
0.0065
0.0070
0.0075 0.0080
Abs
orba
nce
1000 1500 2000 2500 3000 3500 Wavenumbers (cm-1)
Peak height data correlate to effectiveness of cleaning: the smaller the peak, the more effective the cleaning
Before powerflush
After powerflush
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Chemical Cleaning Variables
Chemical cleaner formulationConcentrationTemperatureOrder of addition
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Measuring Chemical Cleaning Efficiency
0%
20%
40%
60%
80%
100%
TSP NaOCl TSP/NaOCl NaOH Citric acid
clea
ning
effi
cien
cy
FTIR peak height before & after cleaning provides an estimate of
cleaning efficiency
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Studying Chemical Cleaning Parameters
0%10%20%30%40%50%60%70%80%90%
100%
25 C 45 C 65 C5% NaOH
clea
ning
effi
cien
cy
Impact of temperature
0%10%20%30%40%50%60%70%80%90%
100%
0.2% 1.0% 5.0%NaOH wt% @ 60 C
clea
ning
effi
cien
cy
Impact of concentration
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Biofilm Chemistry Over Time*Subtraction Result:ir1848, 610 NRX disc #26, 3-month exposure, no clean*Subtraction Result:ir1896, 610 NRX, 14 batches (4 days), disc #7 (1/30 - 2/2/98)*Subtraction Result:ir2288, 610, NRX, #10, 24 hours, 5 batches, 2/26 - 2/27/98*Subtraction Result:ir1974, disc 10, 610 NRX, 1 batch, 4 hrs, without santoprene gasket
-0.008
-0.007
-0.006
-0.005
-0.004
-0.003
-0.002
-0.001
0.000
0.001
0.002
0.003
0.004
0.005
0.006
0.007
0.008
0.009
0.010
0.011
0.012
0.013
0.014
0.015
0.016
0.017
0.018
0.019
0.020
Abs
orba
nce
600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 3000 3200 3400 3600 3800 4000
Wavenumbers (cm-1)
Biofilm exopolymer becomes more cleaning resistant upon aging
2 hrs
8 hrs
24 hrs
6 mo
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Case Study: Comparing Cleaning in Two Winery Product Lines
Fermentation cellar line
Fouling cells
Bottling line
Filler lines
Cellar & bottling lines cleaned daily with hot water & iodophor before & after each use
Filler line cleaned daily with 140F water, caustic/bleach, peracetic acid, 190F water
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Winery Line A 10 WeeksFermentation cellar line
Bottling line
Filler line
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Winery Line B 10 WeeksFermentation cellar line
Bottling line
Filler line
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21bottling A
Cellar A
surge tank10002000
10002000
10002000
cellar
bottling
filler
Winery Line A 10 Weeks
protein
carbohydrate
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22bottling B
Cellar B
surge tank
10002000
10002000
10002000
Winery Line B 10 Weekscellar
bottling
filler
protein
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Winery FTIR Peak Height Comparison
82 Line/Line 4
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
cellar bottling filler 1st
fouling cell location
peak
hei
ght
amidecarbo
Cribari Line/Line 5
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
cellar bottling filler A side filler B side
fouling cell location
peak
hei
ght
amidecarbo
Line BLine A
Conclusions:
• Fillers from both lines were clean
• Both lines A and B exhibit biofilms in cellar and bottling lines
• Line A has thicker fouling layer
• Line A exopolymer is carbohydrate & protein; Line B exopolymer is protein
• Both biofilms resist daily chemical cleaning: hot water, caustic, peracetic acid, iodophore
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Case Study: Mapping Process Cleaning in Bioproducts Plant
Fermentation reactor
Centrifuge
Process filters
Recovery
Fouling cells
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Fermentation Fouling Cells2-day exposure before CIP
2-day exposure after CIP
4-week exposure after CIP
CIP: 5% NaOH, 65°C, 30 min daily
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Recovery Fouling Cells2-day exposure before CIP
2-day exposure after CIP
4-week exposure after CIP
CIP: 5% NaOH, 65°C, 30 min daily
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Fermentation vs. Recovery
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Conclusions• Microscopy provides a valuable tool in industrial biofilm detection
and characterization• Fouling cells provide an ideal way to acquire biofilms in full-scale
manufacturing processes• Fouling cell technology is complimentary to existing microbiology
methods for biofilm analysis, enabling analysis of exopolymer and biofilm morphology while still in place on the fouled surface
• FTIR analysis targets exopolymer and residual chemicals fouling from product
• This approach can be used to “map” the cleaning effectiveness within a process or compare cleanliness over different production lines or sites, and determine whether product fouling or biofilms are the root cause of process and product contamination issues
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WineryFood dye
Food dye
Bioproducts
Industrial salt system
Gelatin
AgNO3
Ultrapure water
Brewery
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With Thanks to Kodak’s Former Systems Cleaning
Group
M. Giang, M. Grannas,D. Gruszczynski, J. Hunt,
D. Irwin, Y. Lerat, C. Puccini,R. Schmanke, J. Steegstra, M. Wallace,
M. Wilcox, G. Wilson,K. Brockler, J. Fornalik