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Fouling and Cleaning Studies in the Food and

Beverage Industry Classified by Cleaning TypeKylee R. Goode, Konstantia Asteriadou, Phillip T. Robbins, and Peter J. Fryer

Abstract: Fouling of food process plant surfaces and the subsequent cleaning needed is a significant industrial problem,and as the cost of water and chemical disposal increases, the problem is becoming more significant. Current literature

on water-based cleaning is reviewed here according to the classification of 3 types of cleaning problems. By doing this,

it is hoped that new knowledge can be highlighted applicable to improving industrial cleaning. (i) For type 1 deposits

(that can be cleaned with water alone)Cleaning time appears related to Reynolds number and surface shear stress. An

increase in Reynolds number seems to decrease cleaning time. Cleaning temperatures greater than 50 C do not appear

beneficial. (ii) For type 2 deposits (biofilms)Removal behavior of biofilms seems to be dependent on the microbial

aging time on the surface. Keeping a material hydrated on a surface enables easier removal of it with water. a. Waterrinsing: Temperature and wall shear stress have varied effects on removal. b. Chemical rinsing: Flow and temperature were

seen to have the biggest effect at the start of cleaning, but contact time was more important as cleaning progressed at a

given sodium hydroxide solution flow and temperature. (iii) For type 3 deposits (that require a cleaning chemical)For

specifically, protein-based systems excessive chemical forms a deposit difficult to remove. Increasing wall shear stress and

temperature was most beneficial to cleaning rather than concentration. The action of temperature can reduce the use

of a chemical for type 2 and type 3 soils. The findings suggest that the right combination of flow characteristics at a

given temperature and concentration is crucial to achieving fast cleaning in all cases. There are a number of cleaning

monitoring methods at various stages of commercialization that may be capable of monitoring bulk cleaning and cleaning

at the surface. To optimize cleaning will require integration of measurement methods into the cleaning process.

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

2. Fouling studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32.1 Adhesion of microorganisms to surfaces. . . . . . . . . . . . . . . . 4

2.3 Preventing fouling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.3.1 Process surface modification . . . . . . . . . . . . . . . . . . . . . . 5

2.3.2 Process alterations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63. Cleaning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

3.1 Product recovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93.2 The effect of CIP parameters on type 1 removal . . . . . . . 10

3.2.1 Flow and wall shear stress.. . . . . . . . . . . . . . . . . . . . . . .113.2.2 Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113.2.3 Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

3.3 The effect of CIP parameters on type 2 and typed e p o s i t r e m o v a l . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 3

3.3.1 Membrane cleaning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133.3.2 Water-rinsing of hard surfaces . . . . . . . . . . . . . . . . . . . . 14

MS 20120483 Submitted 3/29/2012, Accepted 10/14/2012. Authors are withSchool of Chemical Engineering, Univ. of Birmingham, Edgbaston, Birmingham, B152TT, U.K. Direct inquiries to author Fryer (E-mail: [email protected]).

3.3.3 Chemical effects on the cleaning oftype 2 deposits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

3.3.4 Chemical effects on the cleaningof type 3 deposits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

4. Novel cleaning approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164.1 Increasing boundary layer disruption.. . . . . . . . . . . . . . . . .16

4.2 Alternative cleaners to reduce environmental impact . . . 164.3. Other studies related to cleaning behavior . . . . . . . . . . . . 17

4.3.1 Deposit shear . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174.3.2 Deposit deformation and strength . . . . . . . . . . . . . . . . 17

5. Measur ing cleaning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 7

5.1 Online bulk measurements . . . . . . . . . . . . . . . . . . . . . . . . . . 185.2 Online surface measurements.. . . . . . . . . . . . . . . . . . . . . . .195.3 Measuring microbial cleanliness . . . . . . . . . . . . . . . . . . . . . . 19

6. Summary and conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

IntroductionThe success of a branded fast moving consumer goods (FMCGs)

business depends fundamentally on product quality and safety con-

formance at a required level. Poor cleaning or hygiene confor-mance can be a result of fouling layers building up in a plant

or other problems. Figure 1 illustrates a typical route by whicha large FMCG manufacturer will ensure a hygienic plant. There

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doi: 10.1111/1541-4337.12000 Vol. 12,2013 ComprehensiveReviewsinFoodScienceandFoodSafety 121

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Critical review in fouling and cleaning . . .

Define CIP standard

Best process design

Best process parameters

Establish standard at all sites

By site educaon, training and

empowerment and recording site

CIP condions

Is hygiene being

achieved?

Why

not?

NON -

CONFORMANCE

e.g. Poor

maintenance,

control or training

NO

LACK OF FUNDAMENTALS

e.g. The effect of CIP

parameters on different fouling

condions

Scienfic invesgaon

Invesgate design

Invesgate process parameters

Input from pracce

Inputfroms

cience

YES

Inputfromp

racce

Figure 1Flow diagram illustrating the route taken by industry to ensure plant hygiene (Heineken personal communication 2012).

should be fundamental research and development obtained from

both practice and science that are integrated and applied in-plantto provide the optimum cleaning protocol. In food and bever-

age manufacturing operations, cleaning-in-place (CIP) is used toremove residual product, fouling, and microbes that remain in

the process line from production. The act of cleaning thereforemaintains product quality, safety, and production efficiency. Dur-

ing CIP, water and/or chemical solution is circulated around plantprocess equipment. With large-scale manufacturers, the process is

generally fully automated. A typical CIP philosophy in industry isthat of Scottish & Newcastle Breweries (2008):

ensure all production, processing, and packaging plant is

cleaned by a standard regime and to a schedule which ensurescleanliness and microbiological integrity at all times; with min-

imum cost, energy, and delay to production in a manner whichensures human, plant, product, and environmental safety.

A significant body of cleaning knowledge exists within individ-

ual manufacturers, equipment suppliers, and chemical companies;however, the determined cleaning regimens have often been keptconfidential and plant-specific. This has resulted in independent

development of cleaning operations. Organizations such as theEuropean Hygienic Engineering and Design Group (EHEDG)

have produced extensive guidelines on the types of surface andequipment that are easy to clean, such as detailed in the EHEDG

Yearbook (2007).CIP tends to follow a similar series of steps for a prescribed

time and at a prescribed flow rate, temperature, and chemicalconcentration known to give a repeatable level of cleanliness. It

is not yet possible to predict before an operation how a givenpiece of equipment could foul and be cleaned. It is difficult to

identify the best way to clean a processing plant from experiments

of different plants. The direct selection of cleaning protocols isnot always possible. In practice, cleaning protocols can only be

developed semiempirically in industry. In most cases, CIP cannotbe optimized in situ because of the risk posed of compromising

existing cleanliness.Fryer and Asteriadou (2009) suggest a classification of cleaning

problems in terms of cleaning cost and soil complexity. A diagram-matic representation of this relationship is presented in Figure 2.

This classification enables the nature of a foulant to be related tothe type of cleaning employed, and therefore, the cost. This clas-

sification also indicates the environmental impact of the type ofcleaning employed; complex soils require chemical and thermal

cleaning that lead to a high cleaning cost and high environmen-tal impact. Three deposit types were chosen to represent a broad

range of cleaning problems seen in food, beverage, and personalcare products manufacturing:

(i) Type 1: Viscoelastic or viscoplastic fluids such as yogurt and

toothpaste that can be rinsed from a process surface withwater.

(ii) Type 2: Microbial and gel-like films such as biofilms and

polymers removed in part by water and in part by chemical.(iii) Type 3: Solid-like cohesive foulants formed during ther-

mal processing such as milk pasteurization and brewerywort evaporation. These operations mostly require chemical

removal.

Yang and others (2008) also classified cleaning optimizationmethods, here into 2 types of investigation:

(i) Engineering investigations: reducing energy, time, and cost inestablished cleaning operations.

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Figure 2Cleaning map; a classification of cleaning problems based on soil type and cleaning chemical use (from Fryer and Asteriadou 2009).

(ii) Scientific investigations: achieving cleanliness or a clean-ing time as a function of influencing factors; for ex-

ample, wall shear stress, temperature, surface type, andfinish.

The aim of this review was to provide an overview of current

knowledge on cleaning solutions classified by soil cleaning type.This novel classification is hoped to highlight new CIP optimiza-tion opportunities for industry and any future research in the

field. Current knowledge of fouling prevention and novel clean-ing methods are also discussed here.

Fouling StudiesFouling is defined as the unwanted buildup of material on a

surface. The fouling process generally involves a number of steps

(Epstein1983):

(i) surface conditioning,(ii) mass transfer of species to the surface,

(iii) surface deposition,(iv) deposit aging, and

(v) possible removal.

There is also a classification of fouling mechanisms demonstratedby Bott (1990) detailed in Table 1. Fouling problems that have

been reported in the food and beverage industries include (butthis is by no means a complete list):

Protein and mineral deposition in heat exchangers. Ice buildup in freezers. Scale buildup in cooling water systems. Fat burn-on in ovens. Product solidification.

Growth of biofilmoften after the formation of a condi-tioning layer of protein onto the surface.

Accumulation of material in stagnant or low-flow areas ofequipment.

Loss of membrane activity.

Fouling is a costly problem in the food, beverage, and otherindustries, which is often unavoidable due to the heat treat-

ment that often has to be given to products to develop cer-tain colors and flavors and ensure safety. By definition, foods

are sources of nutrients favorable not only to people but alsoto microbes that stick to process surfacesso microbial ad-

hesion to surfaces and subsequent growth are important phe-nomena. The economic penalties of fouling in heat exchang-

ers were discussed by Muller-Steinhagen (2000) and can besummarized:

(i) Capital expenditure, due to:

(a) Excess heat transfer surface area compensating for the occur-

rence of fouling. This has been estimated as an averageof 30% additional capital cost.

(b) Higher transport and installation costsfor bigger and heavier

equipment.(c) Cleaning systems, including their installation and mainte-

nance costs.

(i) Fuel costIf extra energy (such as steam) is required to

keep the fouled heat exchanger operating for the requiredperformance.

(ii) Maintenance costOf the heat exchanger, cleaning sys-tem, and any ancillary equipment in the process (and clean-

ing) loop, for example, chemical tank level probes, flowmeters, interface probes, and boilers.

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Table 1Fouling mechanisms: adapted from Bott (1990) and Sharma and others (1982).

Fouling mechanism Underlying process

Crystallization Formation of crystals on the surface formed from solutions of dissolved substances when the solubility limit is changed.Cooledsurfaces are subject to fouling fromnormally soluble salts,fats, and waxes.Inversely soluble salts,such as calciumphosphatedepositson heatedsurfaces.Where thefluid or components of the fluid solidify onto the surface, this is called

solidification fouling (Sharma and others 1982).Particulate deposition Small suspended particles such as clay, silt, or iron oxide deposit onto heat transfer surfaces. Where settling by gravity is the

determining factor, this is then calledsedimentation fouling.Biological growth (biofouling) The deposition andgrowthof organic films consisting of microorganisms andtheir products,called biofilm.Chemical reaction at

fluid/surface interface

Reaction of some part of the flow to generate insoluble material. The deposit formed on thesurface (particularly heat

transfer surfaces) has a differentcomposition to theprocess fluid (for example, in petroleum refining, polymer production,and dairy plants).Corrosion The materialof the heattransfer surface isinvolved inreactionswith componentsof the fluidto formcorrosionproducts on

thesurface, a specific type of chemical reaction fouling.Freezing Depositformedfroma frozen layeroftheprocessfluid, for example, ice fromwaterorsolidfats froma foodfluid.

(iii) Cost due to production lossCost of continuous pro-duction (without shut-down for cleaning or maintenance)

as compared to the actual production cost.

Accurate measurement of the effects of fouling and the efficiency

is critical. Changes in heat transfer efficiency have widely beenrecorded. Most common is following the change in heat transferduring fouling by including a fouling resistance, Rf, in the equation

relating the initial clean heat transfer coefficient, (U0

), to that attimet, (U):

1

U=

1

U0+ Rf (1)

And the extent of fouling may be expressed by a Biot number(Bi), which accounts for deposit thickness (x) and thermal con-

ductivity (): Bi= Rf.U0, whereRf= x/ for the deposit. Depositresistance during cleaning can be described as the reverse process

to (1) (Tuladhar2001) as

Rd=1

Uc

1

Ut(2)

whereUtis the heat transfer coefficient at time tand Ucthe heattransfer coefficient of the final clean system, so the rate of change

of this is a measure of cleaning.The rate and extent of fouling and cleaning is often classified

in terms of fluid flow, either in terms of the Reynolds number(Re = vd/, where and are the density of viscosity of a

fluid flowing at mean velocityvthrough a system of characteristiclength d, such as pipe diameter) or the surface shear stress. In

this paper, many correlations in terms of Reynolds number arediscussedto convert to velocity requires knowledge of density

and viscosity of the fluid, which is simple for water but may bemore complex for cleaning solutions.

Adhesion of microorganisms to surfaces

The principal f actors responsible for adhesion between surfaceand foulant include: (i) van der Waals forces, (ii) electrostatic forces,and (iii) contact area effects; the larger the area, the greater the

total attractive force (Bott1995). Microbes have a natural affinityto surfaces. Numerous authors have reported the adhesion of bac-

teria to processing surfaces (for example, Geesey and others1996;Benezech2001; Zhao and others 2007). If left to proliferate, in-

dividual microbes can grow into biofilms (adhesive and cohesivecommunities of microbes) that become difficult to remove from

a surface (Jefferson2004). Garrett and others (2008) summarizethe occurrence of biofilms in industry, fouling mechanisms and

methods of observing and probing structures. The adhesion of

organisms usually follows the formation of a conditioning layerof protein (Lorite and others 2011) that makes subsequent adhe-

sion and biofilm formation easier. The sequence of events thatoccur during film formation is discussed by Busscher and others

(2010) and Chen and others (2010) who show the kinetics of filmformation.

Other researchers have studied yeast adhesion and proliferation

on processing surfaces, critical in brewing operations. Reynolds

and Fink (2001) proved that Bakers yeast can initiate biofilm for-mation on plastic when in a low-glucose environment. Mozes andothers (1987) found that yeast could attach and form a dense layer

of cells on stainless steel and aluminum at pH 3 and pH 5 and 6.The authors also determined that a dense layer of yeast cells would

attach to glass and plastics if the negative charge was reduced bytreatment with ferric ions. The system pH will determine the

surface charge of both the substrate and the adhering species. Theisoelectric point, the pH where the material carries no charge, will

also vary with surface and organism. Yeast has also been found byother authors to readily attach to stainless steel, plastics, elastomers

(Guillemot and others2006), and glass (Mercier-Bonin and oth-ers 2004), all of which are used extensively in FMCG industries.

The effect of cleaning parameters on yeast removal from processsurfaces is discussed in later sections.

Product contact surface finishes with a roughness (Ra) valueof up to 0.8 m are recommended (Lelieveld and others 2005),

which is often called 2B finish of stainless steel. Surface rough-ness exists in 2 principal planes, one perpendicular to the surface

described as height deviation and one in the plane of the sur-face described by spatial parameters. The effect of average surface

roughness height, Ra, and surface topography on microbial re-tention has been investigated most thoroughly. Hilbert and others

(2003) investigated the effect of stainless steel roughness (Ra0.9 to0.01 m) on retaining various microbes. The surfaces also had a

conditioning layer. The retention of microbes (measured by indi-rect conductometry) on the conditioned surfaces was similar over

the range ofRa tested.Cluett (2001) investigated the effect of stainless steel surface

finish on the fouling and cleaning of a beer fermenter. Surfacefinishes investigated included 2B milled stainless steel and me-

chanically polished 120 grit, 240 grit, and electropolished (EP)stainless steel. The top surface of the fermenter was half EP, half

240 grit, and the cone was EP. The cylinder of the vessel hadall finishes, one quarter of the vessel from top to bottom repre-

sented by each surface finish. After lager beer fermentation lasting12 d, Cluett (2001) found that all surfaces fouled similarly andthe level of deposition was heavy. He also found that all the sur-

faces cleaned similarly using a similar CIP regime with a spray ball


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(prerinse, caustic, water, acid, water, and sanitizer). However, thenumber of viable microbes was found to decrease in the cone at

the bottom of the vessel.Gallardo-Moreno and others (2004) investigated the effect of

surface roughness by comparing yeast adhesion to glass (Ra 0.8

m and hydrophilic) and silicone rubber (SR) (Ra 0.61 m

and hydrophobic). The authors found larger adhesion rates forSR, and at 37 C rather than 22 C. Whitehead and others

(2006) investigatedPseudomonas aeruginosa(rods of 1 m width and

3m length) andStaphylococcus aureus(1 m sphere) retention ona titanium dioxide surface: smooth with defined surface features(pits) of 0.5m.S. aureuscells were removed more easily from the

smooth surface, whereasP. aeruginosacells were removed more eas-ily from the defects. Whitehead and Verran (2006) also reviewed

the effect ofRa and topography on microbial retention. Researchsuggests that surfaces with a Ra value close to the cell size see

increased retention on the surface. For example, yeasts were foundto require larger defects (5m) for retention and smaller daughter

cells were retained in smaller defects (2 m). Rod-shaped cellsseemed to orient themselves in grains and grooves of similar size.

Preventing fouling

If fouling were not to occur, there would be little need forcleaning. Broadly speaking, 2 methods for preventing fouling have

been approached in the literature:

(i) Functional surfacesFor example, smooth surfaces with spe-

cific finish, topography, hydrophobicity, or surface charge.Nonstick surfaces are designed to have a specific surface

energy to minimize fouling.(ii) Processing alterationsFor example, changing product flow

characteristics, holding times, transient times, and other pro-cess parameters designed to minimize fouling.

Process surface modification. A hygienic surface needs to besmooth, easy to clean, able to resist wear, and retain its hygienic

qualities. Stainless steel is the most common food contact materialused in the industry, being stable at a variety of temperatures, inert,

relatively resistant to corrosion, and it may be treated mechanicallyor electrolytically to obtain a range of finishes (Akhtar and others

2010). The wettability of a surface is dependent on its surfaceenergy. A surface with a high surface energy is hydrophilic and a

drop of cleaning fluid will spread over the surface. A low-energysurface is hydrophobic and a drop of water will not spread. Waterpartially wets glass and acrylic and does not wet Teflon (PTFE)

surfacesbut surfactants are often added to commercial cleaningagents to improve wetting. Wetting is determined by the nature of

both the liquid and the solid substrate. The cleanability (and disin-fectability) of stainless steel has been compared with those of other

materials, and is comparable to glass when cleaning microbes, and

significantly better than polymers, aluminum, or copper (Akhtarand others2010).

Microbes are known to readily attach to SR. Everaert and others

(1998) absorbed long fluorocarbon chains (Ar-SR-C8F17) to SRused in prosthetics in an attempt to reduce the number of adhering

microbes. They found that the initial adhesion rate ofStreptococ-

cusbacteria to the treated rubber was significantly reduced, from

around 2500 to 900 cm2 s1, without a conditioning film ofsaliva and 400 cm2 s1 with a conditioning film of saliva. The

adhesion rate ofCandidaspecies to treated rubber was also reducedcompared to untreated rubber.

Dhadwar and others (2003) investigated the effect of oligopep-tide treatment of glass (hydrophilic) and plastic (hydrophobic) on

yeast adhesion. Overall surface energy was 50 to 60 and 25 mJ/mfor cell adhesion on plastic and glass, respectively. Coating both

surfaces changed the free energy of the system resulting in a de-crease to 35 to 40 mJ/m for plastic and an increase to 30 to 40

mJ/m for glass. Yeast adhesion was significantly reduced on theplastic surface coated in the peptide and increased on the glass

surface. Changes in surface roughness and hydrophobicity due tothe coating will also have contributed to adhesion.

Quain and Storgards (2009) mentioned the testing of func-

tional materials in the lab and in brewery dispense lines suchas hydrophobic fluoropolymer coatings, photocatalytic titaniumdioxide coatings, and the inclusion of antimicrobial silver ions

(0.042%) in stainless steel. The latter was shown to reduce thenumber of adhering bacteria by 99% compared to normal stainless

steel. However, the effect decreased with time.The influence of surface energy on adhesion is well known in

marine and medical biofouling and is characterized by the Baiercurve (Baier1980). This curve demonstrates the weakest adhesive

strength of bacteria to be at surface energies of around 25 mN/m.Equations defining possible minimum adhesion energies be-

tween a deposit and the surface have been developed. The follow-ing equation has been derived:

LWS =

1

2

LWD +

LWF

(3)

whereLWS , LW

D , and LW

F are the Lifshitzvan der Waals (LW)

surface free energy of the surface, deposit, and fluid, respectively,and which can be quantified from contact angle measurements

(Zhao and others2004). Liu and others (2006) studied the inter-actions of 316 L stainless steel with baked and unbaked tomato

deposit: a minimum removal energy range of 20 to 25 mN/m wasfound in both cases. Either side of this surface energy range, the

adhesive strength of the deposit on the surface increased. Zhaoand others (2005a) found that stainless steel surfaces coated with

Ag-PTFE reduced Escherichia coliattachment by 94% to 98%, com-pared with silver coating, stainless steel, or titanium surfaces. A sur-

face with energy of 24.5 mN/m roughly matching the theoreticalminimum adhesion energy ofE. coli, 28.3 mN/m, was achieved.

Composite coatings using nickel, phosphorus, copper, and PTFEwere also used by Zhao and others (2005b) and Zhao and Liu

(2006) to create surfaces with specific energies shown to reducebiofouling. A major EU project (MODSTEEL) developed andstudied a wide range of surfaces and how they might reduce foul-

ing from milk (see Santos and others2004and Rosmaninho andothers2007).

Work by Pereni and others (2006) confirmed the effect ofsurface free energy in minimizing P. aeruginosa adhesion to a

range of coatings including silicone, polished and nonpolished

stainless steel, PFA (perfluoroalkoxy polymer) and PTFE nickel,phosphorus, and aluminum composite coatings. The total surfacefree energy was in the range 17.2 to 48.3 mN/m, as shown in

Figure3(A). Minimum retention of bacteria was found at 20 to27 mN/m. Silicone had a surface free energy of around 20 mN/m

and the lowest colony forming units (CFUs) count. Surface freeenergy has been shown to be the parameter dominating E. coliadhesion over a range of metalpolymer coatings, and a minimumadhesion energy of 25 mN/m was found (Zhao and others 2007),

as shown in Figure3(B).Parbhu and others (2006) used a transient treatment to modify

a stainless steel surface. The treatment was present during the pro-cessing cycle and removed at high pH during alkaline cleaning.


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Figure 3(A)P. aeruginosaAK1 retention on investigated surfacescompared with the total surface free energy (adapted from Pereni andothers 2006). (B) Effect of surface free energy on E. coliadhesion(adapted from Zhao and others 2007).

The treatment was shown to reduce the interaction potential be-

tween stainless steel and phosphate anions resulting in significantreductions in fouling rates.

Akhtar and others (2010) compared adhesion of a range offood and personal care foulants to different surfaces. Particle tips

of different materials were attached to an atomic force micro-scope (AFM) cantilever to study the detachment from toothpasteand some confectionery components: Turkish delight, caramel,

and sweetened condensed milk (SCM). The study did reveal sig-nificantly different detachment forces for the same deposit from

different surface types (see Figure4). Caramel and SCM seemedto be more difficult to detach from glass than stainless steel. It was

possible to relate data from the AFM to measurements taken on

a millimeter scale using micromanipulation probes (Liu and oth-ers 2002,2006,2007). Akhtar and others (2012) describe furtherresearch using AFM to study food adhesion to process surfaces.

Process alterations. Dror-Ehre and others (2010) tested the ef-fect of biofilm development ofP. aeruginosawhen pretreated in an

aqueous solution of molecularly capped silver nanoparticles (MC-NPs). Under specific conditions, cells and surfaces incubated for

39 h at 37 C, Ag-MCNPs retarded biofilm formation even whena high percentage of planktonicP. aeruginosacells survived pretreat-

ment with Ag-MCNPs. At the various incubation times, a stable,low value of biomass was formed that could be easily removed.

The authors found, from micrographs of pretreated cells, that theintracellular material was pushed toward the peripheral parts of the

cell; a potential survival strategy. Treatment of water systems withsilver nanoparticles could prevent significant biofilm buildup.

Tse and others (2003) found that in a 2-phase (liquid-vapor)wort boiling system, the wall temperature did not significantly

affect the rate of fouling. Under conditions where vapor was con-densed at lower flow velocities (0.07 and 0.14 m/s), the initial

fouling phase was more rapid at the higher flow velocity. Theauthors found that the initial fouling rate was halved as the flow

velocity was doubled. These findings suggest that circulating fluid

at a fast flow rate would reduce fouling. The authors also foundthat at the lowest flow rate, 0.07 m/s, and highest temperature,170 C, the foulant appeared the most severe. The fouling also

had different makeup depending on its position in the column.At the top of the column, the deposit was light in color, smooth,

and patchy; at the bottom, the deposit was dark brown and mul-tilayered. The authors suggested 2 fouling mechanisms: chemical

reaction of species in the wort forming polymers and crystallizationof species from the wort due to evaporation at bubble nucleation

sites in nucleate boiling regions. Liu and others (2004) comparedfouling of 2-phase flow (liquid-vapor) and 3-phase flow (liquid

vaporsolid) during the evaporation of Gengnianan extract. Thesolid phase was added as inert solid particles. The 2-phase flow sys-

tem generated fouling in 15 h, whereas the 3-phase flow systemgenerated fouling after 60 h.

Modifying the process by using electric fields has also been dis-cussed. Ohmic heating occurs when an electric current is passed

directly through milk to heat it, rather than it being heated bysurface heat transfer. The process results in lower surface temper-

atures and less fouling initially. However, fouling in the bulk iseasily transferred to the surface, resulting in fouling (Bansal andChen 2006). Kim and others (2011) demonstrated that an elec-

tric field could be used to control membrane fouling withE. coli.

E. coli cell suspensions were treated by an electric field prior to

filtration. The flux of the suspension was maintained through-out the filtration period due to larger fouling particles reducing

cake resistance. Cell death also increased with increasing electricfield strength from 5 to 20 kV/cm. Flux of the untreated E. colisuspension decreased abruptly after the onset of filtration.

Xiaokai and others (2005) investigated the effect of electro-

magnetic treatment of water to minimize scale formation in thetubes of a plate heat exchanger (PHE). The technology is termed

electromagnetic antifouling (EAF). The treatment was shown toaggregate particles in the flow that led to reduced precipitation at

the wall.

CleaningNo economically viable fouling prevention method is yet to

be demonstrated in industry. Should one of the modified sur-

face methods prove economic, then the problem will be greatly

reduced. Understanding the cleanability of surfaces requires com-bining understanding of surface chemistry and engineering, thedeposit and the cleaning fluid (for a recent review of clean-

ability, see Detry and others 2010). Further research discussedhere considers the findings of studies relevant to optimizing

cleaning.One significant issue is determination of the correct cleaning

time. A deposit that has aged on a surface is more difficult toremove than fresh material on a surface, so cleaning is encouraged

after production. Aging of a particular soil type could make adeposit harder to remove from a process surface. For example, a

type 1 soil could become a type 2 soil over time and heating mayresult in a type 3 soil. Goode and others ( 2010) found that in


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0.0001

0.001

0.01

0.1

1

Caramel SCM Turkish

delight

Toothpaste

F/R(N/m)

Stainless steel

PTFE

Glass

Figure 4Force of attraction between stainless steel, PTFE (fluorinated low energy surface), and glass particles and different food materials obtainedusing AFM (from Akhtar and others 2010).F/Ris the force/probe radius with units of N/m.

beer fermentation vessels, there were 2 distinct deposit types to be

cleaned, classified as type A and type B foulants:

(i) Type AFormed during fermentation above the beer level

at the top of the vessel,(ii) Type BResidual yeast attached to the vessel wall and cone

below the beer level during emptying.

Type B fouling is shown by Salo and others (2008), as seen in

Figure5(A), while an example of type A foulant viewed from afermenter man way door at the top of the vessel is given in Figure

5(B). Type B fouling has a shorter aging time than type A fouling.As such, type B foulant can be removed by the falling film in a

tank, whereas type A foulant may require a larger impact forcefor removal or a combination of water and chemical rinses for

complete removal (Goode and others 2010). Similarly, Liu andothers (2002) found that the force required to remove a tomato

deposit from a surface increased with time until after about 200min of heating it remained constant.

Automated CIP has been widely applied in dairies, food pro-cessing, brewing, and wine processing for the last 50 y to return

the plant to a clean state (Stewart and Seiberling 1996). Dur-ing CIP, water and chemicals are circulated around the plant for

a prescribed duration (Tamine 2008). The CIP factors found todetermine cleaning can be described by Sinners circle, a circleof the cleaning parameters: mechanical action, chemical action,

time, and temperature (Lelieveld and others 2005). Cleaning canalso be dependent on geometry. In a pipe, the contribution of the

cleaning factors is equal. In a pipe dead leg, time determines clean-ing (Lelieveld and others2005). A number of attempts have been

made to try to incorporate computational models into the design

process, as shown by Asteriadou and others (2006) and Jensenand Friis (2005). This approach will become more important asunderstanding of the processes in cleaning increases.

Rheological characterization of materials enables their classifi-cation. Materials within a similar class may have similar cleaning

behavior, according to the classification by Fryer and Asteriadou(2009). Vinogradov and others (2004) characterized the rheology

of a dental plaque biofilm. Biofilm rheology has been viscoelas-tic, temperature-dependent and/or time-dependent (Rao 1999).

Characklis (1980) compared the elastic and viscous modules ob-tained for a biofilm and a cross-linked protein gel, fibrinogen. The

elastic modulus was the same order of magnitude for the proteingel and the biofilm. The cleaning map, presented in Figure 2 (Fryer

and Asteriadou2009), is a useful cleaning problem classification

tool and forms the basis for the structure of this review. Examplesof each deposit type include:

(i) Type 1: toothpaste, tomato paste, yogurt, shampoo, beer,wine, milk, and yeast.

(ii) Type 2: microbes and microbial films of bacteria, spores, and

yeast species.(iii) Type 3: milk, whey protein concentrate (WPC), cooked

SCM, starch, boiled wort, and egg albumin.

Some of the research that has considered the influence of clean-ing parameters in flowing systems on the removal behavior of

deposits is listed in Table 2 to 4. Table 2 details type 1 depositremoval studies, Table 3 details type 2 deposit removal studies,

and Table 4details type 3 deposit removal studies. The cleanedgeometry, effect of CIP parameters, and the method of deter-

mining cleaning effectiveness are listed in each Table. The ef-fect of flow has been studied both in terms of the Reynolds

number (Re) and the surface shear stress. Both may providefurther insight into the effect of removal behavior on flow

velocity.Milk processing is a large industry and fouling is a significant

problem, as both protein aggregates and minerals are deposited;Burton (1967) classified the proteinaceous deposit seen in pasteur-izers as type A and the mineral deposit seen at UHT temperatures

as type B. Reviews of dairy fouling research are presented byChangani and others (1997) and Bansal and Chen (2006). Pro-

teins have been identified as a major source of fouling deposits.Fickak and others (2011) found that increasing the protein con-

centration of whey protein increased the amount of fouling on a

pilot-scale heat exchanger. Holding of milk before heating sec-tions has been shown to aggregate -lactoglobulin in the holdingsections rather than the heating sections (de Jong and van der Lin-

den1992). Christian and others (2002) found that increasing themineral content of whey protein decreased the extent of fouling

on a PHE.WPC is often used in research studies to represent a milk fouling

deposit, because it is easier to handle and store than milk, and thefouling composition is thus easier to control and replicate. Robbins

and others (1999) compared the cleaning of milk and WPC froma PHE. They found that in the pasteurization and UHT sections

of the PHE, both materials fouled heavily. However, in the inter-mediate section, WPC also fouled excessively, whereas milk did


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A

Wall fouling

Contact

cone

B

t agar

Fermenteer

Gasket

T

v

(s

s

v

Type A foulin

vessel and th

samples had

scraped from

vessel)

g on the

he gasket

d been

the

Figure 5(A) 80 L stainless steel tank (0.8 m 0.4 mm) with residual yeast fouling attached to the wall and the cone. The wall was also sampled bycontact agar (adapted from Salo and others 2008). (B) Type A deposit seen at the top of a fermenter around the man way door and the gasket (Goode2012).

Table 2Some CIP studies of type 1 deposit.

Effect of Effect of CleaningDeposit Geometry flow or w temperature Effect Re determinant Reference

Toothpaste 1 m l ong, 2 OD, 316 Lss pipe (horizontal)

Increase flowvelocity (1 to 3m/s, decreasecleaning time.

Increasetemperature(from 20 C),decreasecleaning time(to a pointapproximately40 C).

Increase Re (4000to 250000)decreasescleaning time.

Turbidity reaches4 ppm.

Cole and others(2010)

Shampoo 316 ss plate ( 350 mmlong, 30 mm ID,18.3 mmED)(vertical flow cell)

(0.14 to0.47 m/s)higher flowvelocity, moreefficientremoval at thestart ofcleaning.

(31 to51 C),removal ofshampoo layersfaster at highertemperatures ascleaningproceeds.

Visual MSS andspectrophotom-etry

Pereira and others(2009)

Mustard glass T -piece ( variabledepth T,4 and 6cm)

Increase flowvelocity (1 to1.88 m/s)increaseremoval rate.

Above a certainReynoldsnumber, therecirculationzone lengthbecomesconstant.

Visual Jensen and others(2007)

Yeast cellsrehydrated(aged1 h atambient)

glass, polypropylene,and polystyrenesurfaces (210 90mm long) inhorizontal flow cell

Increase w,decreasenumber of cells.

Visual Guillemot andothers (2006)

(i) linearly forplastics

(ii)as a curve forglass

Tomato paste 316 L ss coupons(circular: 26 mm D)

horizontal flow cell

(0.7, 1.5, 2.3L/min) increase

flow rate, theeffect oftemperature oncleaning timedecreases

(30, 50, and 70C) increase

temperature,decrease thetime to removedeposit

(850 to 4800 Re)increase Re,

decreasecleaning time

Visual, imageanalysis, and

MHFS

Christian (2004)

OD= outerdiameter,ID = innerdiameter,ED = equivalentdiameter, ss= stainless steel,MSS=mechatronicsurface sensor, MHFS= microfoilheat flux sensor.

not. Compositional analysis revealed protein fouling from both

materials in the pasteurizer section. Increasing to UHT tem-peratures revealed milk fouling to become more mineral-based,

whereas the WPC fouling remained predominantly protein-based,suggesting comparison of milk fouling and WPC fouling is not

wise at UHT temperatures.Yeast can exhibit type 1 (if in contact with glass) and type 2 (if

in contact with stainless steel) cleaning behavior. Guillemot and

others (2006) found that yeast cells could be wholly removed from

glass using water but that yeast cells had strong adhesion to stainlesssteel. The wall shear stress required to remove 50% of the attached

cells from stainless steel, denoted as w50%, was 30 Pa, while forplasticsw50% ranged from 1 to 2 Pa.

The effect of CIP parameters on the removal of different de-posit types is discussed in the following sections. Even though

there is clear evidence that different deposit types are removed


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Table 4Selected CIP studies of type 3 deposit.

Effect Effect of Effect of CleaningSoil Geometry flow temperature Effect Re chemical/pH determinant Reference

Starch (withphosphorescenttracermolecules)

Continuous andabruptexpansions(ID 26mm,expandingfrom26 to38mm)

Local cleaningtime has aminimumwhere the wssshows amaximum andvice versa

N/A,constant Re> 25000investigated.

N/A. Constant0.5%.

Visual, imageanalysis

Augustin andothers (2010)

Cooked SCM(sweetcondensed milk)

316 L sscoupons(square: 3030 mm long)

Increase flowvelocity from0.25 0.5m/s, decreasecleaning timeatalltemperatures

An increase intemperature(40, 60, and80 C)revealed alineardecrease incleaning time

An increase inRe (6500 to27500)revealed adecrease incleaning timeaccording toPower law.

An increase from0.5 to 1.5%NaOH did notsignificantlyaffectcleaning timeat higher flowvelocities.

Visual, imageanalysis andMHFS

Othman andothers (2010)

Egg albumin 316 L ss coupons(circular: 26mmD)

Increase flowlesssignificant athigherchemical con-centrations.

30 C did notclean.Increasetemperature,decrease incleaning time.However, 50C removedmore depositat 1% NaOHthan 70 C.

Increase Re(1090 to4840)decreasescleaning time(at 50 C, 0.1to 1% NaOH).At70 C0.1%,increase Re,increasecleaning time.

No cleaning at0.1 wt%NaOH.Concentration0.25%to 3%(at 50 C, 2.3L/min)decreasescleaning time.Mostsignificant atlow flow (0.7L/min)

Visual, imageanalysis, andMHFS

Aziz (2008)

WPC 316 L ss coupons(circular: 26mmD)horizontalflow cell

Limited benefitto increaseflow velocityat70 C and1% NaOH.Benefit ifincrease flowat low concen-tration.

Increasetemperature(30 to70 C)decreasecleaning timeat all flowrates andchemical con-centrations(0.7, 1.5, 2.3L/min, 0.1%,0.5%, 1%NaOH)

Increasing Re(1090 to4840) onlybeneficial at0.1% NaOH.

Limited benefitto increaseconcentrationabove 0.5%.

Visual, imageanalysis, andMHFS

Christian (2004)

WPC 10 cm sectionsof sstubes (6mm ID 0.15

mm thickness)fouled incountercurrent heatexchanger

Increasing flowrate does notnecessarily

decreasecleaning time.It is importantto decayphase time.

Walltemperaturedid notaffect

the plateau.Increasing thebulktemperaturedecreasescleaning time.

Re500to 6500investigated.AsRe

increasescleaning timedecreasesgenerally.

N/A. Constant0.5%.

Thermalresistance usingMHFS and mass

Gillham andothers (1999)

OD= outerdiameter,ID = innerdiameter,ED = equivalentdiameter, ss= stainless steel,MSS=mechatronicsurface sensor, MHFS= Microfoilheat flux sensor, wss= wallshear stress.

0.55 m/s at 50 C. High flow velocity and low temperature in

the product recovery stage revealed the fastest cleaning times. Theresults suggested that the structure of the toothpaste film after the

product recovery stage is important in determining the overallcleaning time.

Product recovery can be done by pigging, in which fluid is

expelled from a system by the pig which could be solid, liquid,or gas. Solid pigs tend to be used in long sections of straight pipework where complex geometries do not need to be navigated; for

example, in crude oil pipelines to remove paraffin wax (Guo andothers 2005). The use of crushed ice (with a freezing point de-

pressant) in pigging systems has been developed and researched atthe Univ. of Bristol to remove starchwater mixes (Quarini 2002).

The void fraction of the ice is controlled so that the pig can navi-gate bends and T-pieces as well as straight pipe work. Applicationof this technology in the food and beverage industries is currently

limited. The ice is expensive to make and store. A company calledAeolus promotes a Whirlwind technology that uses compressed

air to remove soft deposits like fruit juice from pipe work with

bends (see www.aeolustech.co.uk). Application of this technology

in the food and beverage industry is also limited as the cost ofcompressed air is considerable. However, use of air in cleaning is

likely to increase in the future as water becomes more precious.

The effect of CIP parameters on type 1 removal

Schlusser (1976) compared cleaning behavior of 3 type 1 soils;beer, wine, and milk, illustrated in Figure 6. The products them-

selves were not heated. The cleaning profiles of each product weredifferent. Type 1 products can have a complex rheology, but are

often shear thinning, that is, they have an effective viscosity thatis a function of shear rate. The shear-thinning rheology of yogurt

was determined by Henningsson and others (2007) who also stud-ied the use of water to displace the yoghurt. For flow velocities

of 0.05 to 0.25 m/s, yogurt was observed and predicted to flowas a plug. If the process was set up so that yogurt flows as a plug,

at changeover, the mixing zone between the 2 yogurts would besmaller and yield reduced losses. Prediction of the mixing zone ofa HershelBulkley material with and without wall slip at 0.19 m/s


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Figure 6Cleaning characteristics of 3 type 1 products, beer, red wine,and milk with water (Schlusser 1976).

was also done by Henningsson and others (2007). With wall slip,it was predicted that the material would have a larger plug flow

region. However, predicting the flow of a high-viscosity plug or

wall layer is very difficult in practice.Flow and wall shear stress. Flow rate has an effect on the re-

moval rate of type 1 materials. The rheology of tomato paste has

been represented by the Carreau model (Bayod and others 2008),and the cleaning behavior of tomato paste in a flow cell has been

investigated by Christian (2004). At 30 C, it was found that by in-creasing the cleaning water flow rate from 0.7 to 1.5 to 2.3 L/min

(Re 750 and 4840), the cleaning time decreased. The relationshipappears linear. This was also true at 50 and 70 C.

Shampoo (SUNSILK R color radiant, viscosity quoted as 7000cP at 24 C) was rinsed by water from a stainless steel plate in a

vertical flow cell by Pereira and others (2009), and they found thatthe faster the initial flow rate (in the range of 0.14 to 0.47 m/s),

the more shampoo was removed from a duct. The same effect wasfound for removing toothpaste (a HershelBulkley fluid with a

yield stress) from a pipe (Cole and others2010). The effect of wall

shear stress (w) in the range of 0.5 to 10 Pa on toothpaste removalwas studied. Shear stress is affected by both fluid density and Re

that are both affected by temperature. Toothpaste cleaning time isgoverned by 2 removal phases by Cole and others ( 2010):

(i) Core removalwhere most of the product is removed as a

slug of product that can be recovered.(ii) Thin-film removalwhere the remaining annular wall film of

toothpaste is removed.

More recently, 3 phases were defined by a further investigation

of the effect of product recovery on cleaning of toothpaste usingwater (Palabiyik and others2012):

(i) Core removalthe first few seconds (a time comparable to

the residence time of the fluid in the system) where approx-imately half the product mass is removed and the remaining

toothpaste coats the pipe wall. Also called the product re-covery stage.

(ii) Film removalfurther product is removed up to about1000 s according to a process that is 1st order in deposit

weight/thickness, leaving a thinner but continuous film oftoothpaste remaining on the pipe wall.

(iii) Patch removalgreater than 1000 s, the continuous film isbroken up and only patches of toothpaste are left on the

surface. These are gradually eroded away according to zero-order kinetics.

It was found in both cases that the time to remove the remaining

patches of toothpaste was the rate-limiting step in overall cleaningtime. For shampoo, Pereira and others (2009) found that flowvelocity had the biggest impact on shampoo removal from the

flow cell at the start of cleaning, less so as cleaning progressed.Palabiyik and others (2012) found that the shear stresses induced

in the deposit during the core removal stage can affect the finalcleaning timecreation of a wavy film in the product removal

stage leads to much more rapid removal than if a smooth film iscreated. The authors also found that the remaining film thickness

was independent of pipe length, suggesting that removal is uniformthroughout the pipe, as also found by Cole and others (2010).

Temperature. For cleaning of tomatopaste in a flow cell, Chris-tian (2004) found that an increase in temperature decreased the

cleaning time by a linear relationship. Both an increase in temper-ature from 30 to 70 C and in flow velocity from 0.7 to 2.3 L/min

decreased cleaning time. Cleaning time decreased by a factor of 6from the lowest flow rate and temperature to the highest flow rate

and temperature.

For tomato paste cleaning, it was found that cleaning time wasalso correlated with Reynolds number (Christian 2004). As the Rewas increased from 800 to 4800, the cleaning time (tc) decreased

according to a power law: tc= 2 106 (Re)0.97. R2 = 0.81.

Jackson and Low (1982) found a critical Re of 6300 for cleaning

of dried tomato juice from a PHE, below which little deposit wasremoved.

Shampoo was rinsed at 0.14 m/s, at 31 and 51 C, by Pereiraand others (2009). After the initial bulk of shampoo was removed

from the flow cell, it was found that the removal of shampoolayers occurred faster at higher temperatures. For toothpaste, Cole

and others (2010) found that an increase in the water temperaturefrom 20 to 40 C decreased the cleaning time; however, increasing

the temperature above 40

C did not decrease cleaning time anyfurther. The same effect may occur when rinsing shampoo; the

investigators did not exceed a water temperature of 51 C in theirexperiments.

Cole and others (2010) found that for toothpaste cleaning (fromvarious length scales and diameters), a dimensionless cleaning time,

c = tcu/d (wheretcis the cleaning time and dis the pipe diam-eter), could be plotted as a function of Re, as a power law model:

c= 9 107 (Re)0.78; with a similar fit, R2 = 0.84. Palabiyik

and others (2012) found that temperature had a greater effect ontoothpaste film removal than flow velocity, and fitted the data.

Design. The velocity of 1.5 m/s is the flow velocity most oftenreported to clean pipe lines effectively in industry CIP (EHEDG

1992). This is, however, anecdotal with no theoretical justifica-

tion (Changani and others1997; Tamine 2008). In industrial pipesystems, there are, however, more complicated geometries such asbends, valves, and T-pieces. It raises the question: does increasing

the flow velocity decrease the cleaning time of other geometries?This gives a better indication of the effect of flow on the cleaning

time of a whole system.Jensen and others (2007) filled a variable depth upstand or

downstand (also called a T-piece) made from glass with com-mercially available mustard and rinsed with ambient water. The

geometry used in the study is shown in Figure 7 and is in thedownstand position. The downstand depth was tested at 4 and 6

cm. The flow velocity was increased from 1 to 1.88 m/s to definethe effect on cleaning the T-piece. Jensen and others ( 2007) found


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Figure 7Downstand geometry used for investigating the influence ofdifferent flow rates during CIP (flow was from left to right) (from Jensenand others 2007).

that:

(i) Increasing the flow velocity increased removal rate. How-

ever, the authors suggested that this was more likely dueto greater acceleration of the water at 1.88 m/s into the

T-piece. At the lower flow velocities, flow had not fullydeveloped before entering the T-piece.

(ii) Some areas of the T-piece were harder to clean than others.The position in the downstand most difficult to clean was

always located in the same position (see Figure8, shown asa downstand).

As expected, the top of the downstand was difficult to clean.However, an additional area located on the downstand pipe was

always the last part to be cleaned in all the experiments, regardlessof velocity. Jensen and others (2007) used computational fluid

dynamics (CFD) simulations to predict the wall shear stress in the4-cm downstand. Their CFD findings are illustrated in Figure

8(A) to 8(C) where blue is low wall shear stress (0 Pa) and red ishigh wall shear stress (5 Pa). As the flow velocity was increased,

the blue area decreased in size. Within these simulations, the areamost difficult to clean, the center of the downstand, is identified.

Increasing the flow rate does not improve cleaning of this area.The wall shear stress achieved at this position is low at all 3 flowvelocities. The other areas hardest to clean are circled.

Jensen and others (2007) examined the effect of pulsed flow inthe downstand. They found that pulsing flow only affected the

cleaning time of the 4-cm-depth T piece, not the 6-cm-depthT piece. They compared cleaning at 1 m/s (v1) and 2 m/s (v2)

and pulsing at 15 s (p1) and 30 s (p2). The cleaning time of the

4-cm downstand was longer when rinsed at 1 m/s than whenthe flow was pulsed. However, rinsing the downstand at 2 m/sgave the quickest cleaning time. The authors concluded that at

turbulent Re, the area of the recirculation zone in the T-piece didnot change. A recirculation zone is typically located after a pipe

expansion and depends on Reynolds number and the expansionratio. At lower Re (less than 10000 in this case), the length of the

recirculation zone may change; hence, cleaning times are shorterfor pulsed flow at 1 m/s than using constant flow at 1 m/s.

Jensen and Friis (2005) used CFD simulations to predict thecleanability of a mix proof valve fouled with B. stearothermophilusspores in accordance with the EHEDG standard cleanability test(EHEDG 1992; Timperley and others 2000). In the EHEDG

test, the apparatus is filled with sour milk and/or spores. An areadifficult to clean is defined as an area that produces yellow agar

in 3 consecutive tests (EHEDG 1992). Yellow agar shows thepresence of spores. The study revealed that the valve was easier to

clean than the radial flow cell (detailed by Jensen and Friis2004).The study predicted that a critical wall shear stress of 3 Pa was

necessary in both systems to ensure cleaning; however, areas ofextremely low wall shear stress and some areas of wall shear stress

higher than 3 Pa had spores remaining. The authors concluded

that wall shear stress was not the only factor governing cleaningin this case. As spores are more likely a type 2 soil, this conclusionseems logical.

Benezech and others (2002) rinsed spores in custard from aprogressive cavity pump (a type of positive displacement pump)

using a standard CIP operation in 2 configurations (i) with an axialexit pipe, where custard was pumped out of the top of the pump

body on the same axis as entry, and (ii) with a tangential exit pipe,custard was pumped out of the body at the side off the axis of

entry. The CIP consisted of a prerinse at 0.5 m/s for 6 min; 0.2%NaOH rinse at 1.5 m/s, 60 C, for 10 min; intermediate rinse at

0.5 m/s for 6 min; 0.2% HNO3 rinse at 1.5 m/s, 60 C, for 10

min; and final rinse at 0.5 m/s for 6 min. The group found that in

the tangential setup, all parts of the pump were cleaned to the samenumber of CFU/cm, approximately 10 CFU/cm2. The authors

defined a high level of hygiene as counts less than 18 CFU/cm2.In the axial set up not all components were cleaned to the same

level. There was an increased number of CFU/cm2 in the pumpbody and gaskets (>18 CFU/cm2).

To clean tanks, spray devices typically called cleaning heads areused. The design of a cleaning head is of paramount importanceto be effective in cleaning. There are 2 main choices:

(i) Static cleaning headsThese devices spray cleaning fluid ontothe tank surface from a fixed position. The effectiveness of

the cleaning head depends on cleaning fluid flow rate andthe size and pattern of the holes.

(ii) Dynamic cleaning headsThese devices spray cleaning fluidonto the tank surface using larger pressures, around 5 Bar

(resulting in large wall shear stresses and direct impact force),and rotation to ensure full vessel coverage. The effectiveness

of the cleaning head depends on the cleaning fluid pres-sure/flow rate to ensure that the preprogrammed pattern isachieved.

Examples of commercially available cleaning heads of both typesare shown in Figure9. Increasing the impact force of a jet stream

of fluid onto a surface can overcome large deposit hydration timesand reduce cleaning times. The fraction effect of time, physical

action, temperature, and chemical action delivered to the tank bya static cleaning head (spray ball) and a dynamic cleaning head

(high-pressure cleaning head) are given in Figure 10 (Tamine2008). For spray ball cleaning, time is required to achieve depositremoval. Cleaning time is required to achieve product removal

using a static head, and mechanical action is required to achieveproduct removal using a dynamic cleaning head. Dynamic heads

enable cleaning behaviors that are less reliant on contact timewith the chemical at high temperature. A type 3 soil could be

cleaned in a similar time as a type 1 soil. It should, however, benoted that impingement jets from a rotary device or from many

small jets in a static device may cause corrosion problems due torouging, from small iron particles worn from the orifices of

the thin walled static spray devices that then deposit on the tankwall.


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A B C

Figure 8CFD simulations of the flow field in 4 cm downstand T piece at (A) 0.5 , (B) 1, and (C) 2 m/s. Blue is low wall shear stress (0 Pa) and red ishigh wall shear stress (5 Pa). White represents wall shear stress in excess of 5 Pa. Water enters the section from the right and exits the T section onthe left represented by the arrow in (a) (adapted from Jensen and others 2007).

A B C

Figure 9Commercially available (A) spray ball static device (GEA, Warrington, U.K.), (B) rotary spray head dynamic device (Alfa Laval, Minworth,U.K.), and (C) rotary jet head dynamic device (Alfa Laval, U.K.).

Morrison and Thorpe (2002) defined the wetting rate at the

mass flow rate (kg/s) required to completely wet a surface ofwidth W (in meter). Wetting rates achieved by single jets from

a spray ball were 0.1 to 0.3 kg/ms. The act of removing depositfrom a vessel involves initial wetting and subsequent softening

(or dissolution) of the deposit, followed by complete removal byfurther impingement. Morrison and Thorpe (2002) measured the

dimensions of the wet area by the impaction of single water jetsonto a sheet of painted acrylic for a range of pressures and distances

from spray balls of different sized holes. They found that if thejet directly impacted the area to be cleaned, then this area was

cleaned within 60 s. The point of impact was smaller than thetotal area being wetted; however, certain areas were not cleaned

by the spray ball. The width of the falling film from the pointof impact remained the same size throughout rinsing. Jet breakup

was observed at 45 C, which increased the distribution of thejet and cleaned a larger area. An interesting model for the flow

behavior of jets is given by Wilson and others (2012).

The effect of CIP parameters on type 2 and type 3 depositremoval

Type 2 deposits can be viscoelastic, temperature-dependent,and/or time-dependent (Rao 1999). Type 3 deposits tend to be

thermally induced and precipitate from the process stream onto theheat exchanger surface over time. For example, wort is a complex

fluid with several components that change structure and solubilityupon heating, including carbohydrates, proteins, vitamins, miner-

als, and lipids. The deposits formed during wort boiling are solid

and dissimilar to the process stream (Tse and others2003).Membrane cleaning. There are many types of filtration pro-

cesses in food and beverage manufacturing operations. The foulingof membranes alters permeability and selectivity and can be char-

acterized by increased pressure differential and decreased mem-brane flux. Membranes used in the food and bioprocess industries

include reverse osmosis (RO), nanofiltration (NF), ultrafiltration(UF), and microfiltration (MF) (Cui and Muralidhara 2010). In

the brewing industry, beer is clarified using MF in which yeastreadily fouls the membranes. Membrane cleaning is complex as it

is necessary to both remove the surface layers and open the poresin the structurethis must be done without the cleaning agent

damaging the material.G

uell and others (1999) found that when yeast cells were present

on cellulose acetate membrane (CAM) as a layer (yeast cake), theyeast was believed to have formed a secondary membrane. In-

creasing the thickness of the yeast cake reduced permeate flux andprotein transmission through the membrane. Increasing the yeast

concentration in the feed solution resulted in lower fluxes andprotein transmission through the CAM. Hughes and Field (2006)

discussed the fouling of MF and UF membranes with yeast at sub-critical fluxes where fouling is negligible. For the MF membrane,

the rate of fouling increased with increasing feed concentration,increasing membrane pore size, and decreasing shear stress. The

UF membrane could not be cleaned effectively.Mores and Davis (2002) examined the effect of pulsing flow

through a CAM to clean it. They found that the flux increased


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Figure 10The fractional importance of different factors: time, coverage,physical action (impact), temperature, and chemical action (chemistry)required for effective tank cleaning by (A) spray ball and (B) rotary jethead (adapted from Tamine 2008).

with increasing shear rate, back pulse pressure, and back pulse

duration. At higher shear rate and back pulse pressure, multipleshort back pulses were more effective in cleaning the membrane.

At low shear rate and back pulse pressure, fewer longer back pulseswere more effective. Longer, weaker back pulses led to the highest

recovered fluxes.

Shorrock and Bird (1998) fouled a MF membrane (hydrophilicpolyethersulfone, 0.1 m pore diameter), with yeast cake. Waterrinsing was found to remove most of the deposit and an increase

in temperature from 30 to 60 C was found to decrease foulingresistance (at 0.74 m/s cross-flow velocity (CFV)). At 40 C, us-

ing NaOH as optimum concentration, there was optimum fluxthrough the membrane, 0.01% to 0.025%. Formulated sodium hy-

droxide solution was found to restore membrane flux completely.Cleaning of MF membranes with WPC was considered by Bird

and Bartlett (2002) using a flat plate stainless steel membrane andby Blanpain-Avet and others (2009) using a tubular ceramic mem-

brane. An optimum alkaline detergent concentration of 0.02%NaOH was found to give maximum flux after cleaning of the stain-

less steel membrane at 50 C, 1.67 m/s. Increasing the CFV from1 to 6 m/s decreased fouling resistance of the ceramic membrane

and gave the least amount of fouling present on the membraneafter 20 min.

Water rinsing of hard surfaces. For the type 3 deposits WPCand egg albumin, Christian (2004) and Aziz (2008) found that

neither deposit was removed with water rinsing at the temperaturesand flow velocities investigated; 30 to 70 C and 0.7 to 2.3 L/min.

The authors determined that chemical action was required for their

removal.Guillemot and others (2006) rinsed rehydrated Saccharomyces

cerevisiae cells from stainless steel in a flow cell over a wall shear

stress range of 0 to 80 Pa. They found that as the wall shearstress was increased, the number of cells remaining on the steel

decreased. However, only a 10% reduction in the number of yeastcells was achieved in this range of wall stress. Goode and others

(2010) rinsed aged yeast slurry from stainless steel coupons usingwater in a flow cell, and they found that increasing theflow velocity

did not significantly affect the amount of deposit removed fromthe surface at ambient temperature; this was over a wall shear

stress range of 0 to 1.24 Pa. Rinsing removed around 50% of thedeposit area. Goode and others (2010) also found that increasing

the temperature of the water rinse removed more deposit up to50 C with flow rate having a negligible effect. However, at 70C, decreased removal efficiency was observed, particularly at thehighest flow velocity, 0.5 m/s.

The yeast was aged at different temperatures and for differenttimes in the work by Guillemot and others (2006) and Goode and

others (2010); 20 and 30 C and 1 h and 5 d, respectively. The cellconcentration was also different at 0.0065 g/mL for Guillemot andothers (2006) and 1 g/mL for Goode and others (2010). These

findings suggest that fouling conditions dictate cleaning behavior,as already found from milk fouling (Changani and others 1997).

Chemical effects on the cleaning of type 2 deposits. Variousauthors have investigated the removal behavior of bacterial spores

from stainless steel. The effect of shear on adhesion has beenstudied using devices such as the radial flow cell (Detry and others

2007,2009) that can, when used correctly, allow ranges of shearsto be studied. Le Gentil and others (2010) cleaned Bacillus cereusspores from 316 L stainless steel pipes using 0.5% (w/w) NaOHat 60 C at 2.2 L/min. The test was carried out over 30 min.

As the cleaning time increased, the number of spores decreasedas expected. In the first 10 min, up to 70% of the spores were

removed, less so in the remaining 20 min. Lelievre and others(2002) investigated the removal of B. cereus spores from 304 L

stainless steel pipes, similar in length and diameter to the pipesused in the study by Le Gentil and others (2010) and 0.5% (w/w)

of NaOH was used at 60 C to rinse the pipe. In this study, theeffect of flow velocity and temperature was investigated over a 30

min clean. The researchers found that cleaning at 60 C removedmore spores than rinsing at 20 C at each 5-min time interval, at

the same flow velocity of 1.97 m/s. They found that increasing theflow velocity from 1.61 to 3.29 m/s (w= 17.45 to 68.95 Pa) at

60 C decreased the number of attached spores in the first 5 min.However, after this time, the contact time was more important

in removing the spores. The increased acceleration at higher flowrates may be controlling the number of spores removed in the first

5 min of cleaning, as found by Jensen and Friis (2004).Bremer and others (2006) investigated the effect of alkali rinses

and acid rinses (formulated and nonformulated) on removing abiofilm generated by recirculating skimmed milk powder in a CIP

skid for 18 h in 15 mm stainless steel tubes. There were a number


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of conclusions:

(i) Rinsing with 1% NaOH (for 10 min, 65 C, 1.5 m/s)

followed by 1% nitric acid (for 10 min, 65 C, 1.5 m/s)reduced the number of cells to a similar level than that found

after rinsing with only NaOH (at the same conditions).(ii) Formulated detergents (with surfactants, chelating agents,

and sequestrants) decreased cell numbers to the same levelas rinsing with NaOH (at the same conditions).

(iii) Addition of a surface-active agent to the caustic solution sig-nificantly reduced the number of cells compared to standard

CIP (NaOH and nitric acid in (i)).(iv) Nitric acid with surfactants removed significantly more cells

than just nitric acid.(v) Addition of a sanitizer step after CIP did not significantly

reduce viable bacteria numbers.

This suggests that the concentration of the alkali, the flow velocity,

and the temperature could be optimized to give the most efficientcleaning regime where all cells can be removed.

Goode and others (2010) investigated the effect of chemical onyeast removal from stainless steel coupons in a flow cell using 2%

Advantis 210 (1% NaOH equivalent). They found that increasing

the temperature from 20 to 70 C decreased the cleaning time.An increase in flow velocity at 50 and 70 C from 0.26 to 0.5 m/salso decreased the cleaning time; however, at 20 and 30 C, an

increase in flow velocity from 0.4 to 0.5 m/s did not significantlydecrease cleaning time.

Chemical effects on the cleaning of type 3 deposits. The effectof chemical cleaning of WPC from milk has largely been char-

acterized in the literature as uneven. The cleaning process has 3distinct phases seen by many independent researchers, for exam-ple, by Bird (1992), Gillham (1997), Grasshoff (1997), Tuladhar

(2001), and Christian (2004):

(i) Swellingalkali solution contacts the deposit and causes

swelling, forming a protein matrix of high void fraction.(ii) Erosionuniform removal of deposit by shear stress forces

and diffusion. There may be aplateau region of constant clean-ing rate, but this depends on the balance between swelling

and removal.(iii) Decaythe swollen deposit is thin and no longer uniform

so that removal of isolated islands occurs by shear stress andmass transport.

Many authors quote 0.5% NaOH to be optimal for WPC removal

from stainless steel, although the existence of cleaning optima hasnot been categorically proved in all cases. Bird and Fryer ( 1991)

found that increasing the NaOH concentration to 2% can pro-duce a deposit with a less open (dissolved) structure than at 0.5%,

thus lengthening the swelling phaseYoo and others (2007) and

Saikhwan and others (2010) explained the processes that underpinthis observation. Plett (1985) reported that a maximum cleaningrate occurs when cleaning with detergent. The contribution of

flow rate is hard to determine in chemical cleaning because bothshear stress imposed on the deposit and mass flow to the deposit are

dependent on the flow rate. In general, the higher the flow rate,the shorter the cleaning time. Timperley and Smeulders (1988)

found that the cleaning time of a PHE decreased with increasingflow velocity from 0.2 to 0.5 m/s. There are arguments supporting

higher flow rates that create turbulent conditions. This is becauseturbulent conditions are known to make the flow patterns of the

microscopic boundary layer unstable. However, Bird and Fryer(1991) found that there was no significant change in cleaning rate

when moving from laminar to turbulent flow. Disruption of theboundary layer is further discussed in Section 4.1. Generally in-

creasing the temperature decreases the cleaning time. Gillham andothers (1999) found that removal of whey protein deposits from

stainless steel pipes was strongly dependent on temperature (less sothe swelling phase).

SCM is an intermediate in the manufacture of some confec-tionary products, made by evaporating water from milk and adding

sugar to lower the water activity of the product. SCM has 70%

to 74% total solids of which 40% to 45% is sucrose (Fisher andRice1924) leaving 29% to 30% milk solids. In the study of Oth-man and others (2010), SCM was cooked for 4 h at 85 to 90 C

on stainless steel coupons and washed by chemical cleaning in aflow cell. It was found that increasing the flow velocity from 0.25

to 0.5 m/s decreased the cleaning time at all temperatures. Anincrease in temperature from 40 to 80 C decreased the clean-

ing time linearly. Interestingly, the authors found that increasingthe NaOH concentration from 0.5% to 1.5% did not significantly

affect the cleaning time at each temperature. This agrees withfindings for WPC cleaning that quote 0.5% NaOH as the opti-

mum concentration. It was the increase in temperature rather thanthe increase in chemical concentration that decreased cleaning

time.Cleaning time was plotted compared with Re for SCM at 1%

NaOH (40, 60, and 80 C) by Othman and others (2010) and at0.1%, 0.5%, and 1% NaOH (at 30, 50, and 70 C) for WPC by

Christian (2004) as shown in Figure 11(A) and 11(B). For WPC,the range of investigated Re was around 800 to 4840. There were

separate groups of data at each temperature that could not beplotted on one master curve. This suggests that temperature wasthe dominant parameter in controlling cleaning time. Christian

(2004) concluded that an increase in Re was only beneficial tocleaning time at low concentration. Jennings and others (1957)

suggested the existence of a threshold Re of 25000 for cleaning apipe surface of dry milk deposit before an increase in Re resulted

in increased cleaning rate. For SCM, the Re range investigated wasmuch higher, from 6500 to 27000. All the data collapsed onto one

curve. As the Re increased, the cleaning time decreased, suggestingthat Re was the dominant parameter controlling cleaning time.

Othman and others (2010) did find, however, that the effect ofRe on cleaning time became less significant as the temperature was

increased. Gillham and others (1999) found that tcwas proportionalto Ren, wherenwas in the range of 0.2 to 0.35 for 0.5% NaOH.

For SCM at 1% NaOH, tcwas again proportional to Ren where

n = 1.28 (R2 = 0.92).

The cleaning of egg albumin was characterized by Aziz ( 2008).Generally, an increase in temperature decreased the cleaning time.

However, at 1% NaOH, cleaning time was faster at 50 C thanat 70 C. Deposit was not removed at 30 C at any flow velocity

or NaOH concentration investigated. An increase in NaOH con-centration from 0.25% to 3% NaOH decreased the cleaning time

(at 50 C, 2.3 L/min); however, increasing the flow rate had a lesssignificant impact on cleaning time at higher chemical concentra-

tion. The author concluded a high temperature, mid to high flowvelocity, and mid-range chemical concentration appeared to be the

optimum, similarly to WPC cleaning optima. For egg albumin,the range of Re investigated was 1090 to 4840. There were sepa-

rate groups of data at 50 and 70 C that could not be plotted onone master curve. This suggests that temperature was the dominant

parameter in controlling cleaning time similarly to WPC.In Christian (2004), WPC cleaning experiments were con-

ducted using 0.5% NaOH at 30, 50, and 70 C and 0.7, 1.5, and


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Figure 11Recompared with visual cleaning time of (A) SCM at 40, 60,and 80 C using 1% NaOH (from Othman and others 2010) and (B) WPCat 30, 50, and 70 C, using 0.1%, 0.5%, and 1% NaOH (from Christian2004). Shading denotes the flow temperature: Black: 30 C, Gray: 50 C,and Open: 70 C.

2.3 L/min. Rd (the fouling resistance) is a measure of resistance

to the flow of heat to the sensor. Rdmeasured at the same flowrate reduced Rd more rapidly as the temperature was increased

from 30 to 70 C. An increase in flow rate from 1.5 to 2.3 L/minrevealed similarRdprofiles, suggesting that temperature dictated

the cleaning time in this case.For all type 3 deposits detailed here, temperature seems to be the

dominant contributor to cleaning time at both low and high flowvelocity and low and high concentration. Reaction rate, solubility,

and possible phase transitions (such as in fats) will all be affectedby temperature.

Novel Cleaning ApproachesThere have been various methods reported in the literature to

improve cleaning.

Increasing boundary layer disruptionVarious authors have considered pulsing flow in pipes to en-

hance wall shear stress at lower average flow velocities to enhancecleaning. Gillham and others (2000) showed that pulsing flow at

a relatively low frequency (2 Hz) enhanced cleaning of a tubu-lar heat exchanger compared to the same steady-flow velocity. A

pulsed flow creates high periodic accelerations of the liquid flow.The directional change in the flow can increase mass transfer of

the cleaning fluid to the surface, thus decreasing cleaning times.A pulsed flow is characterized by a stationary base flow on which

Figure 12Stationary flow and oscillating components of flow, wossymbolizes an oscillating fluid movement,wos,maxis maximum oscillatingfluid velocity, wstat is mean fluid velocity, andtis frequency of oscillation(Augustin and others 2010).

an oscillating fluid movement, wos, is superimposed, as illustrated

in Figure12.The intensity of a superimposed pulsation (wos,max +wstat) can be

quantified using waviness,W, the ratio of the maximum oscillating(wos,max) and the stationary or mean flow velocities,w:

W=wos,max

w(4)

w for an oscillation interval is defined by Augustin and others

(2010) as:

w =1

tos

tos0

w (t) d twithw(t) = wstat +wos

= wstat +wos,max. sin(wt)

(5)

A higher value of waviness is believed to result in a separationof the viscous sublayer and the formation of eddy currents; flow

reversal is critical. This effect can decrease the thickness of thelaminar sublayer at the pipe surface when applying a turbulent

flow. The temporary maximum velocity, wos,max, can occur nearthe pipe wall resulting in large shear rates and high wall shear

stresses. Bode and others (2007) characterized a linear decreaseof cleaning time with increasing waviness from 1 to 5. Below a

waviness of 1, there is limited flow reversal in the pipe and thecleaning time increases. Augustin and others (2010) compared the

cleaning rate of deposit at a flow velocity of 1 m/s ( Re 25000),where waviness was 0, and pulsing the flow, where waviness was 1.

They found that the amount of deposit in the pipe became asymp-

totic at 4 min using the pulsed-flow regime and 6 min using thestationary flow regime. Augustin and others (2010) have validatedCFD models accompanying their cleaning data. Phosphorescent

zinc sulfide crystals were used as an optical tracer enabling accuratecharacterization of flow patterns.

Alternative cleaners to reduce environmental impactThe efficacy of enzymes in cleaning has been investigated over

the last decade. Grasshoff (2002) investigated the efficacy of Sav-

inase, a protease (optimum temperature 50 C,pH 9.5), in cleaninga milk pasteurizer following a 15-min acid wash. Increasing the

concentration of the enzyme from 0.0025% to 0.05% at 60 Cshowed that residual soil was removed faster. In the plant, the


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heat exchanger was opened and inspected after 45 min of enzymecleaning and 6 min of water rinsing (30 L/min). The interior

surfaces were clean. Microbiological product samples collectedshowed no indication of microbial or enzyme contamination after

CIP.The use of commercial enzymes to clean UF membranes has

been discussed by Petrus and others (2008) and Allie and others(2003). Petrus and others (2008) used proteases to clean proteins

(BSA and -Lg) and defined an optimum concentration of 0.1%

for 60 min. The enzyme deposited on the membrane when rinsedfor longer than 60 min. Allie and others (2003) used proteases andlipases to clean abattoir effluent. Up to 55% of fouling was removed

with lipases, and up to 70% by using lipases and proteases and a fluxrecovery of up to 100%. However, to apply enzyme cleaning in

industry enzyme dosage, process control, and the overall economicburden need to be considered.

Orgaz and others (2006) tested the efficacy of fungal enzymes atbreakingPseudomonas fluorescens biofilm bonds. Out of the tested

enzymes, a T. viride enzyme (cultured on pectin) was most ef-fective at removing the biofilm by 84% ( 2%). The enzyme

was cellulose-pectinesterase-based. The least effective enzyme re-moved 19% ( 6%) of the biofilm and was mostly cellulose.

Other studies related to cleaning behaviorVarious authors have quantified parameters related to cleaning

behavior by other methods rather than in a flow cell or pilot plant.Some techniques used to infer cleaning data are discussed here.

Deposit shear. Simoes and others (2005) fouled stainless steelcylinders withP. fluorescensbiofilm in a bioreactor. Three cylinders

were rotated at 500, 1000, 1500, and 2000 min1 sequentially(ReA 2400 to 16100) for 30 s each in phosphate buffer to assess

the effect of rotation speed on biofilm removal. There was anoptimum ReAof 8100 where 45% of biofilm was removed. Either

side of this ReA removal was less and similar at around 15%.Cylinders were also submerged in different chemical solutions and

rotated at 300 min

1

for 30 min and then were rotated at 500,1000, 1500, and 2000 min1 sequentially in phosphate buffer

to test cleaning effectiveness. NaOH and sodium hypochlorite(NaClO) representing a CIP detergent and CIP sterilant were

investigated. Irrespective of ReA, NaOH and NaClO removed asimilar percentage of biofilm at the same concentrations (50, 200,

and 300 mg/L); however, at the highest concentration, 500 mg/L,NaOH removed approximately 5% more biofilm.

Demilly and others (2006) characterized the removal of yeast

cells as a function of wall shear stress from different stainless steelsurfaces using a radial flow chamber, in which flow trajectory

was from the center of the plate outwards toward the edges ofthe plate. This is similar to the impingement of a water jet on

a surface. Radial flow investigations may relate to the action of

a cleaning head in a tank, to provide a microscale method ofinvestigating water jets, and deposit removal. The steel surfaceswere micropolished and electrochemically etched with different

sizes of grain and depths. The number of cells remaining fromthe original number of cells was defined. Interestingly, the authors

found a threshold shear stress above which cells were removedregardless of topography; that detachment of yeast cells was faster

from etched steel than mirror-polished steel.

Deposit deformation and strength. Two methods have been in-dependently developed at Birmingham and Cambridge to deter-mine the strength and deformation behavior of soft-solid fouling

layers on hard surfaces immersed in liquid: the micromanipulationtechnique and the fluid dynamic gauging (FDG) technique, re-

spectively. The micromanipulation technique employs controlledstrain parallel to the deposit, where a T-shaped probe is pulled

across a horizontal circular plate at a constant height, removingthe fouling deposit by a shoveling action. The FDG was devel-

oped to measure the thickness of soft-soli

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