key words
Fluidized bed degreasing, Glass powder
Residual oil, Complex shaped components
M. Barletta1,*, A. Gisario1, S. Guarino1, V. Tagliaferri1
FLUIDIZED BED DEGREASING (FBD) OF METAL COMPONENTS
Abstract
Degreasing is one of most important stages of modern transformation processes in industries
fabricating or assembling metal parts, such as in manufacturing of aircraft, appliance,
automobiles, electronics, and railroad equipment. Chemical degreasing processes mostly employ
chlorinated solvents in a liquid or vapour state in order to remove oils and oil-borne soils from
previously processed parts, such as chips, metal fines and fluxes. Nevertheless, increased
sensitivity to the environmental impact of cleaning agents is pushing scientists and technicians
towards the development of alternative solutions.
In this study, a relatively novel eco-efficient degreasing technique, namely Fluidized Bed
Degreasing (FBD) based upon a fluidized bed of hard particles has been proposed. In this system,
a bed of spherical shaped glass particles was taken in a fluidlike state in a confined fluidization
chamber by using a low pressure air flux. The resulting impacts of the fluidized particles on the
surface of targets to be degreased caused the removal of surface contaminants and the concurrent
accurate cleaning of the exposed surfaces.
In this context, a detailed experimental campaign was aimed at investigating the interrelationship
among FBD operational parameters and degreasing effectiveness, with particular interest towards
the analysis of target geometry and location inside the fluidized bed.
Consistent trends of residual oil according to FBD process parameters were plotted and the
influence of each individual operational variable understood. A related analytical model, basis for
the development of more sophisticated control modulus, was developed and verified by the
experimental findings. Finally, the reliability of FBD process even on complex shaped surface
like pipes and blind holes was assessed.
1. BACKGROUND
Cleaning processes remove soils and contaminants from the surface of
ferrous and non ferrous materials with variable levels of efficiency [1]. These
cleaning processes are used in almost all industrial sectors, such as metal
processing and machining, surface treatments, electronic and optical industries,
aeronautical and medical products manufacturing, … [1].
Many factors play a fundamental role in choosing the degreasing process.
1
Università degli Studi di Roma "Tor Vergata", Dipartimento di Ingegneria Meccanica,
Via del Politecnico, 1 - 00133 Rome (Italy)
*
Corresponding author e-mail: barletta@mail.mec.uniroma2.it phone: +390672507193
+3906202135
fax:
These factors include the chemical and physical properties of the soil to be
removed, the surface properties of the parts to be treated and the level of surface
finishing desired on them, the final destination of the parts to be treated, the
accuracy in cleaning operations, the capabilities of available facilities to perform
cleaning operations as well as the overall cost of the cleaning process. The
choice of the degreasing processes is strongly linked to all these factors, but, as
in the other stages of the modern transformation processes, the costs and the
cleaning accuracy play a decisive role.
Papers in the literature report many actually used solutions (mechanical,
chemical, thermal etc) [1-4] which present remarkable operative advantages in
the cleaning of solid substrates. Most of these solutions are highly inefficient if
many thousands of parts have to be cleaned simultaneously. Moreover, the
experimental trends reported [2-4] show that more accurate results are obtained
by using more expensive cleaning techniques in terms of the time they take to
obtain results. Therefore, laser and plasma cleaning [5-6], even if a high quality
treated surface is obtainable from them, are absolutely unsuitable for high
production volumes because of the large amount of operative time.
The only cleaning techniques suitable for high production volumes are
ultrasound cleaning and vapor degreasing [2-4]. Nevertheless, the most pressing
problem of these technologies lies in their use of solvents that have a severe
impact on the environment (trichloroethylene and perchloroethylene, water,
alcohol, hydrocarbons and fluorocarbons, …). In fact, the need to dismiss the
exhaust solvents after use is the causes of a growing problem related to the more
severe directives for this sector.
At the time of writing, vapor degreasing is the most frequently used
industrial technique [5-6]. It is ideal for removing oil and organic residues from
surface of parts presenting very complex geometrical shape. Moreover, at the
end of the cleaning process, parts degreased in chlorinated solvent vapors are
dry. Therefore, there is no need for an additional drying stage, as has to be used
in aqueous and semi-aqueous processes such as the ultrasonic assisted systems.
Nevertheless, as previously mentioned, the environmental directives make the
procedure to dismiss the exhausted solvent even more complex and expensive
and the control of the vapor emission from the plants more rigorous. So, due to
the growing pressure from market competition, there is a strong demand for
alternative degreasing techniques which guarantee the same advantages of the
vapor degreasing technique with less environmental impact and more
operational safety. These advantages should include low operative costs, a dry
part after the degreasing treatment, high volume of simultaneously treated parts,
high levels of operational efficiency, reliability and reproducibility, a high
degree of compatibility with different materials, and safe operative conditions.
2. FLUIDIZED BED DEGREASING
In this study, a novel and unprecedented eco-efficient degreasing
technique, namely Fluidized Bed Degreasing (FBD), based upon a fluidized bed
[7] of hard particles (mostly, glass beads) has been proposed. In this system, a
bed of spherical shaped glass particles with variable mesh sizes in the range of
100 to 800 micron was taken in a fluidlike state in a confined fluidization
chamber (namely, fluidization column [8]) by using a low pressure (always
lower than 100-150 mbar) air flux. Accordingly, the glass particles were driven
by fluidized air issuing from the lowest part of the fluidization column causing
the particles to impact on the metal substrate. The resulting impacts of the
fluidized particles on the surface of the target to be degreased caused the
selective removal of surface contaminants and the concurrent cleaning of the
exposed surfaces, without involving the use of any solvents and without
damaging or altering them.
3. THE AIM OF THE WORK
In this context, the purpose of this work was manifold: (i) the calibration
of a standardized measurement procedure of the residual oil still clung on the
surface after FBD process; (ii) the analysis of the correlation among FBD
process parameters and the effectiveness of the cleaning operation, (iii) the
development of a physical comprehensive model, describing the evolution of a
cleaning indicator according to FBD processing time and media; (iv) the study
of the influence of the target geometry and location inside the fluidized bed on
cleaning effectiveness.
In particular, a system based upon a UV spectrometer was first accurately
calibrated and, then, used to monitor the amount of residual oil still clung on
targets after the different stages of FBD process. The experimental tests
exhibited that well-defined cleaning standard could be obtained with low
treatment times by simply changing main FBD process parameters (i.e., media
flow speed and mesh size of grains). Besides, the environmental impact was
found to be extremely low due to the mechanism for degreasing the surface
depending on only very small grains of glass and air as its media for treating the
surfaces. Next, by detailed experimentation, the trend of residual oil according
to FBD process parameters was plotted and the influence of each individual
operational variable analyzed. A related analytical model, basis for the
development of more sophisticated control modulus, was developed and verified
by comparing it with the experimental findings. Finally, further experimental
tests showed FBD process was rather insensitive to the influence of target
location (particularly, to impact angle) and dimension on cleaning effectiveness.
This facilitates the contemporaneous low cost treatment of many items in short
time periods, guaranteeing, at the same time, cleaning with high level of global
efficiency.
A last set of designed ‘ad hoc’ experiments were performed to assess the
reliability of FBD process even on complex shaped surface like deep and blind
holes with different length to diameter ratios.
4. MATERIAL AND METHODS
4.1 Abrasive media
The media used in the degreasing treatment was a not sieved glass powder
of two different sizes: 200-400 and 400-800 m. Powder characteristics, in
terms of chemical composition, grain size and shape, hardness and density, are
reported in Table 1.
Aspect
Composition
Grain Size
Factor shape
solid
Na2O
70-73 %
K2O
13-15 %
CaO
0,2-0,6 %
MgO
3-5 %
Al2O3 0,5-2 %
200-400 m
400-800 m
0.95
Hardness
900 HV
Specific Weight
2,45-2,50 kg/dm3
Table. 1. Properties of glass powder used.
4.2 Materials
The metal targets employed during standard degreasing tests were made
from copper alloy (Oxygen-free silver-bearing Copper, UNS C10400) thin
sheets. Their standard dimensions were: 40x40x1 mm3. To study the influence
of target dimensions in FBD process, square metal specimens, respectively, 20,
40 and 80 mm wide and 1 mm thick were used. Finally, to study the influence of
target geometry in FBD process, targets shaped as blind holes and pipes, 200
mm long and 10, 15 and 20 mm as diameter were used. The choice of such
targets was also dictated by the necessity to show the efficiency of FBD process
even on geometries that require very complex paths of media to be cleaned.
Solvent refined severely hydro-finished paraffin base oils (HTC OIL SAE
10 ISO 32), typically used for fine cutting operations, was chosen to soil all the
metal targets employed during the present experimentation. The chosen oil was
high-boiling (>315.5 °C) with specific gravity of 0.8708 g/cm3.
Fig. 1. Fluidized bed unit.
Ub
Area=A
Hml
Q=UmlA
Qmf
H
Q=UA
Fig.° 2. Transition from the fixed bed to bubbling regime.
4.3 Fluidized bed system
Fig.° 1 schematizes the fluidized bed apparatus. It was composed of a
vertical fluidized bed unit made from Plexiglas so as to ensure that the process
condition would be visible during the treatment. In the lower part of the unit, a
homogenization section was equipped with an inserted air flux distributor
(porous plate) made from sintered bronze powders. The homogenization section
and the porous plate are used to produce uniform fluidization in the bed during
FBD process. The pressure drop and the temperature along the bed was
measured by using a set of probes placed at various levels along the flow line,
while the flow was monitored by means of an analogical rotating valve
flowmeter with a 0-10 V output. A ‘built ad hoc’ acquisition system was used to
monitor and store all the process data.
A rotary screw compressor (Quincy model QGB 15) 15 kw as maximum
powder, able to supply up to 120-130 m3/h as flow rate with an operational
pressure ranging from 0 to 10 bar, was used to feed purified air lacking in
moisture and oil to the fluidized bed unit. When air was passed upwards through
the bed of glass particles, the pressure loss in the fluid due to frictional
resistance increased with increasing fluid flow [1-3]. A point was reached at
which the upward drag force exerted by the air on the glass particles was equal
to the apparent weight of particles in the bed. At this point (i.e., minimum
fluidization), the particles were lifted by the air, the separation of the glass
particles increased, and the bed became fluidized. Increasing the amount of
supplied air caused the creation of large bubbles in the bed of air and solid
particles (Fig.° 2). This regime was denoted as bubbling regime [7] and
appeared to be the most promising regime for use in FBD process for the
purpose of cleaning dirty parts [7-9].
Minimum fluidization speed [7] was evaluated for the two glass powders
employed during experimental tests by monitoring the trend of pressure drop vs.
the air flow rate. The value achieved for the smallest glass grains was
approximately 4.5 m3/h and for the largest glass grains was approximately 5.6
m3/h. When working at a flow rate of approximately 8-9 m3/h the regime
presented the characteristics of a fully developed bubbling regime for both the
glass grain typologies. Further increase of the flow rate up to 15-16 m3/h
resulted in the fluidization regime turning into slugging regime [7].
4.5 Experimental plan
During first part of experimental analysis, three different process
parameters were identified and analyzed using a full factorial experimental plan.
Firstly, flow rate which accounts for the variation in the media impact speed on
the substrate to be degreased. Secondly, FBD treatment time which establishes
the treatment time of the part to be degreased. Thirdly, mesh size, from which
the influence of both the media mass and its diameter have on the effectiveness
of the degreasing process can be analyzed. To study these parameters, three
different flow rates (8, 12 and 15 m3/h) were employed. Furthermore, two
different media grain sizes were used: grade 20 (400-800 m) and grade 40
(200-400 m). In each case, FBD treatment times were ranged from 5 to 60 s.
However, the complete schedule of the experimental tests is reported in Table 2.
FULL
FACTORIAL
LEVELS
EXPERIMENTAL FACTORS
Treatment time [s]
Air flux
[m3/h]
Grain size
[m]
I
5
8
300-400
II
10
12
400-800
III
IV
15
30
15
-
-
V
VI
45
60
-
-
Table. 2. Experimental tests conducted.
During the second part of the experimental analysis, the influence of target
location inside the fluidized bed and of target dimension was analyzed. In
particular, three different target radial locations, five different target vertical
locations and four different angles between specimen and flux were
experimented. Besides, specimens with three different ratios (1/7, 2/7 and 4/7)
between their side and fluidized bed column diameter were experimented.
However, Table 3 resumes all the experimental tests performed.
I
II
III
IV
V
α
0
30°
60°
90°
Z
10
15
20
25
30
X
3,5
7
10,5
D/L
1/7
2/7
4/7
Table. 3. The experimental tests: target location and dimension
The third part of the experimental analysis was dedicated to the degreasing
tests of the complex shaped targets. As said in Section 4.2, pipes and blind holes
with three different ratio of their length to diameter (from 10 to 20:1) were used.
Table 4 resumes the last experimental tests performed.
Blind Holes
Pipes
Length, mm
200
200°
Diameter, mm
10, 15, 20
10, 15, 20
Table. 4. The experimental tests: target geometry
Each test reported in Table 2 to 4 was repeated, at least, 5 times in order to
investigate the reproducibility and reliability of experimental results.
4.6 Experimental protocol
The steps of experimental procedure were as follows: (i) pre-cleaning of a
standard target using combined cleaning techniques: vapor degreasing followed
by ultrasonic bath with solvent; (ii) calibration of the fluorescence system by
using the standard target through which it was possible to obtain a baseline
representing the ideal point to be reached by FBD process; (iii) uniform soiling
of the entire target surfaces with the standard oil by a system consisting of spin
coater PI-KEM Ltd (model KW-4A) provide with a fluid dispenser; (iv)
monitoring of oil amount onto the target surfaces by using the ‘built ad hoc’
optical desk; (v) execution of FBD tests according to scheduled experimental
plan; (vi) monitoring of oil amount still clung on target surfaces after every step
of FBD process.
Some cautions were taken to ensure the best accuracy of FBD tests. In
particular, before entering the fluidized bed column, each soiled target was
inserted in a holder made for the special purposes of this experimentation. The
system held the target to be treated in a fixed position, hence ensuring
standardized hydrodynamic conditions of the bed for all FBD treatments. In
each case, soiled targets were driven inside the fluidized bed unit by using a
pneumatic control system in which the vertical entrance avoided the target to be
treated impacting on the wall of the column itself. The movement system
allowed managing the vertical and horizontal location of the targets inside the
fluidized bed as well as their attitude (inclination with respect to the fluidized
bed vertical axis).
Fig.° 3. The fluorescence system: 1 lamp, 2. monochromator, 3 Collimator lens, 4. Phototube, 5.
Focalization lens, 6. Chopper, 7. Specimen, 8 Computer.
4.7 Description of the fluorescence system
To estimate the presence of residual oils still clung onto target surfaces
after FBD, the technique of fluorescence was used. For this purpose, oil with
remarkable fluorescent properties in UV field was chosen to soil the targets.
To study the oil fluorescence phenomenon, an appropriate system (Fig.° 3)
able to excite the oil and then to capture the subsequent irradiation was built. To
excite the oil, an UV spot light source Hamamatsu (model L9588-01) 200 W as
maximum power, able to irradiate with wavelengths in the range of 240 to 700
nm, was used as source of ultraviolet rays. The radiation emitted from the UV
spot light source was carried in a monochromator. The bundle from the
monochromator was then focused on the target with the aid of both a collimator
lens and a second lens capable of focusing. The presence of the monochromator
allowed to select a pre-determined wavelength (between 300 and 500 nm) to
excite the soiled target. The excited target emitted radiation that was then
captured by a collimator lens and after that sent to a lens capable of focussing.
The focused radiation was captured by a new monochromator and finally sent to
a phototube Hamamatsu (model R847) able to detect signals in the range of 185
to 850 nm as wavelength (420 nm as peak wavelength). The signal could be
read from the phototube and, with the aid of an acquisition system based upon a
National Instruments acquisition board (model SC2345), the relieved signal was
sent to a dedicated laptop that stored the experimental data. So, the emitted
fluorescence spectrum was recorded. A chopper was essential for this system as
it was able to periodically interrupt the ray in exit from the first monochromator
assigning a predetermined frequency that was then set up on the survey tools.
This means that the radiation could be isolated during experimental tests and so
troublesome phenomenon that would be produced from other light sources was
minimized. For such purpose, the chopper was placed between the first
monochromator and the first collimator lens. A great deal of attention was paid
to the alignment of the system components.
In order for the signal to be sufficiently powerful, the oil needed to be
excited to wavelengths that were not too high, so the wavelength chosen to
analyze the specimens treated with the fluidized bed was a signal superior to 6

mind that for industrial purposes the interval of wavelength between 400 and
440 nm is appropriate. In fact, in this interval the difference between the two
curves (cleaned metal and soiled metal) was approximately an order of
magnitude.
The calibration of the optical desk was carried out according the following
step: (i) a pre-cleaning of a standard specimen using combined cleaning
techniques: vapor degreasing followed by ultrasonic bath with solvent was first
performed; (ii) then, the cleaned specimen was monitored by the fluorescence
system in order to deduce a baseline for subsequent tests; (iii) afterwards, the
specimens were soiled with rigorously monitored amounts of oil (from 0 to 1 g
of oil per m2 of specimen surface). The oil was then uniformly dispersed by spin
coating all over the surface of the specimens; (iv) the level of soil achieved was
monitored using the optical desk to correlate the specific amount of oil on
specimen surface with the optical signal energy
5. ANALYTICAL DEGREASING MODEL
5.1 Power dissipation degreasing model
The model developed in this section relates to the mechanism of oil
removal from the surface of a workpiece during FB treatment. As previously
mentioned, this mechanism is linked to the abrasive action of grains, essentially
entrained by fluidization air or driven by the bubbles, which impact on the
surface of the workpiece causing the detachment of oil drops. The physical law
governing the removal of material is essentially energetic and, so, a threshold
level of energy is defined which activates the phenomenon.
The strength of adhesion to a solid surface can be measured directly by
using suitable force measurements, or it may be estimated from the
thermodynamic ‘work of adhesion’ value, Wa, a concept first introduced by
Harkins [12]. In a simple system where a liquid L adheres to a solid S, the work
of adhesion is defined as:
Wa   sv   lv   sl
(1)
where Wa is the theoretic work of adhesion and sv ,sl and lv represent the
surface tension for solid-vapor, solid-liquid and liquid-vapor, respectively. The
problem concerned with using Eq. 1 is that, of the three interfacial tensions,
only lv can be measured with any confidence since it is the tension between two
fluid phases, which, in this case, are the liquid and air. Tensions involving the
solid cannot be independently measured. One approach is to combine Eq. 1 with
the Young-Dupre’s equation
 lv cos    sv   sl
(2)
to provide a more useful expression of the work of adhesion:
Wa   lv 1 cos 
(3)
where is the contact angle that the liquid makes with the solid surface (Fig.°
4). Provided that  and lv can be measured experimentally, it is then possible to
use Eq.3 to calculate the work of adhesion.
Fig.° 4. Impact of a glass sphere on a drop of oil.
The impact of a glass sphere to remove an oil drop is represented in Fig.°
4. Moreover, the energy of the particle can be written as follow:
Ec 
1 2 1 4 3
2
mv   r v cos  
2
2 3
(4)
where  is the density of the particle impacting on the oil, r the radius, v the
velocity and  the angle with which the particle moves in relation to the
horizontal plane.
For the particle to detach oil from the surface the kinetic energy must be
equal to the work of adhesion:
Wa  W p
(5)
if heat and work connecting with flow of oil is disregarded.
The following equation can be obtained from Eq. 5:
1  4 r 3 v cos  2
2 rv 2 cos 2 
2
3
Wp 

3
r 2
(6)
The glass bead is effective only if its velocity exceeds a critical velocity.
Fig.° 5. Critical velocity vs. radius of particles for different angles of impact.
The critical velocity can be derived from Eq (6) as follows:
vc  k
3 lv 1  cos  
2 r cos 2 
(7)
Fig.° 5 shows the critical velocity vs. the radius of the particles for the different
angles of impact. The most favorable conditions were found at an impact angle
of 0°.
5.2 Oil removal rate
Oil removed by a single glass bead mrem depends on the radius of the
particle, the density of the oil o and on the length lc that the glass bead travels
before dissipating all its kinetic energy:
mrem  k (t )r 2  olc
(8)
In order to calculate oil removal rate, it is necessary to know the number
of particles impacting on targeted surface per unit of time. An expression of this
quantity is given in Eq 9:
3 A v
N  Ab vb N v  e 3 b b
4r  p
(9)
where Ab is the section of the column of the fluidized bed, vb the velocity of the
emulsion in the fluidized bed, Nv the numbers of particles per unit of volume, e
the density of the emulsion in the bed, p the density of the particles.
Nv 
3 e
4r 3  p
(10)
From Equations 8 and 9 an expression for the oil removal rate M can be
obtained:
3 A v A
M  e 3 b b s k t r 2 olc
4r  p Ab
(11)
where, As is the section of the target, vb  0.71 gDe the bubble rise speed and


De  1.49 D2 u  umf 
0.4
the equivalent diameter which depends on the diameter D
of the bed and the superficial speed u  umf  [7]. The efficiency k(t) depends on
time because it is strongly related to the level of oil on the surface. In fact, the
oil on the treated surface decreases with the FB treatment time so the thickness
that the sphere of glass can remove is therefore reduced (i.e., it becomes
smaller). Because of this phenomenon, the coefficient k(t) becomes lower with
time (see Fig.° 6).
Fig.° 6. The coefficient k(t) becomes lower with treatment time.
Fig.° 7. Calibration procedure.
6. RESULTS AND DISCUSSION
6.1 Calibration of residual oil measurement system
Fig.° 7 reports the experimental results of the calibration process of
residual oil measurement system. As can be seen, a linear trend was found to
relate the signal energy detected by the optical desk and the specific amount of
oil distributed on the target surface. A loss of linearity starts affecting the
experimental results for very low specific amount of residual oil on the target
surface, that is, for values lower than 0.1 g/m2. In that condition, the energy of
the optical signal is very weak and makes the fluorescence system not more able
to discriminate among different cleaning conditions. Therefore, being around
0.9 g/cm3 typical oil densities, the fluorescence system is able to quantitatively
appreciate oil films on the specimen surface with thicknesses starting from less
than 100 nm. Rather lower amounts of oil can be only distinguished (up to 10
nm) by the fluorescence system, but not quantitatively appreciated.
Fig.° 8. Fluorescence results at 8 m3/h and grain size 300-400 m.
Fig.° 8 reports the trend of the energy of the optical signal according to
wavelength  of the incoming UV radiation with the FBD processing time. As
can be seen, the trend reported for a 5-second-treated specimen is much closer
to the trend of a perfectly cleaned specimen rather then to the trend of a soiled
specimen demonstrating how highly the cleaning process effectiveness is even
in a very short range of FBD treatment time. Analyzing the other trends reported
in Fig.° 8 (treatment time variable in the range 10-60 s), a slower improvement
speed of the surface cleaning condition with the treatment time can be noted. A
sort of saturation effect of FBD towards the amount of residual oil on the
surface can be deduced. Nevertheless, the surface cleaning process
progressively proceeds towards the baseline (i.e., cleaned surface).
From such experimental data, it was possible to extrapolate the degreasing
curves that represent the amount of oil removed. By indicating the average
signal of the soiled target with Os, the average signal of the cleaned metal with
Oc, and the generic average signal at a generic time x of treatment with Ox, it is
possible to calculate the percentage of residual oil R on the surface of the treated
target:
R
Ox  Oc
Os  Oc
(12)
6.2 Analysis of FBD operational parameters
The curves of residual oil according to processing time with air flux and
media mesh size are reported in Fig.° 9. They were obtained from solving the
experimental optical signals by Eq. 12. It can easily be seen that with the
increase in degreasing time, the signal of the soiled metal draws near the signal
of the clean metal. As said in previous section, the rate with which the metal is
cleaned is very fast for low dipping time.
Fig.° 9. Comparison between experimental results and analytical model:
(a) 300-400 & 8m3/h, (b) 400-800 & 8m3/h, (c) 300-400 & 15m3/h, (d) 400-800 & 15m3/h
Watching data in Fig.° 9, two phases in FBD can be identified. The first
phase concerns short treatment time, for there is a strong difference in the
efficiency of the two systems, and the second phase, which starts after about 20
seconds, is characterized by the slow approach towards similar asymptotic
conditions for all the settings of FBD operational parameters. It is therefore
possible to formulate the hypothesis of an achievable asymptotic degreasing
level value.
Comparison of the experimental results reported in Fig.° 9 (a and b)
reveals that the efficiency of FBD and, in particular, the required treatment
times to approach to a full cleaning of targets surface are related to media mesh
size: the smaller the grain size the higher the efficiency of FBD treatment. This
phenomenon is probably related to the number of impacts the abrasive grains
make on the surface of the part to be treated. By keeping the flow speed
constant, the number of smaller abrasive grain impacts considerably exceeds the
number of the impacts achieved with large mesh size abrasive. In fact, this value
is strongly linked to the number of abrasive grains per unit of volume and per
unit of time transported by the air flux towards the surface to be cleaned: the
smaller the dimension of the abrasive grain the greater the number of the grains
in the air flux. Furthermore, the mechanism detaching oil from specimen surface
requires very small amount of energy to dislodge an oil droplet, so, even a small

dvg2 to
diameter (d) abrasive grain can provide enough kinetic energy
12
activate the above cited mechanism. Accordingly, the mechanism detaching oil
droplets from the soiled surface is much more effective when smaller mesh size
grains are used.
On the other hand, keeping the flow rate for the two glass powders
constant produces a difference in bubbling rise speed, that is, in the speed of the
particles driven by the bubble itself towards the surface of the target to be
treated [3]. In fact, the bubble rise speed ub and, therefore, the impact speed of
the particle driven on the specimen surface, are higher for the smaller particles
which are characterized by a lower minimum fluidization speed value umf. In
fact, bubble rise speed ub is expressed by:
ub  u 0  u mf  0.711 gd b
(13)
where the speed u0 remains constant as it represents the ratio between the
flow rate and the cross section of the tubular reactor, and, in the chosen regime,
the value of db, which represents the mean bubble size, is assumed to be
constant and approximately equal to the tube diameter.
Fig.° 9 (c and d) shows the results achievable by increasing the flow rate
from 8 to 15 m3/h and keeping the main dimension of abrasive grain constant.
An increase in flow rate causes further increase in bubble speed, that is, an
increase in grains impact energy on the surface to be cleaned, hence determining
a more efficient treatment process. Therefore, by dipping a part to be degreased
in a faster air-particle mixture, the impact of grains on the part dirty surface
creates a quicker cleaning action by dislodging and so detaching more
effectively the oil drops from the surface, acting in a similar way to a soft
indenter in a surface finishing process. In such a process condition, the air flow
was also found to cause the massive elutriation of oil drops detached from the
surface because of the lower density of the oil (0.8 g/cm3) compared to the
higher density of the solid particles (2.7 g/cm3). Therefore, the oil removed can
be collected by means of appropriate equipment sited in relation to the outflow
from fluidized bed unit. The iteration of this phenomenon by all the abrasive
grains effective impacts on the surface of the part determines the rapidity of the
degreasing treatment process.
6.3 The analytical model: comparison with experimental results.
The analytical model developed was compared with the experimental
results. The model described in the previous paragraph was calibrated by means
of the parameter k(t) using the experimental results obtained for the flux of 8
m3/h. k(t) represents a measure of the cleaning process effectiveness represented

t
by this analytical formulation k t   K 0e c .
Grain size
200-400
400-800
K0
0.139
0.038
c
12
23
Table. 5. The experimental coefficients for the flow rates of 8, 12 and 15 m 3/h.
Fig.° 10. Removal efficiency k(t) vs. treatment time for different grain size.
The expression constants K0 and c have been chosen so as to obtain the
best fit between the experimental results at 8 m3/h and the analytical model.
The constants calculated are reported in Table 5. Fig.° 10 reports the
removal efficiency obtained for different grain sizes. Subsequently, the model
was validated by comparing it with the experimental results obtained for
different process conditions (different values of air fluxes). The detail of
achieved results is reported in Fig.° 9. A good fit between experimental and
numerical data can be seen, particularly for shorter FB processing time. In fact,
the error related to the evaluation of the function k(t) is negligible in the first
part of FBD process, where the level of oil on the surface of the target is still
sufficiently high. In the second part of the process, the amount of oil on the
surface of the target decreases further and further causing serious and severe
complications in the attempt to predict the right value of k(t), being, in that
condition, the fluorescence system much less sensitive. Consequently, this
results in serious percentage errors in the determination of residual oil trends.
Fig.° 11. The influence of target location and dimension.
6.4 The influence of target location inside the bed and geometry.
Fig.° 11 reports the experimental removal oil ratio for targets located in
different locations inside the fluidized bed and for different ratio between
fluidized bed diameter and target side. As can be seen from experimental data,
just two ‘positional’ experimental factors were found to be influential on
degreasing effectiveness: radial and vertical locations. Impact angles of the
media onto the target surface were found to be not influential. This result can be
ascribed to the minor importance of the kinetic energy of impacts of each
abrasive grain on process effectiveness. As mentioned in Section 6.2, FBD
process efficiency is related to number of impacts of media and not to their
energy. Accordingly, changing impact angles do not influence the number of
impact. Just the kinetic energy is reduced according to the exposure angle of the
target surface to the incoming flux of media. As a consequence, no direct
relationship can be claimed between degreasing effectiveness and impact
angles. To the contrary, vertical and radial locations were found to influence the
degreasing process. In fact, going towards higher vertical location or moving far
from the middle of the bed toward the wall of the bed, the target goes towards
zone with less dense [7-8] emulsion between media and air. As a consequence,
less impacts of media onto the target surface takes place and this results in less
efficient FBD process.
A partial exception to the rule is represented by the experimental data
achieved for 100 mm as vertical location. In such case, the poor efficiency of
FBD process can be probably ascribed to the vicinity of the target to the porous
plate distributor. In that zone, the target is affected by the air jet outgoing from
the porous plate distributor, which produce a high irregular aerodynamic
behavior and uneven distribution of the media in the fluidization column. This
results in a minor efficacy of the media impacts on targets surface, thereby
causing a significant decreasing in FBD process efficiency.
Targets dimension was found to minimally influence FBD process
efficiency. No strong difference in FBD cleaning efficiency of differently sized
targets can be claimed, hence demonstrating the good flexibility of FBD system
and its applicability to cleaning of larger workpieces.
Figs.° 12 and 13 report oil removal factor for complex shaped target
geometry: blind holes and pipes with different length to diameter L/D ratio. As
can be seen, going towards higher FBD processing time, the oil removal factor
goes progressively towards lower values. For pipes (Fig.° 12), after 300 s as
processing time, a value of oil removal factor as low as 0.03 is approached,
thereby confirming the good efficiency of FBD even on such a complicated
geometry. For blind holes (Fig.° 13), after 300 s as processing time, the value of
oil removal factor is worth just less than 0.1. Therefore, FBD process
experiences some difficulties in performing cleaning process of blind holes.
This can be probably ascribed to the accumulation of media inside the blind
holes, which prevent further media to come, impact and exert their cleaning
action. In practice, the recess reduces the number of effective impacts of media
on targets surface to be cleaned, hence lowering the overall FBD process
effectiveness.
Fig.° 12. The influence of target geometry: pipes.
Fig.° 13. The influence of target geometry: blind holes.
By comparing residual oil factor for flat specimens and complex shaped
targets, it can be noted the best FBD efficiency on simple geometries. However,
as said, useful results can always be claimed even for complex shaped surface if
longer treatment time is waited for.
7. CONCLUSIONS
The definition of a new technique for the degreasing of metal targets
without using solvent at all has been investigated in this work. Fluidized bed
technology has been adopted, and the influence of the leading process
parameters on the degree of cleaning achievable has been fully investigated. The
experimental results demonstrate that fluidization technology can be applied in
surface cleaning with excellent performance in terms of oil removal rate on flat
surface (dipping time in the range of 5-60 s). Besides, only oil traces are
detected after 60 s as FBD treatment time.
The quantitative results have shown that FBD carries out its process until
it reaches an asymptotic cleaning condition for each choice of operational
parameters. Increase in FBD treatment time improves cleaning efficiency until a
characteristic FBD cleaning asymptotic condition is approached. The cleaning
effectiveness mostly was found to depend on media mesh size and flow rate. In
particular, employing smaller particle size and higher flow rate meant that the
asymptotic level of cleaning was reached faster. This aspect was strongly linked
to the active mechanism inferred, that is, the formation of oil drops due to the
impact of micro-glass beads on the surface to be degreased followed by the
removal of oil from the fluidized bed unit by means of the entrainment effect of
the air flow on the less dense oil drops.
In agreement on what has just been mentioned, increasing the flow rate
and decreasing media mesh size causes the number of impacts to increase, hence
producing faster cleaning actions.
Among positional parameters (target locations inside the bed), just vertical
and radial location were found to be influential on FBD process effectiveness as
the media distribution inside the bed is strongly related to those operational
parameters. In fact, moving the targets to be cleaned towards the bed wall or far
from the porous plate distributor means move them towards zone less dense in
cleaning media. Consequently, less effective impacts between media and targets
surface occur, hence reducing FBD overall efficiency.
Targets dimension was found to minimally influence FBD process
efficiency. No strong difference in FBD cleaning efficiency of differently sized
targets can be claimed, hence demonstrating the good flexibility of FBD system
and its applicability to cleaning of larger workpieces.
Target geometry was also found to influence FBD process efficiency.
Particularly, blind holes were found to be harder to clean, as its recess entertains
media, which act as shield for further impacts of fresh incoming media onto the
surface to be cleaned. This phenomenon strongly limits FDB process efficiency
on such geometries. Furthermore, by comparing cleaning levels reached on
complex shaped targets and flat specimens, it stands to reason that FBD process
efficiency is maximized when simple geometrical shapes are treated. However,
useful results can be achieved even on complex shaped targets if longer
treatment times are waited for, with residual oil factor being worth much less
than 0.1.
To conclude, FBD is very interesting even from an industrial point of
view. In fact, FBD can be easily scaled-up to an industrial dimension in order to
treat simultaneously many thousands of components. Further advantages of
FBD technique are the low cost of equipment and low energy consumption
(only related to the flow rate fluidizing the micro-glass particulate), the low
operation temperature (the treatment was performed at room temperature
avoiding all the problems related to the bad odor emitted by treatment requiring
the soil to be heated). Furthermore, after treatment the part is dry (no use of
drying equipment is required after the degreasing treatment), and by simply
using a system which collects elutriated oil and then burning or recovering it,
the environmental impact is definitely very low.
8. ACKNOWLEDGMENTS
It is our pleasure to thank Mr. Daniele Ceccarelli for assistance in defining
fluidized bed system and Dr. Roberto Pizzoferrato and Mrs. Giuliana
Intreccialagli for help in defining, in building and in the set-up of the
fluorescence monitoring system. Moreover, it is our pleasure to thank
Fornitecnica Srl for the interest they have shown in scaling up the plant. Lastly,
it is our pleasure to thank Clive Prestt of Prestazione OXFORD In Lingua
Inglese for editing and proof reading the English of this manuscript.
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