PROCESS AND DEVICE FOR PREDICTING COATING THICKNESS
A process and a device for prediction of the thickness of a layer of a coating or paint applied upon an object by dip painting. The paint layer thickness (h) at at least one point on the surface of the object ( 2 ) is predicted. A correlation between the paint layer thickness and the current density in the paint layer ( 3 ) is empirically determined. Further, a correlation between the specific resistance of the paint layer ( 3 ) and the current density in the paint layer ( 3 ) is empirically determined. Depending upon the value of the applied voltage, the electrical potential at the point is calculated. The current density, the paint layer thickness and the specific resistance of the paint layer ( 3 ) at the point following dip coating are calculated. For this the electrical potential at the point as well as two correlations are employed.
1 . A process for the prediction of the thickness (h) of a paint layer ( 3 ) at at least one point of the surface of an object ( 2 ), wherein the paint layer ( 3 ) is applied upon the object ( 2 ) by a dip painting, wherein the dip painting includes the steps:
dipping the object ( 2 ) into a dip basin ( 1 ), which contains a liquid paint,
producing an electrical field in the dip basin ( 1 ) by application of a voltage (U), wherein the object ( 2 ) functions as electrode and a counter-electrode ( 4 ) is present, which process includes the steps automatically carried out using a data processing unit:
calculating the electrical potential (Φ) at the point depending upon the magnitude of the applied voltage (U),
depending upon the calculated potential (Φ), calculating the current density (j) at the point, and
depending upon the calculated current density ( 3 ), predicting the layer thickness (h) at the point,
and including
emperically determining a coorelation between the paint layer thickness (h) and the current density (j) in the paint layer ( 3 ), and
emperically determining a correlation between the specific resistance (p_Paint) of the paint layer ( 3 ) and the current density (j) in the paint layer ( 3 ),
wherein the paint layer thickness (h) and the specific resistance (p_Paint) of the paint layer ( 3 ) is calculated at the point after the dip painting using
the electrical potentional (Φ) at the point and
the two empirically determined correlations.
2 . The process according to claim 1 , wherein a correlation between the thickness growth
(
ⅆ
h
ⅆ
t
)
and the current density (j) is determined and used as the correlation between paint layer thickness and current density (j), and a correlation between the growth
(
ⅆ
ρ
ⅆ
t
)
of the
specific resistance (p_Paint) of the paint layer ( 3 ) is determined and used as the correlation between specific resistance (p_Paint) and current density (j).
3 . The process according to claim 2 , wherein multiple prediction time points (t — 1 , . . . , t_m) lying in the time of the dip painting are predetermined and the respective thickness (h) of the paint layer ( 3 ) at the point for each prediction time point (t — 1, . . . , t_m) is calculated, wherein for each prediction time point (t — 1, . . . , t_m)
with use of the two empirically determined correlations the thickness growth
(
ⅆ
h
ⅆ
t
)
of the paint layer ( 3 ) and the increase of the specific resistance that
(
ⅆ
ρ_Pa
int
ⅆ
t
)
of the paint layer ( 3 ) in the time between the precding prediction time point and the prediction time point is calculated,
the paint layer thickness (h) at the prediction time point is calculated as the sum of the paint layer thickness (h [t_i]) at the preceding prediction time point and thickness growth(Δh[i]) and
the specific resistance of the paint layer ( 3 ) at the prediction time point is calculated as the sum of the specific resistance (p_Paint [t_i−1]) of the paint layer ( 3 ) at the preceding time point and growth(Δp_Paint[i]) of the specific resistance (p_Paint).
4 . The process according to claim 1 , wherein the respective paint layer thickiness (h) is computed at a first point and a second point of the surface of the object ( 2 ) wherein for each computation the same empirically determined correlations are employed.
5 . The process according to claim 1 , wherein the thickness (d) and the specific resistance (p_FO), which the object ( 2 ) exhibits prior to dip painting at the point, are predetermined and additionally are employed for the computation for the paint layer thickness (h).
6 . The process according to claim 1 , wherein
the process steps are formulated as program code, and
the program code is a component of a computer program, which runs on a data processing unit
7 . A computer program-product, which can be loaded to a memory of a computer and includes software steps, which can be carried out by a process according to one of claim 1 , when the product is running on a computer.
8 . A computer program-product, which is stored on a computer readable medium and including includes a computer readable program means, which allows the computer to carry out a process according to one of claim 1 .
9 . A digital storage medium with electronic readable control signals adapted to interface with a programmable data processing unit, such that a process according to one of claim 1 can be carried out.
10 . A device for predicting the thickness (h) of a paint layer ( 3 ) at at least one point of the surface of an object ( 2 ),
wherein the paint layer ( 3 ) is applied upon the object ( 2 ) by a dip painting, wherein the dip painting includes the steps:
dipping the object ( 2 ) into a dip basin ( 1 ), which contains a liquid paint,
producing an electrical field in the dip basin ( 1 ) by application of a voltage (U),
wherein the object ( 2 ) functions as electrode and a counter-electrode ( 4 ) is present,
wherein the device includes a data processing unit adapted for predicting the thickness (h) of a paint layer ( 3 ) at at least one point of the surface of an object ( 2 ) and for automatically carrying out the following steps:
calculating the electrical potential (Φ) at the point depending upon the magnitude of the applied voltage (U),
depending upon the calculated potential (Φ), calculating the current density (j) at the point, and
depending upon the calculated current density (j), predicting the layer thickness (h) at the point,
and including
emperically determining a coorelation between the paint layer thickness (h) and the current density (j) in the paint layer ( 3 ), and
emperically determining a correlation between the specific resistance (p_Paint) of the paint layer ( 3 ) and the current density (j) in the paint layer ( 3 ),
wherein the paint layer thickness (h) and the specific resistance (p_Paint) of the paint layer ( 3 ) is calculated at the point after the dip painting using
the electrical potentional (Φ) at the point and
the two empirically determined correlations.