|
catalogue search
|
You may also be interested in
Laser sensor, Pt1000 temperature probe, Transducer, Capacitive accelerometer, Absolute pressure transmitter
Text version of the page
www.kistler.com 19
Analyzing: Injection Molding Process Analysis
and Optimization
DataFlow provides a range of tools across
the entire process chain:
During mold sampling and optimization,
DataFlow provides process data in a variety
of different graphics in order to speed
up the mold sampling process and to utilize
the full optimization potential.
During process optimization, DataFlow can
be used to determine process tolerance
limits and to evaluate processing properties
based on the measured data. In this
way, the system reduces mold sampling
times and ensures a fast optimization of the
process. The determined tolerance limits
can be used for monitoring part properties
and quality assurance during the production
process and dispense with the need
for manual examination.
During mold set-up, cavity pressure reference
curves can be stored. Optimized molds
can be operated fast and efficiently on different
machines and the optimum operating
point can be determined quickly.
During production DataFlow calculates
from the measured process data maximum
values, freely definable integrals, the filling
index and the injection work. Moreover,
the system allows the definition of
tolerance ranges. Transgression of these
tolerance ranges by the values recorded
from the current process will either trigger
an optical notification or lead to an activation
of the reject gates or robots.
DataFlow provides automatic quality assurance
for molds with large numbers of
cavities and integrates it into the process.
Trend graphics can predict errors in the active
production process to eliminate them.
Networking statistics allow statistical production
analysis (cp, cpk values, production
distribution) for the purpose of documentation.
Automatic reports provide a
documentation of quality for customers.
Statistics data generated by DataFlow can
be used to detect and eliminate weak
points in the production process and help
to determine the reject quota while the
production monitoring function can then
be used to directly identify the cause of
excessive rejects.
|