CPT International 02/2021
Create successful ePaper yourself
Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.
now. While it was initially ademand<br />
from carmakers, intended to ensure<br />
reproducible production steps and<br />
high quality, for many casters traceability<br />
(e.g. via RFID chips) now includes<br />
the almost complete penetration of<br />
individual process steps, and thus also<br />
the reduced potential for faults. “The<br />
casting knows best what has happened<br />
to it –wejust have to make it talk,”<br />
sums up Prof. Hartmann. While it is<br />
relatively easy to mark acasting during<br />
the die-casting process, it is definitely<br />
more difficult in the case of core shooting<br />
and sand casting. Hartmann is<br />
working with Franken Guss Kitzingen<br />
on the Castcode project, involving the<br />
marking of components via the mold,<br />
whereby amark isembedded in the<br />
pattern plate. This would enable the<br />
calling up of current data on the melt,<br />
Christof Amend, Melting Operations<br />
Manager at Düker in<br />
Laufach, demonstrates charging<br />
via joystick. The chutes<br />
for input materials can be<br />
seen on the left.<br />
Fully automatic core production<br />
at Inacore inErgoldsbach:<br />
industrial robots carry<br />
out most of the work steps<br />
here. They place the cores in<br />
racks marked with RFID<br />
codes.<br />
Photo: Inacore<br />
mold material data including machine<br />
data (mold plant, core-shooting<br />
machine) and, for example, cooling<br />
data. The hand molding shop Karl Kasper<br />
Guss introduced RFID chips for<br />
administrating mold boxes some time<br />
ago. In the Inacore core shop in Ergoldsbach<br />
in Bavaria, which supplies the<br />
BMW light-metal foundry in Landshut<br />
with inorganic cores, the RFID chips are<br />
attached tothe racks. This enables them<br />
to assign production parameters to<br />
batches. The production cycles and their<br />
associated data can be called up in realtime<br />
via aPC, and can be compared<br />
with older data. Inacore cooperates<br />
with the University of Passau so that<br />
one day –with the help of this wealth<br />
of data –nomore faults will be possible.<br />
Data quality counts<br />
It cannot, however, beassumed that a<br />
wealth of production data automatically<br />
provides good forecasts on quality.<br />
“I could have amountain of data with<br />
little information, or just 120 lines of<br />
data with really important information,”<br />
Gottschling knows, and Hartmann<br />
adds: “Getting agood data structure<br />
in the company isthe very first<br />
thing that must be done before optimizations<br />
are possible.”<br />
The two professors recently proved<br />
this with aparticularly creative project<br />
on data gathering: the state of sand is<br />
acoustically determined using their<br />
so-called ‘chafing generator’ and the<br />
forecasting data is used to calculate an<br />
optimum time window for sand regeneration.<br />
The consequence: aprocess with<br />
improved energy and resource conservation.<br />
Safeguarding the future<br />
by reducing rejects<br />
Afoundry can save alot of money by<br />
reducing the number of rejects. The<br />
Danish Norican Group working with the<br />
South African IT company DataProphet<br />
offers the latest system for foundries,<br />
intended to reduce the number of<br />
rejects in serial production by up to 45<br />
percent. Such systems are already in operation<br />
in aSpanish foundry group and at<br />
the South African Atlantis foundry.<br />
The system from Swedish company<br />
pour-tech, recently presented in CP+T<br />
1/2<strong>02</strong>1 from page 24, also promises to<br />
reduce the number of rejects. Foundries<br />
where defective casting is particularly<br />
expensive, e.g. roller foundries, have<br />
already used IT systems for the early<br />
prevention of defects for some time<br />
now. At Walze Irle in Netphen, for<br />
example, probes provide data that computer<br />
algorithms use to determine melting<br />
point and melting range values, as<br />
well as tapping and casting temperatures,<br />
to prepare for casting.<br />
The race for the future of the sector<br />
in the digital age –with minimal rejects<br />
and maximum process reliability –has<br />
therefore started. “If weknow all the<br />
data, all the starting conditions and the<br />
laws of nature we can provide atotally<br />
accurate forecast,” Prof. Gottschling<br />
replies to the question of how exact the<br />
forecasting function could be. This may<br />
well prove difficult. But Prof. Hartmann<br />
is certain that foundries could become<br />
“more flexible, more agile, more reliable<br />
and more robust,” –anadvantage<br />
as afoundry location, that should definitely<br />
be exploited.<br />
CASTING PLANT &TECHNOLOGY 2/2<strong>02</strong>1 35