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CPT International 02/2021

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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

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