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CPT International 02/2016

The leading technical journal for the global foundry industry – Das führende Fachmagazin für die weltweite Gießerei-Industrie

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global foundry industry – Das führende Fachmagazin für die
weltweite Gießerei-Industrie

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K AUTOMATION<br />

Author: Laura Schwarzbach, KUKA Roboter GmbH, Augsburg<br />

Well guide<br />

At the BMW plant in Landshut, permanent casting molds are cleaned with a manually guided<br />

KUKA robot<br />

In cooperation with the MRK-Systeme GmbH, an innovative solution for<br />

robot-based dry ice blasting for eight different types of tools has been developed<br />

(Photos: KUKA)<br />

The cleaning of permanent casting<br />

molds in foundries by using dry ice<br />

is today still largely done manually,<br />

which places a great strain on the<br />

worker. However, this is not the case<br />

at the foundry of the BMW plant in<br />

Landshut, Germany. Here, a KUKA robot<br />

of the KR Quantec series takes care<br />

of the cleaning procedure. The robot is<br />

taught its path by the worker through<br />

manual guidance.<br />

Since 1898, around 1,500 employees<br />

of the BMW Group in Landshut have<br />

been manufacturing five million cast<br />

components of aluminum and magnesium<br />

per year with a total weight<br />

of around 69,000 t. The scope of production<br />

includes engine components<br />

such as cylinder heads or crankcases<br />

as well as parts for the body structure<br />

and chassis. Once a week, the permanent<br />

molds in the foundry are cleaned<br />

with dry ice. The advantage of this<br />

non-abrasive and non-corrosive cleaning<br />

procedure is that it neither damages<br />

the material to be cleaned nor does<br />

it leave behind dry ice residue. With<br />

dry ice (solid CO 2<br />

), the most complex<br />

geometries, as are often found on permanent<br />

molds, can be cleaned without<br />

damaging or dismantling equipment.<br />

At BMW in Landshut, this was previously<br />

done manually. In cooperation<br />

with Augsburg-based MRK-Systeme<br />

GmbH, an innovative solution has<br />

now been developed for robot-based<br />

dry ice blasting for eight different types<br />

of tools.<br />

Founded in 2004, MRK-Systeme<br />

GmbH and its fourteen employees develop<br />

and implement function packages<br />

for human-robot collaboration. The<br />

system solutions are used mainly by<br />

automobile manufacturers and their<br />

suppliers but also by all other branches<br />

of industry. In cooperation with<br />

Cold Jet, the Augsburg company developed<br />

a cell for the foundry of the BMW<br />

plant in Landshut in order to make the<br />

cleaning procedure with dry ice more<br />

efficient and effective. The main player<br />

in this solution: a manually guided<br />

KUKA robot of the KR Quantec series.<br />

The worker first selects the “Smart-<br />

ICE” software on the KUKA smartPad<br />

teach pendant and from there uses the<br />

graphics to select the type of permanent<br />

mold as well as the relevant areas<br />

on the casting mold. The worker then<br />

manually guides the robot intuitively<br />

through these areas (Figure 1). This offers<br />

primarily ergonomic advantages<br />

when compared to the manual procedure.<br />

With the aid of the force/torque<br />

sensor, the robot can be easily guided<br />

without process forces. In addition,<br />

peripheral signals (e.g. to the actuators<br />

or from/to the dry ice aggregate<br />

through the Aero interface) can be easily<br />

saved in the program by the operator<br />

via touch operation. The worker<br />

then gets the robot to automatically<br />

execute the taught 3-D path and clean<br />

the permanent mold with the dry ice.<br />

“Since the worker no longer carries out<br />

the cleaning procedure directly, he is<br />

no longer exposed to dirt during the<br />

process,” explains Michael Mohre,<br />

Oper ations Manager at MRK Systeme.<br />

34 Casting Plant & Technology 2/<strong>2016</strong>

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