10/22/20, ICI Virtual Conference

Gerald Richard

https://tractica.omdia.com/newsroom/press-releases/digital-twins-market-growth-is-being-driven-by-industrial-digitization-and-the-

demand-for-enhanced-simulation-capabilities-with-global-revenue-to-reach-9-4-billion-by-2025/

Virtual representation of a physical object

CAGR of 35.32%

imbalanced filling indicated

through local filling times

Color indication of melt

entering different ingates

Mass flux through

individual ingates into the

casting

Buderus Feinguss, Hirzenhain

Jetzt BFG Feinguss (Impro, UK)

Casting geometry

with insulated areas

(shell hidden)

Temperatures at shell surface

Resulting porosity

Solidification sequence

Buderus Feinguss, Hirzenhain

Jetzt BFG Feinguss (Impro, UK)

Folie 8

porosityair entrapment

cracks

distortion

microstructure properties

core gas

graphite formation

mold defects

dross/inclusionscold lap

heat treatment

1. Input

variables

2. Input ranges

3. Goals

4. Objectives

Create Input Define Execute

1. Parametric

CAD geometry

1. Pouring

temperature

2. Pouring time

3. Shakeout

time

4. Etc.

Software will

autonomously:

1. Schedule

2. Modify

3. Run

4. Monitor

SOP:

large process

variation

running production:

process variation reduced

(process robustness)

running production:

robust process

+

optimized operating point (quality, costs, productivity)

Changes in the Yield are Shown by Varying the Marker Color

Fre

e s

urf

ace

are

a

Filling Time

Casting P

rice (

$)

Design

﹁ Objective: Minimize Casting Price

﹁ Designs Simulated = 48

﹁ Simulation Time = 6h 16min

Free surface area

Lowest Casting Price =

$24.29

Ca

stin

g P

rice

($

)

1

2

3

Scatter plot: Traditional vs Optimal

Po

rosity

Yield

Best yieldBest porosity

Best

compromise

Co

nta

ct a

rea

Yield

Best design

Bubble size: Porosity

Gerald Richard

Steel Application Manager

MAGMA Foundry Technologies Inc.

g.richard@magmasoft.com