perspectives on digital manufacturing - future steel … · 20/06/2017 · perspectives on digital...
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Perspectives on Digital Manufacturing
Pinakin Chaubal
General Manager, ArcelorMittal Global R&D
Future Steel Forum, June 14-15, 2017 Warsaw, Poland
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The Center for International Manufacturing (Cambridge University) has come up with what they
believe will make up the “Smart” factory of the future with more a Commercial / Supply Chain focus.
Smart Manufacturing is not just the Smart Factory
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These technologies can be used individually or in combination to support the development of new
applications, especially in making our manufacturing operations and integrated supply chains “Smarter”.
Future Steel Forum 2017 FocusIndustry 4.0 – Smart Factory Building Blocks
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20/06/2017 Confidential 15
Advance Automation:
KOBM Auto Tap at ArcelorMittal Dofasco
• Automatically tap Steel from KOBM Vessel, includes
– Vessel tilling
– Slag carry over control
– Ladle movement (before, during and after tapping)
– Flux/alloy addition
– Ar stirring
– Slag coating
Global Platforms:
ArcelorMittal Line Scheduling with Artificial Intelligence.
Many simultaneous changes:
thickness, width, steel grades,
thermal cycles, zinc coating,
skin pass elongation,
GA layer, passivation / oiling, …
Earth lifetime
(seconds):119000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
00
143173440000000000
# of possible sequences
with 70 coils:
Parallel
Computing+ =Flexible &
Optimal
Production
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New Limits: Deep Learning for radical quality check
(1) Accuracy of current ASIS (Automatic
Surface Inspection Systems) is not too high
(2) Post-ASIS filtering + human intervention
improves accuracy by 25%
Human analysis is a very costly process (20
potential slivers to find a real one) and almost
impossible to roll out.
• Collaboration with start up company
• New Deep Learning techniques were applied
on top of current ASIS, creating a model from
a 100.000 images dataset
• Accuracy achieved is similar to (2)
• Radical reduction of human inspection and
model can be rolled out
Traditional ASIS + rule-filtering New Deep Learning techniques
• Slivers are still a production defect to be worked out by all steel manufacturers
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And Steps to Success
1. Alignment : Actions => drivers that support goals of the enterprise
2. Systematic Gap assessment to determine the roadmap
3. Proof-of-Concepts that demonstrate value : Rapid transition from cost to value
4. The culture of the organization will be impacted on this journey -> prepare the change
management accordingly.
5. The alignment of the Operations Technology (OT) and the Information Technology (IT)
6. Sharing successes / challenges / lessons learned across the company’s enterprise facilities
7. Do not go to it alone