am next digitalization break out...through big data analytics and machine learning connected...

AM NEXT

Digitalization Break OutAndreas Graichen

siemens.com/am-energy© Siemens AG 2018 All rights reserved.

October 2018 Andreas Graichen / Siemens AG

© Siemens AG 2018 All rights reserved.

Introduction:

Our AM journey at Siemens in Finspong (Sweden)

Perceived fitness

of AM-Process

2009 2013 2018

Pre-Mature Hype?

Challenges

• Material knowledge

• Design culture

• Stand-alone software

• Training

• Machine performance

• Quality issues

• Health and Safety concerns

• ….

Disappointment: ”It is

not just 3D-Printing! It

is much more

complex…”



Vision: Unified chain of data transmission

Automated 3D Scanner

and X-Ray Tomography

Manufacturing Execution System

Tool control directly from CAD

Paperless Factory

Robotic cleaning

In- and offline monitoring

leading to Self-healing



Starting Position: 2017

2017/18

Traditional Workshop

“Siemens wants to make 3D-Printing in metal as simple as 2D-printing on paper!”



Step 1 (Today): Become ”Connected”

through MES and use build job simulation

Connected

Workshop

2018


▪ MES & QMS

▪ Build simulation

▪ Encryption

▪ AM Network



Step 2: Become ”Learning Workshop”

through big data analytics and machine Learning

Connected Workshop

Learning

Workshop

2018 & 2019


Big Data &

Machine Learning



Step 3: Become ”Intelligent Workshop” Through Robots, VR/AR

and Artificial Intelligence

Connected Workshop

LearningWorkshop

IntelligentWorkshop

2019


e.g. Robots, VR/AR



Step 4: Become ”Autonomous”, closed loop and self healing

processes; gas turbines order spare parts by themselves

Connected Workshop

LearningWorkshop

IntelligentWorkshop

2020+


AutonomousWorkshop

Cloud

IoT for AM



SUMMARY 1:

Different levels of digitalized Additive Manufacturing

Prototyping

Commercial

Production & Repair Integrated

Manufacturing

3D-Printer

Network

IoT for

Industrial

AM

Cloud



Digitalization Landscape Finspong (simplified)

AM Network(=Customer Portal with CAD-

upload; later automated

quotations; hosted on AWS, later

maybe Mindsphere)

MES(= Orders, Operator guidance,

Powder batch management,

Quality Assurance etc.)

QMS (=FY2019/Q3;

AMOM2; powder test

handling & test bars;

MES-plug in)

AM Monitor(= Big Data Collection of pictures

and sensor data, including

machine learning algorythms;

AWS and later Mindsphere)

Teamcenter

PLM2020

v11.5(= storage of all CAD and CAM

files, parameter settings; used as

platform for Model Based Design)

SAP ATLAS(=BoM & BoP, orders, economy, end storage of all order

relevant data)

Confidential

ID3D(= Encryption and

Authorization/Digital Rights

Management)

Metal SLM

(only EOS)

AM

Explorer

Customer



SUMMARY 2: IT-System Aspects in an Industrial Setting



Backup



All Parts of the Digital Chain Should be Able to Communicate

Freely

Manufacturing Control

NX TeamCenter

Cloud = IoT powered by MindSphere

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