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The Intelligent Factory: How IoT is optimising operations across the value chain Internet of Manufacturing

Munich – 7th February 2017

Heiko Witte

Head of Engineering Improvement & Quality

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Big Data is our business

We process 8 million data points per day

Rolls-Royce proprietary information

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Digital and Industry 4.0 in Rolls-Royce

Jointly with our partners, we aim to apply the principles of Digitisation and Industry 4.0

to create future oriented hightech value-chains

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BDLI Model – Basis for Rolls-Royce Activities in Germany

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Industrialisation of the Internet of Things

Todays IoT Evolving Technology The Vision

Factory Part Tracking

Digital In-Service

Surviving Hostile

Environments

Nano Sensors

Energy Scavenging

Cyber security

Micro Electronics

High Temp Electronics

5G Communications

Advanced Packaging

Location Awareness

Micro electronic tags

Tech companies

SME’s

App Developers

Universities

1011110101001001000111101010010 MANUFACTURE DESIGN IN-SERVICE

Billions of connected

devices

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Future: Model Based Enterprise 10

Requirements

Design

Simulation

Manufacturing Assembly

Supply Chain

Service/MRO

True Design in Context

Enables multi

functional simulation

Integration of ME

model based

operations

Enables in context

assembly instruction

Enables thru life

product integration

Enables in service

inspection feedback

MBD

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Industry 4.0

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Use Case: Project Insight 12

• Optimization of planning and control of factory (assembly)

operations

• Improve process, reduce variability

• Learning systems reacting on arising issues in logistics and

planning

• Predictable lead times

InSight | Assembly, Planning & Control

Insights

• optimize planning and control of

engine assembly from many legacy

systems including *.xls, *.ppt, *.pdf

and emails

How can we optimize

production?

Question

Production Optimizer™ is a continuously

learning application that helps production

planners synthesize improve productivity

and operational efficiency.

• Real time tracking of:

• Assembly line performance

• Demand plan objectives

• Resource planning

PROF. DR.-ING. U. BERGER Chair of Automation Technology

Production Optimizer™

Compare Plans

Historical View

Fleet View

Up-stream View

Remedial Actions

On-time delivery

Reduce production days

Improved quality

Confidence level of the plan by

artificial intelligence

Capacity utilization reduce production

days / up to 40%

Outcome

Process Integration: LEAN-Flowline and Scrum Methodology

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Scrum-Methodology Flowline

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Summary 16

• Value stream approach to implement digital technologies

• IoT providing key opportunities for improvements in a facory

environment

• Linking digital technologies with Lean product development

methods is key

• Focus for digitization is on

• BETTER PRODUCT

• BETTER PROCESS

• NEW BUSINESS MODEL OPPORTUNITIES