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Industry 4.0 for the Oil and Gas Sector Research and Innovation Challenges and Mechanisms David Cameron CCFN Digital Transformation, Oslo, 13 th October 2016

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Industry 4.0 for the Oil and Gas Sector

Research and Innovation Challenges and Mechanisms

David CameronCCFN Digital Transformation, Oslo, 13th October 2016

Industry 4.0

Industrie 4.0 13

1 Intr

oduc

tion

1 Introduction

Securing the future of German manufacturing industry Germany has one of the most competitive manufactur-ing industries in the world. This is due to its ability to manage complex industrial processes where different tasks are performed by different partners in different geographical locations. It has been successfully em-ploying information and communication technology (ICT) to do this for several decades – today, approxi-mately 90 percent of all industrial manufacturing pro-cesses are already supported by ICT. Over the past 30 years or so, the IT revolution has brought about a radical transformation of the world in which we live and work, with an impact comparable to that of mechanisation and electricity in the first and second Industrial Revolutions.1 The evolution of PCs into smart devices has been ac-companied by a trend for more and more IT infrastruc-ture and services to be provided through smart net-works (cloud computing). In conjunction with ever greater miniaturisation and the unstoppable march of the Internet, this trend is ushering in a world where ubiquitous computing is becoming a reality.

Powerful, autonomous microcomputers (embedded systems) are increasingly being wirelessly networked with each other and with the Internet. This is resulting in the convergence of the physical world and the virtual world (cyberspace) in the form of Cyber-Physical Sys-tems (CPS). Following the introduction of the new In-ternet protocol IPv62 in 2012, there are now sufficient addresses available to enable universal direct network-ing of smart objects via the Internet. This means that for the first time ever it is now possible to network resources, information, objects and people to create the Internet of Things and Services. The ef-fects of this phenomenon will also be felt by industry. In the realm of manufacturing, this technological evolu-tion can be described as the fourth stage of industriali-sation, or Industrie 4.03 (Fig. 1). Industrialisation began with the introduction of me-chanical manufacturing equipment at the end of the 18th century, when machines like the mechanical loom revolutionised the way goods were made. This first in-dustrial revolution was followed by a second one that

End of 18th century

Start of 20th century

Start of 1970s today

Source: DFKI 2011

4. industrial revolution based on Cyber-Physical Systemss

3. industrial revolution uses electronics and IT to achieve further automation of manufacturing

2. industrial revolution follows introduction of electrically-powered mass production based on the division of labour

1. industrial revolution follows introduction of water- and steam-powered mechanical manufacturing facilities

First mechanical loom1784

First programmable logic controller (PLC), Modicon 0841969

comp

lexity

time

First production line,Cincinnati slaughterhouses1870

Figure 1:The four stages of the Industrial Revolution

Concepts:• Cyber-Physical Systems• Vertical Integration• Horizontal Integration• Internet of Things• Artificial Intelligence • Analytics

Not a new paradigm. Rather the maturing of the 3rd industrial revolution. Automation finally works!

It takes around 50 years for technical step-changes to result in measurable improvements in productivity.

Challenges to oil and gas• Digital end-to-end engineering

– For the whole life of the facility

• Inter-company value chains– Cutting the cost of EPC and M&M

• Standardisation, products and services– Instead of tailor-made and owned

• Robotics, minimum-manning and autonomy– In difficult and challenging places

• Vertical integration: getting data to the decision maker– Commercial and technical decision makers need to be first-class digital employees

Unrestricted © Siemens AG 2016

Page 3 Dr. Sebastian-Philipp Brandt, Siemens CT RDA BAM SMR-DE, Corporate Technology

Query

Siemens Power Generation Use-caseUniform solutions for equipment monitoring

BSX-TC3562-XE01

BSX-TMP12A-XE01

BSX-TICCFB1-XE01

MS-XC255-X12

BSX-TC3562-XE01

BSX-TC3562-XE01

MRR-T8901-8462

CRR-M8393-9272

“Ignitor on”

Analytics

Normalstart?Sensor types,

turbinestructure,

site con-figurations,

measurable

quantities,

Processes

Dom

ain

onto

logy

Sem

antic

map

ping

* http://optique-project.eu/

Who will deliver the solutions?• Platform Companies?• IT System Integrators?• ERP?• Automation?• Equipment Manufacturers?• Analytics Providers?

Every vendor is offering their own cloud.

How do we get these clouds to overlap, work together and work with our legacy?

Research issues to be solved• Specifying and maintaining useful semantic models about real things• Good, fast, effective databases – in memory and in place• Use of natural language – in data and interaction• Efficient, predictable access to data spread across the cloud• Secure, role-based access to data• High-performance computing to access data, reason and calculate• Modelling, optimization and reasoning – analytics – not just statistics• Sensitive and effective transformation of work practices• Development of friendly, usable user services • i.e. industrial informatics.

We are building an innovation cluster

• Operators, EPC and service companies to provide the hard business problems

• Research providers to bring the experiments into prototypes and pilots

• Integrators, both large and small, to deliver the products and services

SIRIUS: Centre for Scalable Data Access in the Oil and Gas Domain