Jason Hoover EPIC 2018

Using Digitalization to Improve Productivity in Process Industries Pitt’s Electric Power Industry Conference (EPIC) October 15, 2018 | Pittsburgh, PA, USA

Digitalization – A megatrend that is transforming our world

Digitalization In the future, we’ll be living in a world that’s increasingly interconnected by complex and heterogeneous systems. By 2020, the amount of data stored worldwide will have grown to 44 zettabytes. Around 50 billion devices will be linked online.

Source: IDC, The Digital Universe of Opportunities: Rich Data and the Increasing Value of the Internet of Things, April 2014; Dave Evans (Cisco): The Internet of Things, How the Next Evolution of the Internet Is Changing Everything, April 2011

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Digitalization – A megatrend that is transforming our world

Digitalization: The Opportunity By the same token, according to some forecasts, interconnected industrial assets will create a multitrillion US $ industry in less than a decade.

Source: IDC, The Digital Universe of Opportunities: Rich Data and the Increasing Value of the Internet of Things, April 2014; Dave Evans (Cisco): The Internet of Things, How the Next Evolution of the Internet Is Changing Everything, April 2011

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The Industrial Evolution Digitalization is the next frontier of industrial productivity Phase 3 Phase 2

Automation

Phase 4

Digitalization

Electrification

Phase 1

Mechanical Production

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Study results: Proper focus on digitalization efforts can result in game-changing operational improvements Digitalization by Industry 1.82

Telecom

2.05

Automotive

2.35

Electronics

2.70

Manufacturing

Digitalization Opportunities and Benefits Asset management and business analytics

$80B

Will be spent in the next 24 months on operational efficiency…

-25%

… that could lead to reduction in OPEX if smartly spent on digital…

Remote Operation

Industrial Internet of Things (Web of Systems)

8%

Chemicals

3.21

Cloud applications

… and produce gamechanging field recovery rates …

Construction

3.33

Oil & Gas

3.82

Big data analytics

+11%

… resulting in sustained profit increase

Source: McKinsey and Co; Accenture; 1 = high, 2 = medium, 3 = low, 4 = rudimentary Restricted © Siemens 2018 Page 5

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The Digital Twin allows for prediction and optimization of system behavior • A digital twin is the virtual representation of a real system.

• It consists of models that describe the system’s geometry, properties and functions.

• It is created during the design stage. Then, once the real system has been constructed, it is continuously adapted based on the data that is tracked and recorded.

• The digital twin accompanies a system throughout all phases of its life: • At the beginning, to simulate system behavior • Later, during operation, to predict system behavior and optimize it Restricted © Siemens 2018 Page 8

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Software and Data Analytics are key to building and maintaining the Digital Twin Pre- / Feed

Fabrication & Commissioning

Operations & Maintenance

Siemens Digital Services

VIRTUAL WORLD

Siemens Software Software Cyber Security

REAL WORLD

Design & Engineering

Asset Performance Management Asset Performance Management Data Analytics

MindSphere – the IoT operating IoT Operating System system

Digitally Enhanced Electrification, Automation, Rotating Equipment Digitally Enhanced Equipment

DIGITAL TWIN Restricted Š Siemens 2018 Page 9

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The Siemens MindSphere Platform: An IoT ecosystem for data analytics MindApps Data Analytics Apps to gain immediate insights and transform insights into actionable results.

Open Ecosystem for customers, partners and developers to create MindApps.

Partner Apps

Customer Apps

Siemens Apps

MindSphere Cloud-based IoT operating system connecting OT to IT environment.

Cloud infrastructure.

Public cloud, private cloud, or on-site solution as a closed system.

MindSphere

MindConnect Plug & play connectivity for quick connection of Siemens assets and Open standards (e.g. OPC UA) to other assets.

Secure and encrypted data communication.

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Asset Performance Management: The digital twin must consider an abundance of data to optimize operation and performance

Process values

x x

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x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

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x

x

x

x

x

x

x

x

Events x

Parameters

x

x

x

Alarm limits x

x x x

Setpoints

x x

x

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Inexpensive sensors are enabling the connectivity of smaller, large scale assets

Smart Motors – connected to the IoT

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Drive Train Analytics for condition monitoring Support for VFDs, motors, and gear units

Reduce non-scheduled production downtimes …

Drive System Connectors

Drive System – Data collection

Secure connection

Accelerate troubleshooting ...

Optional:

Managed digital services

Improve availabilitycentered operation and maintenance planning …

Maintenance / Service manager

Automated reports

Drive System UIs

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Drive Train Analytics typical architecture

Drive System Analyzer

Customer’s Computer

Siemens

Analytics Tools for Experts

Periodic Reports

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Drive Train Analytics Use Case Large Power Station in the USA

Drive Train Analytics produced a real, quantifiable savings of $120K in first year.

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Managed Fleet Services are proven to reduce Total Cost of Ownership (TCO) for VFDs and Drive Systems

Total Cost of Ownership – 20 yrs

Large cost reduction w/ VFD; primarily via energy savings

$$

$$ Up to 30% reduction

Unplanned downtime

TCO reduction via improved process uptime

Asset operation & maintenance services

• Initial equipment cost • Installation • Energy efficiency • Maintenance

w/o VFD

w/ VFD

“Optimized”

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MindTwin is an example of IoT, APM, and software integration Using Siemens XHQ, COMOS, Walkinside, and MindSphere

Problem

Inadequate knowledge of asset conditions leads to inefficient or inadequate maintenance

Solution

Digital twin provides situational awareness to predict and plan maintenance

Benefits

 Asset life,  Service factor,  Maintenance spending

XHQ: visualization, navigation, integration, context, KPIs

COMOS: design, reference, MRO

Walkinside: 3D/spatial

MindSphere: analytics

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Oil pipelines have tremendous opportunity to realize efficiency improvements through IoT Opportunities Significantly reduce OPEX by: • Optimizing per batch at each pump station • Utilizing energy price differential along pipeline • Optimizing DRA application • Enabling ratchet penalty avoidance • Increasing life span of capital equipment by minimizing vibrations and avoiding pressure surges, mechanical wear, and overheating • Central storing of pump performance profiles and pump station energy price data • Continuous real-time energy monitoring • Intelligent analysis for station to station load balancing and proper handling of transient operations (batch changes) Restricted © Siemens 2018 Page 18

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Contact Info

Jason Hoover Director - Digitalization Siemens Large Drives 500 Hunt Valley Road New Kensington, PA 15068 E-mail: jason.hoover@siemens.com

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