internet of things webinar series
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© 2016 SAP SE or an SAP affiliate company. All rights reserved. 2 Customer
The information in this presentation is confidential and proprietary to SAP and may not be disclosed without the
permission of SAP. This presentation is not subject to your license agreement or any other service or subscription
agreement with SAP. SAP has no obligation to pursue any course of business outlined in this document or any related
presentation, or to develop or release any functionality mentioned therein. This document, or any related presentation
and SAP's strategy and possible future developments, products and or platforms directions and functionality are all
subject to change and may be changed by SAP at any time for any reason without notice. The information in this
document is not a commitment, promise or legal obligation to deliver any material, code or functionality. This
document is provided without a warranty of any kind, either express or implied, including but not limited to, the implied
warranties of merchantability, fitness for a particular purpose, or non-infringement. This document is for informational
purposes and may not be incorporated into a contract. SAP assumes no responsibility for errors or omissions in this
document, except if such damages were caused by SAP´s willful misconduct or gross negligence.
All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ
materially from expectations. Readers are cautioned not to place undue reliance on these forward-looking statements,
which speak only as of their dates, and they should not be relied upon in making purchasing decisions.
Legal disclaimer
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 3 Customer
SAP Internet of Things – Webinar Series
SAP IoT Overview Nils Herzberg Mar 8
SAP Logistics Hub Uwe Kürsten Mar 22
Create new business models based on vehicle
data analysis with SAP Vehicle Insight Mirjam Metzler Mar 29
SAP Asset Intelligent Network Mathew Easley/Dirk Kempf Apr 5
SAP Predictive Maintenance Simon Lee Mar 21
SAP HANA Cloud Platform & HANA Cloud
Integration Alex Braun /
Piyush Gakhar Mar 15
Moderator: Jos Houben
SAP IoT Application Services Harry Lube Apr 26
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 4 Customer
Where are maintenance and service today? Different stakeholders with different concerns
How can I improve my
product’s reliability and
uptime for my customer?
How can I reduce my
warranty costs?
How can I generate new
service-revenue streams?
How can I provide the best service at the right time?
How can I utilize my
maintenance budget better?
How can I prevent unplanned
asset downtime? OEM Operator
Service provider
How can I prioritize maintenance
activities and operate with
reduced risks?
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 5 Customer
Companies are moving
from a reactive to a
proactive approach to
maintenance.
An opportunity is available
for organizations to
leverage machine data for
better business insights.
Where are maintenance and service heading? Organizations are maturing their maintenance strategies
Reactive
Preventive
Condition-
based
Predictive
Wait until a
machine fails
and then
undertake
maintenance.
Perform
maintenance at
regular intervals,
based on
observations of
abnormalities.
Continuously
observe the
status of assets
and react to
predefined
conditions and
events.
Advanced analytics of
operational and
business data helps
determine the condition
of specific equipment to
predict when to perform
maintenance.
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 6 Customer
Danger
Maintain speed –
avoid vehicle on
left
IoT provides a proactive and after-the-fact view of
business processes.
Digitization of enterprises with
the Internet of Things (IoT) Historical and
real-time data
Data-driven view
of business
Change
manage-
ment
Why is the trend an advantage? Move from reactive to proactive business processes
. . . To proactive decision making From reactive behavior . . .
SAP today provides post-mortem view on business processes
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 7 Customer
75% Percent of businesses will be
digital by 20202
Reduction in the price of
sensors, microprocessors, and
wireless technologies over the
past four years1
80%
For the IoT to become
mainstream2
2–5 years
1 1
1 0 0
0 0 1
1
1 1
Why now? The world is more connected, enabling digitization of businesses
1) Source: Economist Intelligence Unit – ”The Rise of the Machines” 2) Source: Internal SAP study provided by Boston Consulting Group, 2016
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 8 Customer
10%–40% Reduction of maintenance costs of factory equipment
Up to 50% Reduction of equipment downtime
3%–5% Reduction of equipment capital investment by extending the useful life of machinery
US$ 630 billion Potential economic impact
annually in 2025
5%–10% Reduction of maintenance costs
3%–5% Increase in output by avoiding unplanned outages
5%–10% Reduction of equipment capital investment by extending the useful life of machinery
Manufacturing
Work sites Oil and gas, mining,
and construction
US$ 360 billion Potential economic impact
annually in 2025
Source: The Internet of Things: Mapping the Value Beyond the Hype, McKinsey Global Institute, June 2015 Video Trenitalia: Creating a System of Maintenance Management Powered by SAP HANA
What is the business benefit? Improving asset reliability promises large savings opportunities
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 9 Customer
How does such a solution generate value? Business value to OEMs and operators
Increased first-visit fix rate By understanding the detailed situation that has lead to an asset failure
better, OEMs and operators can identify the right skills and spare parts
that are relevant for corrective actions.
Improve service profitability OEMs can offer higher margin services that include remote monitoring
and simultaneously resolve more calls remotely to reduce service costs.
Reduced maintenance cost Maintenance schedules can now be driven by sensor information that
allows operators to perform only the required interventions at exactly the
right time.
Warranty cost reduction Service experts can conduct root cause analysis on their products in use
that can be leveraged to improve the design and production quality to avoid
further warranty claims.
Improved equipment effectiveness With the use of machine learning algorithms (such as anomaly detection or
lifecycle analysis) asset operators can predict failures early and implement
corrective actions, which significantly increases the availability of critical
assets.
Business model innovation OEMs are now able to offer new service business models for their products
that were previously impossible, such as full-service agreements or pay per
use.
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 10 Customer
Insight Action
IT/OT* Convergence
• Big Data ingestion
• Big Data infrastructure
• Merging sensor data
with business
information
Maintenance activities
• Prioritized maintenance
and service activities
• Optimized warranty
and spare parts
management
• Prescriptive
Maintenance
• Quality improvements
Data analysis
• Root cause analysis
• Asset health monitoring
• Machine learning
• Anomaly detection
• Triggering of corrective
actions
Connected assets
• Onboarding
• Connectivity
• Device management
• Security
Business Value
• Customer experience
• Increased quality
• Lower costs
• Operational efficiency
• R&D effectiveness
• Material procurement
Sensor Data Insight Action Outcome
SAP Predictive Maintenance and Service solution From sensor to outcome
*) OT = operational technology
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 11 Customer
Many companies are optimizing today Across many industries
Compressor manufacturer
Equipment manufacturer Train operator
Utilities company The business model was changed from
selling compressors to selling compressed
air. The results were improved capabilities
for compressor stations and a move from
unplanned to planned maintenance.
Some 40% of maintenance effort is for
corrective maintenance. Implemented
remote train diagnostics, engineering
rules, and predictive models, which
resulted in lower maintenance costs,
less effort, and higher passenger
satisfaction.
The business requirement was to improve
asset performance. Predictive
maintenance resulted in a reduction in
equipment failures, while improving
reliability and customer satisfaction.
The goal was to strengthen company brand
by improving product quality and reliability
through analysis of equipment telematics
data. The results were reduced warranty
costs, a shortened detection-to-correction
cycle, and improved equipment uptime.
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 12 Customer
Failure rate Burn-in
"infant mortality" Wear-out Normal life
Asset lifetime
Emerging Issues Detection
Early identify, monitoring and management
of emerging asset issues using exploration,
root cause and warranty analytics
Predictive Maintenance and Service
(AHCC)
Holistic management of asset health and
decision support for maintenance schedule
and resource (e.g. spare parts) optimization
based on health scores, anomaly detection
and spectral analysis
Asset Investment Optimization and
Simulation
Analyze remaining useful life of assets to
optimally plan for new investments based on
business needs, asset health and risk of
failure.
SAP ERP, S4HANA, CRM, C4C
Vision for Connected Asset Lifecycle Management
Connected Asset Life Cycle addresses warranty, maintenance and investment related business challenges
throughout the asset lifecycle
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 13 Customer
Geo-
Spatial
Insight
Provider
Asset
Explorer
Insight
Provider
Key
Figure
Insight
Provider
3D
Visualizat
ion
Insight
Provider
Predictive Maintenance and Service
Data Management Data Processing
Work
Activities
Insight
Provider
Derived
Signal
Insight
Provider
SAP HANA SAP IQ SAP Data Services* SAP ESP*
*Optional components
Asset Health Control Center (AHCC)
Extendable
by additional
Custom
Insight
Provider &
Custom Data
Services
Predictive Maintenance and Service On-Premise Edition
Connected
Assets
Devices,
machines,
sensors
Integration
possible with
Telit
DeviceWise,
SAP PCo
Process
Automation
Closed-loop
business
process
integration
into PM and
MRS
IT
Integration
Remaining
Useful Life
Prediction
Distance-
Based
Failure
Analysis
Anomaly Detection with Principal Component Analysis
Data Science Services Insight Provider
OT (Device)
Integration
IoT
Ap
pli
cati
on
s
Op
era
tio
nali
zed
An
aly
tic
s a
nd
Data
Scie
nce
Serv
ices
IoT
Base
Serv
ices
Big
Data
Pla
tfo
rm
Asset Health Fact Sheet (AHFS)
Components
Insight
Provider
SAP Products and Capabilities Driving Scale - Business Applications Built on Modular Analytics
Data Fusion
Storage Data ingestion
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 14 Customer
Health status at a glance
Health status of the complete fleet
Aggregated from component health scores
Based on out-of-the-box machine learning
Derived Signals Management
Personal and extensible
Flexibly composed by insight providers
Drill-down into 1 machine
Integrated into operational processes
E.g. close-loop integration for services
via Multi-Resource Scheduling (MRS)
SAP Products and Capabilities Asset Health Control Center: Supervise Machine Health and Act on Issues
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 15 Customer
SAP Products and Capabilities Data Science Defined – Applicable Use Cases
Anomaly Detection
• Apply Principal Component Analysis to
sensor data to identify the ‘outliers’,
those items or events which do not
conform to the expected pattern
• Automatic detection of multivariate
anomalies, which could lead to failures
in components
Distance-Based
Failure Analysis
• Store ideal state “snapshot” of
component, compare against regular
capture of current state snapshot
• Comparison analysis can result in early
malfunctions in order to reduce
downtime
Remaining Useful
Life Prediction
• Conduct Weibull Life Time Analysis
on captured repair data to estimate
component lifetime
• Calculate remaining useful life and
probability of failure for each
machine/component and store
scores in time series storage
P Q
PCA
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 16 Customer
SAP Products and Capabilities Backend Integration
MRS integration features
• Order management
• Capacity Planning
• Maintenance scheduling
• Prediction based rescheduling
• Material availability check
PdMS PdMS MRS
Create notification in
business system
Optimize
maintenance
schedule
Track work
activites
• Create work activities for
identified issues in Asset
Health Fact Sheet
• Business system can be
PM / CS / CRM / C4C
• Track created work
activity in Work Activity
Insight Provider
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 17 Customer
Insight Providers shipped as part of the PdMS Base
Package extend AHCC and AHFS with new features
Insight Provider Name Explanation
Asset Explorer Insight Provider Asset Explorer selects and displays assets with its key figures and attributes. It includes hierarchical component
composition and global filtering.
Geo-Spatial Insight Provider Geo-Spatial Insight Provider provides a map view that visualizes and interprets data geographically. It supports
tool tips, layering, color coding, selection, geo-fencing and is map provider agnostic.
Key Figure Insight Provider Key Figure Insight Provider supports user defined key figures (e.g. KPIs) and provides the dynamic display of it
according to the global filter.
3D Visualization Insight Provider 3D Visualization of telematics data and derived signals.
Work Activity Insight Provider Provides the ERP Backend integration (retrieving and creation) of Work Orders and Notifications and supports the
integration to a scheduling solution (MRS will be preconfigured).
Components Insight Provider Components Insight Provider provides a hierarchical list of components with attributes such as health status,
health scores, and fey figures.
Derived Signal Insight Provider
Derived Signal Insight Provider generates and displays derived (calculated) signals (e.g. Health Scores, Alerts)
from raw data by using HANA Rules Framework or Data Science Services. It also provides a drill down to further
explanatory details
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 18 Customer
Insight Provider Asset Explorer Insight Provider
Business Purpose Asset Explorer selects and displays assets with its attributes.
It supports hierarchical components and filtering.
Features
Display of assets with its attributes
Configurable list of displayed attributes
Filtering assets by configurable dimensions
Filtering assets by functional locations in the functional location
hierarchy
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 19 Customer
Insight Provider Geo-Spatial Insight Provider
Business Purpose The Geo-Spatial Insight Provider provides a map view that
visualizes and interprets data geographically. It is meant for use
cases with assets in a distributed service area.
Features
Detailed information for displayed assets via tooltip
Support for map overlays that can be toggled individually
Color coding of displayed assets
Single selection of assets to launch AHFS
Geo-fencing and selection of geo-fenced assets
Map provider agnostic
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 20 Customer
Insight Provider Key Figure Insight Provider
Business Purpose The Insight Provider for Key Figures supports user defined key figures.
Key figures are aggregated according to the global filter.
Features
Flexible key figure calculation by using HANA stored procedures.
Support of key figure sets that bundle key figures into sets that are
always added together to AHCC or AHFS.
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 21 Customer
Insight Provider 3D Visualization Insight Provider
Business Purpose The Insight Provider for 3D visualization allows users to quickly
move through a set of parameters to visually detect reoccurring
patterns or correlations to find leading indicators to failure across
multiple assets.
Features
Able to select a sensor from a list and see the values (sensor
readings, derived signals) along the Y axis.
The time along the X axis and different machines as the Z axis.
The Insight Provider is able to overlay maintenance events on
the 3D chart to filter the assets.
Detailed information for displayed assets via tooltip.
Interactive setting of thresholds on 3D chart.
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 22 Customer
Insight Provider Work Activity Insight Provider
Business Purpose The Work Activity Insight Provider enables the back-end integration to
the business systems. It performs an action out of the prediction or
based on the status of a machine or its component.
Features
Configurable list of displayed attributes
Detailed information and current status of service notifications and
work orders.
Detailed view of the scheduled maintenance activities and its
assigned resources from AHCC.
Creation of work orders from AHFS.
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 23 Customer
Insight Provider Components Insight Provider
Business Purpose Components Insight Provider provides a hierarchical list of
components with attributes such as health status, health scores, and
fey figures.
Features
Hierarchical component view with attributes
Configurable list of displayed attributes
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 24 Customer
Insight Provider Derived Signal Insight Provider
Business Purpose Derived Signal Insight Provider generates and displays derived
(calculated) signals (e.g. Alerts) from raw data by using HANA Rules
Framework or Data Science Services.
Features
Configurable list of displayed attributes
Drill down to further explanatory details
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 25 Customer
The PdMS On-Premise Edition can be extended with customer-
specific analyses that seamlessly integrate into the application
The Extensibility Concept allows to extend existing Insight Providers by:
Extend the logic of existing Insight Providers
Define customer-specific key figures (e.g. KPIs) and bundle key figures into sets that are always added together to the
analysis.
Define customer-specific rules for creation of alerts and other derived signals that can be consumed by other Insight Provider.
Customize out-of-the-box data science algorithms
Create models by training one of the provided data science algorithms with customer data.
Provide new data science algorithms
Extend the existing data science services by creating own analysis packages using the programming library R.
Provide new Insight Provider
Extend the analytical capabilities by adding new Insight Providers that implement customer-specific analyses.
Custom Insight Providers can be added to the Asset Health Control Center and Asset Health Factsheet in the same way the
pre-defined Insight Providers do and seamlessly integrate into the application.
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 26 Customer
Discovery Workshop
Data Modeling
Validation Iterations
O P T I O N A L P R O O F O F C O N C E P T
G O - L I V E
I M P L E M E N T A T I O N
( S A P S E R V I C E S / C D )
< 3 months
PdMS Go-Live
CDP (optional)
Extending to Meet Business Needs Optional PoC is an opportunity to increase customer value proposition
Implementation
• Understand
and reframe the
problem(s)
• Ideate possible
solutions
• Ensure
technical
feasibility
• Determine
standard out-
of-the-box fit
• Evaluate
technical
feasibility
• Weekly iterations
to collect feedback
• Pass acceptance
tests and/or
success criteria
• Prepare data
• Model data
• Generate
derived signal
models
• Standard
Implementation
• Based on SAP
standard PdMS
product
• Custom
development of
new functionality
• Go-Live Support
• Standard Support
• SAP CD Support
(optional)
• Application
Management
Service (AMS)
(optional)
S T A R T
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Webinars, Recordings & Presentations
available @
http:sap.com/k4u
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© 2016 SAP SE or an SAP affiliate company. All rights reserved.
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constituting an additional warranty.
In particular, SAP SE or its affiliated companies have no obligation to pursue any course of business outlined in this document or any related presentation, or to develop
or release any functionality mentioned therein. This document, or any related presentation, and SAP SE’s or its affiliated companies’ strategy and possible future
developments, products, and/or platform directions and functionality are all subject to change and may be changed by SAP SE or its affiliated companies at any time
for any reason without notice. The information in this document is not a commitment, promise, or legal obligation to deliver any material, code, or functionality. All forward-
looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. Readers are cautioned not to place
undue reliance on these forward-looking statements, which speak only as of their dates, and they should not be relied upon in making purchasing decisions.