IoT in der Praxis
Transcript of IoT in der Praxis
© Hitachi Vantara Corporation 2018. All Rights Reserved© Hitachi Vantara Corporation 2018. All Rights Reserved
IoT in der Praxis
Solutions Engineer, EMEA CentralData Analytics & IoT
Harald Erb
OT108Years
INDUSTRIAL
CITY
BUSINESS
CONSUMER
IT59
YearsAPPLICATIONS
ANALYTICS
INFRASTRUCTURE
BIG DATA
CLOUD
IoTis in our
DNA
Hitachi Vantara combines IT, OT
and Industry Expertise
HITACHI’s unique Expertise
Hitachi VantaraHitachi Data
SystemsPentaho
Hitachi
Insight
Group
Software
Data
Scientists
OT/IT
Expertise
Solutions
&
Services
IT Infrastructure
SolutionsIndustryExpertise
Partner Eco-System
ArtificialIntelligence
DataAnalytics
X as a Service
© Hitachi Vantara Corporation 2018. All Rights Reserved
Hitachi IoT Solution Portfolio
Data
Operations
Data
Analytics
Data
StreamingData
IntegrationReplication and
SynchronizationData Pipeline
Optimization
Reporting
& VisualizationMachine Learning
Orchestration
Embedded
Analytics
Video Data
Management
Stream
Processing
Edge
Digital
Twin ModelingData Caching
and Analytics
Device
Management
Common IoT-
Platform Services
Insight
Solutions
Co-creation
Services
Industry Solutions(Hitachi BUs, ISVs, SIs)
Edge-to-Cloud
Infrastructure
… more to come …
Edge Controllers/Appliances Converged & Hyper-Converged Block, File- and Object Storage
Outcome Workshops Solution Architecture Data Science Proof of Value
Discrete Process Trans Telco Mining FinServ …etc…
Maintenance
Insights
Manufacturing
Insights
Video
Insights
© Hitachi Vantara Corporation 2018. All Rights Reserved
Usage based Insurance Solutions
Example: Connected Car Platform
• More Data
• New Insights
• New and/or improved Products & Services_
Pitctu
re:
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.com
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Traffic laws can have short-term improvements on
accidents reduction
‒ Long-term improvements require behavior change
Telematics can help drivers reduce their risk of accidents
significantly by
‒ Identifying risky driving behaviors
‒ Providing feedback on how to improve driving behavior
Positive reinforcement through continous feedback &
coaching coupled with incentives & rewards improve driving
behavior and dramatically reduce accidents
Change Driver Behavior with Direct Engagement
Driver Scoring
© Hitachi Vantara Corporation 2018. All Rights Reserved
More Data – New Insights
Driving Statistics Distracted Driving
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DriveSync Connected Car Platform
Challenges
• Ability to handle large amounts of data (1.6B data points/day)
• Perform predictive behavior patterns from disparate data sources
• Support reporting needs from creating custom dashboards to generating detailed reports on the fly
Solutions
• Seamless integration and connectivity to all IMS data sources
• Embedded business analytics for fast time to market
• Enterprise class platform that provides data-driven insight and predictive analytics
Benefits
• Help insurance carriers retain current and attain new customers
• Reduce the number of claims through driver behavior monitoring
© Hitachi, Ltd. 2018. All rights reserved.
Fleet Optimization
Example: Fleet Management Solution
• Combine Sensor Data with Contextual Information
• Overcome scarce availability of capable technicians
• Lower costs, reduced customer downtimes_
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Web-Based Fleet Management Platform
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Business Objectives
Issues: Trucks have become more and more technology based, availability of capable
technicians is scarce, and managing large number of maintenance centers is expensive.
Business Objectives: Better Fleet Management - lowering costs, improving efficiency
of maintenance to reduce customer downtime
Strategic Goals: Need to take competitive advantage of truck data. 40-50,000 trucks
purchased per year – more data than any truck OEM. Gain a competitive edge through
lowered costs & predictive technology (automation in repairs & diagnostics).
© Hitachi Vantara Corporation 2018. All Rights Reserved
Benefits of Predictive Maintenance
Return on Capital
Return on Net Assets
Profit
Throughput
Availability QualityProductivity
Service
On Time In Full Delivery
Net Assets
Projects
Capital Expenditure
Cost
Fixed Costs Variable Costs
Operating Expenditure
An Effective Predictive Maintenance Program not only impacts OPEX and CAPEX,
but SAFETY and CUSTOMER SATISFACTION also
© Hitachi Vantara Corporation 2018. All Rights Reserved
Vehicle Sensor Data
Store models and sensor data
Asset ModelSensor DataUtility Vehicle Asset
Air Pressure
Axle Vibration
Lights
Load Weight
Movement
Temperature
Sensor Data
Journey
StreamBlend
Infer
Sense
Inspect
Embed & Integrate
Store
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Adding Context to Sensor Data
Vehicle Location
•GPS
• Lat / Long
•Mapping
•Movement
Vehicle Profile
•Make
•Model
•Mileage
Operational Systems
•Maintenance History
•Maintenance Schedule
•Service Centers
•Parts Ordering
•Parts Inventory
Sensor Data Contextual Data
Business Outcomes
• Real-Time Fleet Status and Health
• Repair Recommendations
• Optimized Maintenance Scheduling
• Automated Parts Ordering
IoT Data Refinery
Sensor Data
Journey
StreamBlend
Infer
Sense
Inspect
Embed & Integrate
Store
© Hitachi Vantara Corporation 2018. All Rights Reserved
Visualize & Analyze Results
Fleet overview
Vehicle Status & Health
Production Reporting (PDF example)
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Train as a Service
Example: Smart Trains
• Batch and (Near) Real-time Data Processing Architecture
• Failure/Performance Analysis and Prediction
• New Business Model: Train as a Service_
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Smarter Trains are more predictable…
Rail Predictive Maintenance tools help to:
Avoid unplanned downtime by avoiding unexpected failure of the equipment
Reduce parts replacement by avoiding unnecessary part replacements
Reduce repair cost (including labour) with effective root cause analysis
Reduce costs with better planning of supply chain
Reduce labour costs with optimization
© Hitachi Vantara Corporation 2018. All Rights Reserved© Hitachi, Rail Europe Ltd. 2017. All rights reserved.
Example: Doors – System description
Door Open
Door Shut Status Door Open Status
Door Open Button
Lock operation
Opening operation
© Hitachi Vantara Corporation 2018. All Rights Reserved© Hitachi, Rail Europe Ltd. 2017. All rights reserved.
Example: Doors – What do we do with this information?
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Cause: Obstacle stuck in door
Requires rapid intervention
Persistent proportional rise in Cycle Time
may be indicator of degradation and incipient fault
© Hitachi Vantara Corporation 2018. All Rights Reserved
Predictive Maintenance
Challenges
• Managing petabytes of data (3.6 million data points per second)
• Inability to perform complex analysis -both in real-time and in batch
• Presenting custom visualisations in a scalable and multi-tenanted fashion
Solutions
• End-to-end Big Data platform
• Scale to data growth
• Predict operational events
Benefits
• Long term benefits will be £20m+ savings in maintenance costs
• More reliable and cost-effective transportation system for United Kingdom
• Better service delivery
© Hitachi Vantara Corporation 2018. All Rights Reserved
Solution Overview
Asset Control & Maintenance
Big Data & Analytics
System & Sensor Integration
Data Management & Transmission
Data CommunicationsMachine Sensors Data
Collection
Hitachi IEP Train Data PlatformAsset Control &
Maintenance
Business Intelligence
Predictive Analytics
Asset Management
Asset Control
Data Warehouse
Maintenance
Schedule
Asset Management & Maintenance
Reporting Dashboards & Analytics
Predictive maintenance
& Service scheduling
Operational Insight
Management Reporting
Asset Control Decisions
Business Transformation | Change Management | Programme Management
MessagingStore and forward
Telemetric & ambient data
Operational & Audit Data
Train Performance Data
Real time alert messages
Operational Status
Alerting
Sensors
Sensors
Sensors
Sensors
Takeaway
Guten Appetit!
Gerne stehen wir Ihnen noch
Für Fragen in der Mittagspause
Zur Verfügung
www.it-novum.com/vvb
Laden Sie hier exklusiv unsere Vorträge runter und erhalten Sie außerdem das
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Contact
Harald Erb
Hitachi Vantara
Solutions Engineer, EMEA Central Data Analytics & IoT
m: +49 (0)177 5944403
Andreas Kuhn
it-novum
Sales Manager Big Data Analytics
t: +49 (0)661 103-363