Wie Industrie 4.0 Szenarien neue Geschäftsmodelle ermöglichen Bei Industrie 4.0 spricht man oft von Big Data & Machine Learning. Der Weg von Remote Service zu Predictive Maintenance ist dabei nur ein Anwendungsbeispiel wie aus Visualisierung und Vorhersage ein richtiger Mehrwert geschaffen wird.

Kay Jeschke, SAP Deutschland SE & Co. KG 29. Sept., 2016

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Agenda Die SAP IoT & Big Data Strategie Die technische Basis Predictive Maintenance

Der virtuelle Zwilling

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Customer

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Das Internet der Dinge und Industrie 4.0 Gesteigerte Komplexität und Varianz  Big Data

Smart Products

Smart Factory Internet

Industrie 4.0

ERP

MES

1

SCADA / HMI

»

Manufacturing industries & manufacturing processes

»

Systems, things and devices in the shop floor

» OT- IT Machine Layer

SMART industrial THINGS SMART industrial DEVICES

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convergence

of Things » » »

All industries All things and devices New, connected business models

» Business

networks SMART THINGS SMART DEVICES

Page 4

What does Big Data mean?

Volume

Big Data Velocity

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Variety

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Big Data und das Internet of Things Paradigmen Wechsel durch Big Data & IoT Business Value

High Process Batch Aggregated Descriptive Data silos

Data Real-time Granular Prescriptive Sharing

Low

Klassische Rolle von IT Systemen

Anforderungen an IOT & Big Data

    

    

Prozess gesteuert Batch Prozesse – zwischen verschiedenen Systemen Aggregierte Daten – Per Produkt / Markt Beschreibende Analysen – Was passierte? Daten Silos – IT vs. OT, limitiert innerhalb des Unternehmens

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Daten gesteuert Echtzeit Prozesse– sofortige Reaktion Hohe Granularität– Data Streaming Vorhersagenden Analysen– Was wird passieren? Data sharing – über Unternehmensgrenzen hinweg

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Big Data and Internet of Things Die digitale Transformation führt zu disruptiven neuen Geschäftsmodellen

Lot Size One

Vertical Integration Smart factory Horizontal Integration

Big Data

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Smart Data

Predictive Maintenance Predictive Quality

New Product Offerings

Selling Services not Products

Business Processes

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SAP Digital Core und IoT Strategie

HANA Plattform

Schnelligkeit

Intelligenz

Integration

Liefert Business Usern hilfreiche Einblicke im richtigen Moment

Von Automatisierung zu vorhersagenden Empfehlungen

Zwischen internen Abteilungen und verbunden mit der ganzen Welt

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Page 8

Agenda Die SAP IoT & Big Data Strategie Die technische Basis Predictive Maintenance

Der virtuelle Zwilling

© 2015 2016 SAP SE or an SAP affiliate company. All rights reserved.

Customer

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Technische Basis für IoT & Big Data SAP HANA Platform Desktop, Mobile APPs und Business Intelligence Anwender

Berechnung

Business Planning & Forecasting

High Performance Applications

Application Development Environment

OLAP

SQL

In-Memory

Reporting & Dashboards

Calculation engine

Adhoc & OLAP Analytics

Predictive

Column Storage

Text

Spatial

Series Data Storage

Predictive Analysis

Data Exploration & Visualization

Lumira / BI

Graph

Rules Dynamic Tiering

Spark Adaptor

Speicherung Data model & data

Fast computing

Smart Data Streaming

High performance analytics

Smart Data Access

Aged data on Disk

Access Hadoop Data

Kostenoptimierte Datenspeicherung

Smart Data Integration & Quality

10101001 01011010 01110

Laden Stream Processing

Quellen

Store time-series data

ERP

OLTP

Virtual Tables

Geo

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User Defined Functions

Store & forward

Transformations & Cleansing

Text

Social

Logs

Machine

Sensor

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SAP HANA Platform In Memory computing Ist die Grundlage der HANA Plattform HANA ermöglicht die Kombination von OLTP an OLAP in einem System

Zeilen und Spalten Speicherung Kompression Partitionierung Keine Aggregate

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Page 11

Big Data benötigt unterschiedliche Speicherformen HANA Data Management Platform Information Management | Text | Search | Graph | Geospatial | Predictive

SAP HANA In-Memory

HANA Dynamic Tiering

HADOOP HANA VORA

0.0sec Instant Results

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Warm Data

Infinite Storage Raw / Archive Data

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IoT und Big Data werden bevorzugt in der Cloud realisiert SAP Hana Cloud Platform  die cloudbasierte Entwicklungsplatform für Innovtionen

A platform for innovation…

Engines & Libraries

Structured & Unstructured Integration Mobile Apps

Unified Developer Experiences

Business Semantics SQL & NoSQL

…with build-in Enterprise Readiness. 24x7

Software Change Management

Availability

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Security

Scalability

Maintainability

Harmonized Stack

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SAP IoT Platform Strategie Typische IoT “MGC” Architektur Maschine:

Gateway:

Cloud/Core:

Turbinen, Pumpen, Roboter etc.

Industrie PC, Router, Raspberry PI, Smart Phone, Local PC

Big Data Analytics and application platform (Cloud, On Premise, Hybrid)

IoT Gateway

Cloud (IoT Core) IoT Gateway

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Core Page 14

Agenda Die SAP IoT & Big Data Strategie Die technische Basis Predictive Maintenance

Der virtuelle Zwilling

© 2015 2016 SAP SE or an SAP affiliate company. All rights reserved.

Customer

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Predictive Maintenance

Graph from http://reliabilitycenteredenergymanagement.com/wp-content/uploads/2011/10/P-F-Curve.jpg

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Wie funktioniert Predictive Maintenance SAP

SAP

SAP

ERP

CRM

SCM

IH Auftrag SCADA Elektronik SCADA Mechanik

Event Streaming in Echtzeit

Monitoring in Echtzeit

Engineering Change Order

Analyse in Echtzeit

Material Planung

Prediktion ex post

Wetter

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Fehler Muster Customer

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SAP Predictive Maintenance and Service Alert Analysis Visualisierung von Maschinen-KPIs und Drilldowns Rollenbasierte Visualisierung von Maschinenwarnungen und -KPIs

Grafischer Drilldown der Alarme (per Region, Kunde, etc.) für echtzeitnahe Erkenntnisse Erfassung von Anlagenstandorten Hinzufügen von Geo-Positionsdaten zu Anlagen für deren Erfassung auf Karten Grafische Hervorhebung von Alert-Situationen auf der Karte und Drilldown in die betreffenden Anlagen

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Customer

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SAP Predictive Maintenance and Service Machine Learning Anwendungsfälle für vorausschauende Analysen Prognose von Störfällen zur Vermeidung von Ausfallzeiten

Auf der Fehlersituation basierende Ersatzteilplanung

Optimierung von Instandhaltungsplänen Prädiktives Qualitätsmanagement Machine Learning mit SAP Predictive Analytics

Anwendung von Algorithmen für Machine Learning auf Sensor- und Fehlercodedaten in SAP Predictive Maintenance and Service, z. B. Klassifikation, z. B. Entscheidungsbäume Outlier Analysis z. B. Anomaly Detection Lebenszyklus-Analysen, z. B. Weibull

Root-cause Analysen, z. B. Key influencing factors

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Customer

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SAP Predictive Maintenance and Service Vibrations Analyse Automatische Vibrationsanalyse für Anlagen mit sich drehenden Komponenten Erfassung von Vibrationen Hochfrequenzaufnahmen von Vibrationen Berechnung des Vibrationsspektrums

Bestimmung des Grenzwertbereichs für die automatische Erkennung von Abweichungen Prozessautomatisierung Identifizierung relevanter Oberschwingungen für die einzelnen Komponenten Automatische Erkennung von Abweichungen für die einzelnen Systemkomponenten Anlegen von Alarmen bei festgestellten Mängeln

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Customer

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Agenda Die SAP IoT & Big Data Strategie Die technische Basis Predictive Maintenance

Der virtuelle Zwilling

© 2015 2016 SAP SE or an SAP affiliate company. All rights reserved.

Customer

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Die Idee vom virtuellen Zwilling Nameplate Info

Nameplate Info

Maintenance Strategy Maintenance Strategy 3D Parts # / BOM

3D Parts # / BOM

Service Bulletins & Revs Service Bulletins & Revs

Service Bulletin Service Receipt Bulletin Receipt

Failure Modes

Failure Modes

Service Bulletin Service Processed Bulletin Processed

Recalls

Recalls

Usage Information Usage Information

Safety Controls

Safety Controls

Installation Installation Information Information

Process Controls

Process Controls

Failure / Incident Failure / Data Incident Data

Service Bulletin

Service Bulletin

Designs & Drawings

DesignsPublish & Drawings

Consume

Sensor Definition

Sensor Definition

Licensing

Licensing

Op Instructions

Op Instructions

Maint Instructions

Maint Instructions

Safety Instructions

Safety Instructions

Product Training

Product Training

Manufacturer © 2016 SAP SE or an SAP affiliate company. All rights reserved.

Consume

Design Improvements Design Improvements

Publish Consume Design Recommendations Design Recommendations

Service Provider

Risks & Controls Risks & Controls Measurement Measurement Documents Documents

TelemetryTelemetry

Operator Customer

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SAP Asset Intelligence Network Das Netzwerk für den virtuellen Zwilling

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Customer

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Big Data and Internet of Things Die digitale Transformation führt zu disruptiven neuen Geschäftsmodellen

Lot Size One

Vertical Integration Smart factory Horizontal Integration

Big Data

© 2015 2016 SAP SE or an SAP affiliate company. All rights reserved.

Smart Data

Predictive Maintenance Predictive Quality

New Product Offerings

Selling Services not Products

Business Processes

Customer

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Thank You

Kay Jeschke Solution Sales Executive Manufacturing Industries

M +49 160-8896144 E [email protected]

© 2015 2016 SAP SE or an SAP affiliate company. All rights reserved.

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