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Conectividad enplanta y mto. Predictivo

2CUSTOMER© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ

Intenet de las cosas en SAP

Manuf. Execution

Suite

ActivosConectados

TrabajadorConectado

NuevosLanzamientos

Junio ‘17


The Intelligent Enterprise Framework

1

2

3

Intelligent Suite

Intelligent Technologies

Digital Platform

The Intelligent Enterprise

features 3 key components:

AI/ML | IoT | Analytics

CustomerExperience

Manufacturing& Supply Chain

Digital Core PeopleEngagement

Network & SpendManagement

Intelligent Technologies

Digital Platform

DataManagement

CloudPlatform

Intelligent Suite


Open

innovation

Industry

innovation

kits

Embedded

intelligence

Industry innovation kits

Integrated capabilities that

accelerate solving critical

industry problems

Embedded intelligence

Intelligent technologies

like machine learning,

the Internet of Things,

blockchain, and analytics

embedded in the

applications

Open innovation

Best-in-class innovation

with intelligent technologies

delivered over

SAP Cloud Platform

SAP Leonardo

Optimize

Extend

Transform

SAP Leonardo – power the Intelligent Enterprise with intelligent

technologies for every enterprise process to create better outcomesbetter

outcomes


Embedded intelligence

SAP Leonardo and business applications

Business

applications

provide

intelligence

at the core of

your business,

enabling you

to run ahead

in today’s

marketplace

SAP Leonardo

powers the

intelligent

enterprise with

intelligent

technologies for

every enterprise

process to create

better outcomes

SAP Leonardo is embedded

for greater business insight,

understanding, and impact

Extending SAP business

applications with intelligent

technologies such as machine

learning, the IoT, and Big Data

Business

applicationsSAP

Leonardo


Internet of Things

Big Data

Data Intelligence

Blockchain

Analytics

Machine Learning

SAP HANA Data Management Suite

Multi-Cloud Infrastructure

SAP Cloud Platform Microservices | Open APIs | Flexible Runtimes | Integration

SAP HANA | SAP Data Hub | SAP EA Designer Services | SWIFTAWS S3

Hadoop…

SAP

Open innovation

SAP Leonardo

Rapid

prototyping

Design-led

innovationSolution ideation

and visionIntegration

blueprint

Business case

development


Industria 4.0

Internet of Things

Internal INDUSTRIAL scenario External scenario

SCADA / HMI

Machine Layer

MES

ERP (PLM, PP)» All industries

» All things and devices

» Ubiquitous

» Personalized

SMART Industrial

THINGS & DEVICES

Industry 4.0» Manufacturing

industries

» OT-IT convergence

» Systems, things, and devices on the shop floor


Casos de uso más demandados

Trazabilidad de la

Producción

Rendimiento de la

producción

Optimización de

procesos

Monitorización

energética

Calidad Predictiva

Mantenimiento

Predictivo

Producción

Conectada

Monitorización de

Planta

Logística

Conectada


DESIGN PLAN RESPOND PRODUCE DELIVER OPERATE

ERP

MES(ME & MII)

PCo

PLC(Machine)

MONITOR

Arquitectura planta conectada

» Sensor detects material carrier

» Requests control parameters from ME

» Production plan

» Bill of materials (BoM)

» variant management

» production steps

» Production details management

» Detailed and flexible

» production step routing

» Shop floor controls for each step

» Mapping of ME production details to PLC control parameters (recipe)

» Serial Numbers

» Quality results per lot

» Order confirmation

» Inventory update, Equipment usage

» Log parametric data

» tolerance checks

» Return „conformance“ or „non-conformance“ decisions


» Machine reports completion and requests next operation

Co

nn

ec

tors

10© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ

SAP connectivity Portfolio

SAP Leonardo Foundation

SAP Leonardo Bridge

SAP Leonardo Edge

IoT Technical Services

IoT Business Services

▪ Streaming▪ Persistence▪ Business

transactions▪ Machine Learning*▪ Analytics*

ConnectedProducts

ConnectedAssets

ConnectedFleet

Connected Infrastructure

ConnectedMarkets

ConnectedPeople

*Planned Innovation

SAP Cloud Platform

Internet of Things

Services Suite

Rules Engine /

Mashup Builder

Event

Processing

Dashboards Application

Enablement

Location

Services*

Edge

Processing

Connectivity

Management*

Device Life-Cycle

Management

Data

Management

Device

Adapters

API Business HubMobileSecurity Data & Storage Dev & Ops User Experience IntegrationCollaboration Analytics

Machine

Learning*Digital Twin

11© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ

DESIGN PLAN RESPOND PRODUCE DELIVER OPERATE

ERP

MES(ME & MII)

PCo

PLC(Machine)

MONITOR

Arquitectura planta conectada

» Sensor detects material carrier

» Requests control parameters from ME

» Production plan

» Bill of materials (BoM)

» variant management

» production steps

» Production details management

» Detailed and flexible

» production step routing

» Shop floor controls for each step


» Serial Numbers

» Quality results per lot

» Order confirmation

» Inventory update, Equipment usage

» Log parametric data

» tolerance checks

» Return „conformance“ or „non-conformance“ decisions


» Machine reports completion and requests next operation

Co

nn

ec

tors


SAP Manufacturing Execution

Main Differentiators

SAP Manufacturing Execution – What is it?

• Shop Floor Execution System for the discrete industries

Main Differentiators• ERP Integration “out of the box” (ECC & S/4HANA)

• Controls production of every single unit (lot size 1)

• Easy interaction with shop-floor automation layer

• Unit level Tracking & Tracing / Genealogy

What operation, tool or machine was used, where parts came from, etc.

• Comprehensive non-conformance management including in-line sampling

and ability for visual test and repair

• Process Interlocking

• High flexibility and extensibility; pure SOA based architecture

• High usability with browser-based user interface

• Role-specific access and personalized dashboards for operators

• Flexible production process modeling without additional programming

• Supports HANA

• Active community of partners and customers


SAP Manufacturing Integration and Intelligence Main Differentiators

SAP Manufacturing Integration and Intelligence – What is it?

– Extensible manufacturing platform allowing rapid adaption to any manufacturing process

Main Differentiators• Integration: Provide interoperability (in)between shop floor solutions and

enterprise ERP (PP, PM, MM, QM)

• Intelligence: Visualize data and include KPIs from any of above sourcesProvides simple and efficient local user interface and dashboards

• Innovation: Powerful SOA-enabled business logic to enable customer-specific processes for planning, execution, maintenance and quality

• Allows fast prototyping to achieve fast ROI

• Broad and extensive partner network

• Applicable to all manufacturing industries and utilities


Condition Based MaintenanceIndividual Measurement Point / Tag information with alerts

Measurement Point Detail

Measurement Point: Oil Viscosity

Type: Equipment

Asset Name: Equipment 2-1

Lower Range Limit: 10

Low Control Limit: 25

Target: 50

High Control Limit: 75

Upper Range Limit: 90


Process / Asset Visibility and Performance (Virtualization)


Predictive Quality

Improvements

Deep Dive

Predictive Quality


“Every single source of information that influences the quality”


Efficiently Identifying Faults Earlier

Business Outcome

› Reduce waste and rework due to higher accuracy of quality checks

› Early issue detection due to solution performance

Pressure

Temperature

IR image features

Manufacturing

Molding press

Sensors

IR cameras

Raw material

ERP Data


Manufacturing Performance ManagementAt Corporate, Facility, Production and Asset Level

» Analyze Performance Management KPIs

at any time and any organizational level

» Benchmark performance internally and

externally

» Manage by exceptions with thresholds

and alerts

» Browser based reporting that works on

both PC & Mobile devices


Provide real time visibility to energy consumption across the enterprise - Insight To Action – energy, fuel, steam and water use is optimized in line with production schedules and energy contracts.

Plant A Plant B Plant C

ShopFloor

TopFloor

SAPERP

SAP MII on HANA

Performance

Traditional DB

SAP Energy Monitoring & AnalyticsEnterprise Operations Management


Role based Insights to enable Intelligent Decisions

CxO

Plant & Unit Heads

Supervisors

✓ Setup manufacturing KPI Governance in line with Corporate

objectives

✓ Review and benchmark Revenue, Cost, Delivery Performance,

Quality & Customer satisfaction across manufacturing plants

✓ Expedited decisions

✓ Monitor and Analyze Manufacturing Performance

Indicators

✓ Improved adherence to production schedule

through real time production insights and

expedited actions

✓ Continuous improvement of Yield/Through put,

product Quality, Vendor Quality through

advanced analytics(Predictive, Statistical Process

Control etc)

✓ Advanced algorithm based

insights pointing to causes

✓ Analyze & review prioritized

causes and their impact and

initiate corrective actions

Key Performance Indicators

Manufacturing Performance Indicators

Manufacturing Activity Indicators

ProductivityQuality Cost Delivery Safety


Reactiva

Preventiva

Basada en

condición

Predictiva

Estrategia de Mantenimiento: Reactiva a Proactiva


Increase

effectiveness

Increase

efficiency

IT and OT

connectivity

Time, effort, or cost

is well used for the

intended task or purpose.

Effectiveness is the

capability of producing

a desired result.

Optimization of maintenanceBring business context to your operational data

Asset health control center

Create maintenance

or service order

Execute order

on mobile deviceVisual supportSchedule order

Ord

er S

tatu

s

Non-SAP applications

SAP S/4HANA

C4C / CRM


Condition Based MaintenanceIndividual Measurement Point / Tag information with alerts

Measurement Point Detail

Measurement Point: Oil Viscosity

Type: Equipment

Asset Name: Equipment 2-1

Lower Range Limit: 10

Low Control Limit: 25

Target: 50

High Control Limit: 75

Upper Range Limit: 90


Process / Asset Visibility and Performance (Virtualization)


Reactiva

Preventiva

Basada en

condición

Predictiva

Estrategia de Mantenimiento: Reactiva a Proactiva


Increase

effectiveness

Increase

efficiency

IT and OT

connectivity

Time, effort, or cost

is well used for the

intended task or purpose.

Effectiveness is the

capability of producing

a desired result.

Optimization of maintenanceBring business context to your operational data

Asset health control center

Fault pattern

recognitionMachine health

prediction

Create maintenance

or service order

Execute order

on mobile device

%

0011001

1101001

Visual supportSchedule order

Ord

er S

tatu

s

Non-SAP applications

SAP S/4HANA

C4C / CRM


SAP Leonardo IoT

for Asset Management

Digital Core: System of

Record

Digital Innovation: System of

Innovation

SAP Leonardo IoT for Asset ManagementEnabling intelligent insights

Asset

Strategy &

Performance

Asset

Intelligence

Network

Predictive

Maintenance

& Service

Predictive

Engineering

Insights

S/4HANA

&

ECC

Maintenance

Management

An architecture built for next generation

Enterprise Asset Management

Digital Core

Corrective, emergency and preventive maintenance planning &

execution via notification and order processing in an integrated

system

Digital Innovation

• Asset Central – Provides a re-usable asset registry across IoT

applications for seamless integration and data consistency

• SAP Asset Intelligence Network

Collaborative asset management bringing key stakeholders

(operator, OEM, service providers, …) together in a digital

ecosystem solving complex execution, predictive and planning

activities with centrally managed asset information

• SAP Predictive Maintenance and Service

Enables enhanced predictive maintenance techniques to

optimize EAM business processes for greater asset availability

and reduced cost

• SAP Asset Strategy and Performance Management

Define and plan maintenance execution strategies holistically

(insight/foresight; insights from network) for improved

performance

• SAP Predictive Engineering Insights

Model and visualize the physical structure of an asset for real-

time calculation of stress and fatigue to drive predictions

Integration

Asset

Central


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

Sense Data Insight Action Outcome

SAP Predictive MaintenanceFrom sensor to outcome

*) OT = operational technology


Asset Lifetime

Failure rateBurn-in

"infant mortality"Wear-outNormal 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 & VA)

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

Connected Asset Life Cycle addresses warranty, maintenance and investment related business challenges

throughout the asset lifecycle


Multiple Approaches to Predictive MaintenanceIT driven approaches are on the rise

Asse

t C

on

ditio

n

TimeTotal Failure

Functional FailureAudible Noise

Ancillary Damage

Battery Impedance Test

Hot to Touch

Potential Failure = First Indication of Failure

Human

Driven

T

F

Equipment

Driven

IT Driven (data science & business rules)

Oil Analysis

X-ray Radiography

P Potential Failure

Why more IT driven approaches?▪ IIoT/device connectivity

▪ Big data available for training models

▪ Declining hardware and software costs

▪ Massive computing powerP

P

P

More time to respond enables

greater flexibility to dynamically plan

maintenance events


Scope of the MLE of

SAP Predictive Maintenance and Service

Offline

No connectivity

Traditional maintenance

processes

High service costs

Connected assets

First (partially) connected

assets

Limited information

exchange

Error code transfer

Limited monitoring and

device management

Asset monitoring

Possibility of remote

access

Fully connected

assets

Transfer of error

codes and sensor

values

KPI definition and

evaluation

Condition monitoring

Comprehensive, ML-based

situational analysis

Integration of analysis

results across processes

(Semi-) automatic and

system-guided derivation of

required actions

Optimization of existing

processes (maintenance,

inventory management, ...)

Condition-based

maintenance

Master data (asset

structure) integration

Mathematical approaches

for condition monitoring

Simple predictive models

(usage trends, ...)

ML-based analyses of

specific components

(vibrations, individual

failures, ...)

Level 0 Level 1 Level 2 Level 3 Level 4

Fully data-driven

maintenance

Analytical

maturity

Added value

from reduced

operating costs

Technological journey toward advanced predictive maintenance


SAP Predictive Maintenance and Service, on premise editionSolution components and value drivers

Business DataMachine Data


SAP Leonardo for Edge Computing

Business User

Domain Expert

Data Scientist

Data ManagerSAP Leonardo IoT Foundation

SAP Leonardo IoT Edge

Machine Learning Engine

Analysis Tools Catalog


Explorer Equipment

Page

Logistics & Maintenance

Execution SystemsActions

Insights

Alerts

Raw

Data

Enables a data science driven

approach to condition monitoring

Flexible extension concept for

customers to build industry or

customer specific models and

analytics

A scalable Machine Learning

Engine that drives data science

insights into our business

processes

Flexible visualizations across

equipment structures

End-to-end process integration…

Alert, Discover, Remedy


Conectividad en planta

» Multiple vendors

» Multiple machines

Connected Manufacturing

SAP ME

SAP MII

SAP QIM

SAP CAMS

SAP PCo SAP OEE

Connected Manufacturing

SAP ME

SAP PCo

SAP MII

Asset Intelligence Network

Distributed Manufacturing Network

OEM Cloud(Mindsphere)

S/4 HANAEnterprise Management

» Business Context

» OEE, Energy Management


SAP Predictive Maintenance and Service, on premise editionSystem and component level visualizations




Explorer (fleet view)

Explorer Equipment

Page






Execution Systems


Equipment Page


Explorer

SAP Predictive Maintenance and Service, on premise editionExplorer - Analysis Tools Catalog

*”Health Status Overview” is an example of a custom Analysis Tool built using SDK

Work Orders Notifications

3D Chart


SAP Predictive Maintenance and Service, on premise editionExplorer

Locations

New Orleans Refinery

Eagle Ford Field

Locations

Explorer



Locations


Eagle Ford Field

Locations Filter by Location

Filter by Locations

Explorer



Locations


Eagle Ford Field

Locations

Filter by Locations

Filter by Location Analysis Tools Catalog


Explorer



Locations Filter by Location Analysis Tools Catalog


Explorer




Key Figures Analysis Tool

Analysis Tools Catalog Analysis Tool


Explorer




Equipment List Analysis Tool



Analysis Tool

Explorer



Locations Filter by Location Analysis Tools Catalog


Analysis Tool

Explorer

Equipment Scores Analysis Tool




Map Analysis Tool



Analysis Tool

Explorer




3D Chart Analysis Tool



Analysis Tool

Explorer




Custom Analysis Tool



Analysis Tool

*”Health Status Overview” is an example of a custom Analysis Tool built using SDK

Explorer


SAP Predictive Maintenance and Service, on premise editionEquipment Page

Equipment View Explorer

Explorer

Equipment View

Serial #12345

Equipment Page


Equipment Page

Explorer

SAP Predictive Maintenance and Service, on premise editionEquipment Page

Equipment View

Equipment View Explorer

Serial #12345

Equipment Page


SAP Predictive Maintenance and ServiceEquipment Page

Information▪ Highlights

▪ Attributes

▪ Model Information

▪ Installation Information

▪ Life Cycle Information

Structure and Parts▪ Structure

▪ Spare Parts

Documentation▪ Documents

▪ Instructions

▪ Announcements

Monitoring▪ 2D Chart

▪ Error Codes

▪ Failure Modes

▪ Improvement Cases

▪ Work Orders & Notifications

Time Line


How to qualify a machine learning problem in SAP Predictive Maintenance

and Service

Do you want to perform a

one-time analysis?

Can you formulate your

problem clearly?

Can you solve it with

simple rules?

Do you have sufficient

relevant historic data?

Does your data exhibit

relevant regular patterns?

Machine

learning

Consider the

rules engine

Consider manual

work1

Include more data

/ additional data

sources

Refine your

problem

1 Using SAP Predictive Analytics, for example

No

No

No

No

No

Yes

Yes

Yes

Yes

Yes


SAP Predictive Maintenance and ServiceMachine learning challenges

High dimensional data

No labeled failure data

Rare failure events

Outdated models, human scale

Use case specific algorithms

Feature construction/selection requires data

scientists & domain user collaboration

Model management, continuous learning and scoring

Anomaly detection and reinforcement

through user feedback

Failure prediction using ensemble learning

Extensibility and integration of new algorithms

SOLUTION


SAP Predictive Maintenance and Service, on premise editionMachine Learning Engine





Explorer Equipment Page


Execution Systems



*Roadmap Item

Continuous Improvement & Learning

Failure

Prediction

Trigger prediction when

algorithm detects a

specific combination of

input variables

Anomaly Detection

Trigger anomaly alert

when the algorithm

detects an abnormal

pattern

New

Algorithms

Extensibility

Model

Management

Tools

Reinforcement*

Domain expert

feedback


SAP Predictive Maintenance and Service, on premise editionMachine Learning Engine

*Roadmap Item

Continuous Improvement & Learning

Failure

Prediction

Trigger prediction when

algorithm detects a

specific combination of

input variables

Anomaly Detection

Trigger anomaly alert

when the algorithm

detects an abnormal

pattern

New

Algorithms

Extensibility

Model

Management

Tools

Reinforcement*

Domain expert

feedback

• Supervised learning enables failure

predictions like Remaining Useful Life

• Finds contributing factors to failure events

• Unsupervised learning detects anomalies

• Enables Health Scores

• Expert feedback

• Models change as operational

environment changes

• Extensibility for out-of-the-box

algorithms

• Possibilities to deploy new

R based algorithms

54CUSTOMER© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ *Roadmap Item

SAP Predictive Maintenance and Service, on premise editionMachine Learning Engine – Model Management

• Machine learning models are automatically applied to new incoming data

• Models are regularly re-trained using scheduling capabilities

• Model management capabilities allows us to maintain model versions

Configure model Score model

Deactivate

Train model

Retrain model

Model

ConfigurationModel Version Scores


Customer exampleCompressor manufacturer

• Provider of compressed air systems and

compressed air consulting services

• Changed their business model from selling

compressors to selling compressed air

• Moved customers from CAPEX to OPEX

• Compressors equipped with sensors

• SAP Predictive Maintenance & Service On-Premise Edition

• SAP HANA

• SAP CRM Service

Company

Solution

Benefits

• IoT as an enabler for the new business model

• Improved availability of compressor stations

• Move from unplanned to planned maintenance

Process Innovation

IT / OT

ConnectivityCondition Monitoring

Remote Service

Fault Pattern

Recognition

Machine Health

Prediction

Create Service

OrderSchedule Order

Execute Order

on mobile deviceVisual Support


Customer exampleIndustrial equipment manufacturer

• Leading manufacturer of separators and

decanters for industrial usage

• New service offering which monitors equipment

during the operation to ensure service contract

compliance

• SAP HANA Cloud Platform

• SAP Predictive Maintenance & Service Cloud Edition

• SAP CRM Service

Company

Solution

Benefits

• Service execution based on real-time machine data

• Increased machine uptime

• Improved service contract compliance

• Higher service productivity and customer satisfaction

Process Innovation

Spare Parts &

Tools

Remote

Service

Engineer

Real-time

Monitoring


SAP Leonardo IoT for Asset Management Networked best-of-breed applications

SAP Cloud

Platform

Asset Strategy

& Performance

Asset

Intelligence

Network

Predictive

Maintenance &

Service

Predictive

Engineering

InsightsS/4HANA

Innovate with Cloud based network

applications (SAP Leonardo IoT

for Asset Management)

Efficiently manage Core

Processes in Maintenance

Management (S/4 HANA)

Integration

Integration

Asset Core

Asset Core


A network to bring together business partners

Global

Inventory Asset Lifecycle

Work

Scheduling

Benchmarking

Pay

on

Performance

Lease

Management

Equipment

History

Applications

Pump OEM

Valve OEM

Service

Provider

Mining

Company

O&G

Company

Utility

Company

Content Integration Network

OEMs & Service Providers Operators

Asset

Intelligence

Network


SAP Asset Intelligence Network: Asset Information & Collaborative Maintenance


Optimize existing processes

for more efficiency or

reliability

Extend current business

processes to capture new

sources of value

Transform company’s value

chain or business model

TransformExtendOptimize

The SAP Innovation Framework offers three approaches to innovation


✓ Repeatable integrated

capabilities that

accelerate solving

critical industry

problems

✓ Industry innovation

services

Industry innovation kits

SAP Leonardo

Retail

• Assets

• Logistics

• Zero waste

Consumer

Products

• Assets

• Logistics

• Cold chain logistics

Discrete

Manufacturing

• Serviceand assets

• Logistics

• Pay for outcome

• Spare parts

Utilities

• Service and assets

Travel and

Transportation

• Logistics

Telecom

• Big Data margin assurance

Chemicals

• Service

and assets

• Spare parts

Sports and

entertainment

• Venue

• Team silver

• Team gold

Life Sciences

• Assets

• Cold chain

logistics

Oil and Gas

• Service

and assets

Mining

• Fleet

operations

Automotive

• Fleet

insights


Explore

One-day design

thinking workshop

1

Academies

Events

Customer Interest

Create ValidateReimagine

Contract

Discover and Design

Clickable interactive

prototype with the

SAP Build tool

2

SAP Leonardo ‒ customer engagement model and SAP Leonardo Services

Scale

Scale and transform

Scale

Additional SAP

Leonardo services

to advance new

business or service

models and to scale

up and pursue

additional use cases

3

• Functional prototype

• Value assessment

• scenario design

and architecture

Industry innovation kits8-10 weeks

to productionstarting at €60k

Deliver

As few as 10

weeks to productionCost depends on use case(s)

Open innovation path

Awareness

Gracias.

Contact information:

Carlos Chicharro

SAP DGTAL Expert

Innovation Business Unit – EMEA South

[email protected]

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