sap İnovasyon forum İstanbul - predictive maintenance and servİce-sap

SAP INNOVATION FORUM ISTANBUL

SAP Predictive Maintenance and Service

Francesco Mari

Vice President – Business Innovation – Internet of Things

DIGITAL ERA

Connected Innovation

© 2016 SAP SE or an SAP affiliate company. All rights reserved. 2Internal

Physical Objects Deteriorate with Usage

Ma

ch

ine

Ca

pa

bili

ty /

Re

sis

tan

ce

to

Fa

ilure

Time

Potential FailureP

Total

Failure

F Functional Failure

Preventive Maintenance

& Monitor Condition

Equipment UnusableRepair or Replace

Mechanically Loose

Ancillary Damage

Early Signal 3 - Oil Contamination Detected

Audible Noise

Hot to Touch

Early Signal 2 – Vibration Analysis Fault

Early Signal 1 – Ultrasonic Energy Detected

“Can”

“Want”

Maintenance strategies are aimed at preventing failures and

increasing the availability of the assets while investing the

minimum possible amount of resources


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?


Enters the Internet of Things // IoT := IT + OT

Currently, IT and OT are mostly separated world:

• Different technologies

• Different organization and responsibilities

• Different skills and professional profiles

• Often, even different codes and standards

Removing the barriers between IT and OT

we can overcome all these obstacles

• Critical decisions based on facts – rather than approximate

information

• No delay between facts, analysis, decisions and reactions

• Holistic optimization of systems, and of systems of systems


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 solutionFrom sensor to outcome

*) OT = operational technology


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 costMaintenance schedules can now be driven by sensor information that

allows operators to perform only the required interventions at exactly the

right time.

Warranty cost reductionService 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 effectivenessWith 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 innovationOEMs 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.


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 maintenance and serviceBring business context to your operational data

Asset health control center

Fault pattern

recognitionMachine health

prediction

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

0011001

1101001

%


Predictive Maintenance and Service On-Premise Edition (PdMS OPE)

Business Applications built on Modular Analytics

Geo-

Spatial

Insight

Provider

Asset

Explorer

Insight

Provider

Key

Figure

Insight

Provider

3D

Visualizat

ion

Insight

Provider

Predictive Maintenance and Service

Insight Provider

Lifecycle Management

Data Science Modeling &

Scoring

Insight Provider Runtime Services

Work

Activities

Insight

Provider

Derived

Signal

Insight

Provider

SAP HANA Enterprise

Edition

SAP IQ

SAP Data Services*

SAP ESP*

SAP Predictive Analysis*

SAP Lumira*

*Optional components

Asset Health Control Center (AHCC)

Additional

Custom

Insight

Provider

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

Process

Integration

Data Management

Remaining

Useful Life

Prediction

Distance-

Based

Failure

Analysis

Anomaly Detection with Principal Component Analysis

Data Science ServicesInsight Provider

Product

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)

Maintenance Innovation in Context

Railway Case


The Business Value of Maintenance Innovation

Perform ALL the required interventions, and ONLY the required interventions, at the RIGHT TIME, ensuring

availability of the RIGHT RESOURCES

Prevent breakdowns while trains are in operations

Prevent extended maintenance downtime due to unforeseen activities

Reduce Unplanned Downtime

Avoid any unnecessary activity

Plan in advance and in detail for any intervention, ensuring availability of spare parts, facilities, tools and trained resources

ReduceCosts of

Operations

>8-10% of direct savings on impacted maintenance costs

>x% of reduction of breakdowns of trains in operations

>y% increase in asset availability

Ground diagnostic

On board diagnostic

Dynamic Maintenance

Management System


dischargingcharging

full

Bad condition

P (reference state) Q (current state)

Problem: Components of critical assets that can lead to unplanned downtimes

when they fail tend to be over-maintained independently from their actual status

Solution:

1. Data extraction and preparation: Extract the equipment’s sensor data from time

series storage and prepare it.

2. Learn a model and score new data: Compute the distances of each component

to a reference component using earth mover’s distance (lazy learner type of

algorithm) and store distances in time series storage.

3. By comparing the current values of sensor data of an item for a given point in

time (current state) with examples of pre-defined reference states (e.g. battery

full, charging, discharging etc.) it is possible to calculate a value that shows a

trend toward one of these pre-defined reference states and helps to get an

accurate interpretation of the current state of an item.

4. Due to the identified state action can be proposed and triggered automatically.

5. Components are shown in a ranked by distance ordering in the application.

Benefits:

Early identification of malfunctioning components in order to reduce downtime.

Interpretation of battery sensor data based

on pre-defined reference states

compare

similarity

Distance-Based Health Scoring


Ranking of Distance Among Homogeneous Components

Rank Battery1 1282 3483 1334 1445 0086 1817 3668 0519 336

10 536…

371 103372 135373 281374 463375 096376 109377 086378 139379 308380 280

Massive automatic analysis of components vs. normal behaviors to measure and rank the distance, and

identify the potential bad actors

Maintenance policies get

differentiated by the various

sections of the ranking (e.g.:

do not perform any

preventive actions for the

batteries in the top 50% of

the ranking)

Very significant projected

savings on maintenance

costs without increase in

failures (partially already

confirmed by actual results)


Transforming the Game in Maintenance Operations

Risk

Cost Definition of maintenance policies can be seen as the management of the tension and trade-off between costs and risks. Most of the efficiency efforts are aimed at making sure that the right balance is reached

Internet of Things-based maintenance innovation represents the opportunity of transforming structurally the system and reach a new level of balance between costs and risks

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