ADVANCED DIAGNOSTICS AND PREDICTIVE ANALYTICS OF …iecon2013.org/files/IECON2013_IF4_01_Prenninger.pdf · advanced diagnostics and predictive analytics of vehicle data ... advanced

ADVANCED DIAGNOSTICS AND PREDICTIVE ANALYTICS OF VEHICLE DATA DR. JOHANN PRENNINGER

IECON 2013, Nov. 12 2013, Vienna

ADVANCED DIAGNOSTICS AND PREDICTIVE ANALYTICS OF VEHICLE DATA AT BMW

1 Contents

2 State of the Art On- and Offboard Vehicle Diagnosis

3 Analytical Challenges, the customers view

4 The FACTS process for agile Analytics at BMW

5 Conclusion

Page 2 IECON 2013, Nov. 12 2013, Vienna

1 Contents




5 Conclusion



Service advisor

• Customer visit of

service station for service or repair.

• Service advisor is

picking up the car and the original statement (o-tone) of customer.

• Mechanic

performs diagnosis, reads out onboard data, failure messages etc.

• Big picture of

failure situation.

• Repair is done as

proposed and guided by diagnosis software.

• Diagnostic /

technical data is created/logged at this time.

• Data transfer of

technical and business data to the headquarter.

• Storage in

different data warehouses.

• Interpretation and

analysis of the data.

• Check and Payment of Warranty Claim.

• Starting point for

Data Mining.

DIAGNOSIS AND REPAIR. TOUCHPOINTS TO THE PROCESSES OF THE DEALERSHIP

Data ReadOut

Diagnosis & Repair

Data Transfer

Analysis & Reporting


DIAGNOSIS AND REPAIR START MUCH EARLIER. CUSTOMER IMPRESSION AND FEEDBACK IS VALUABLE

Page 5

TeleServices

Connected Drive

Internet Forum, …

• The driver

“produces” data

about his driving

experience.

• He expresses himself

online about product

issues.

• He is occasionally

asked via surveys

and studies (TÜV,

IACS, JD-Powers, …)

Customer survey

TeleServices,

Connected Drive,

Internet Forum, …

• The customer

expresses & shares

his aftersales

experience online.

• He is asked

individually about

his service / repair

experience.

• He evaluates his

satisfaction.


Diebstahl-

warnanlage

Reifendruck-

kontrolle

Regensensor

Lichtschalt-

modul

Heizungs-

bedienteil

Heizungs-

bedienteil

(Fond)

1-Achs-

Luftfeder

Bedienzentrum

Mittelkonsole

Anhänge-

modul

Kombi-

instrument

Sicherheits- u.

Informations-

modul

Fahrzeug-

zentrum

Mensch-

Maschine-

Interface

Park Distance

Control

Digitale Diesel

/Motor

Elektronik 1

Adaptive

Cruise

Control

Schaltzentrum

Lenksäule

A-Säule links

B-Säule links

A-Säule

rechts

B-Säule links

Tür vorne

links

Sitz Fahrer

Audio System

Kontroller

Tür vorne

rechts

Sitz hinten

Aktive Roll-

Stabilisierung

Dynamische

Stabilitäts-

kontrolle

Elektronische

Getriebe-

steuerung

Sitz Beifahrer Sitzmodul

Fahrer

Sitzmodul

Beifahrer

Antennentuner Multi Media

Changer

Audio-CD

Wechsler Videomodul

Bedienzentrum

Mittelkonsole

Fond

Adaptive Light

Control

Elektronische

Dämpfer-

kontrolle

Elektromech.

Feststell-

bremse

Drehraten-

sensor

(kein SG)

Sitzmodul

Beifahrer

hinten

Powermodul

Digitale Diesel

/Motor

Elektronik 2

Schiebehebe-

dach

Chassis

Integration

Module

Verstärker

Navigations-

system

Telefon-

interface

Spracheingabe-

system

Kopfhörer-

interface

Heckklappen-

lift

Sitzmodul

Fahrer hinten

Standheizung/

Zuheizung

Controller

Wischermodul

Series

optional

Diagnose-

Zugang

Zentrales

Gateway

Modul

Car Access

System

Türmodul

Beifahrer Türmodul

Fahrertür

Türmodul

Fahrerseite

hinten

Türmodul

Beifahrerseite

hinten

ONBOARD DIAGNOSIS DELIVERS AN INTENSIVE MIX OF DATA OF A COMPLEX FAILURE-SITUATION


Diebstahl-

warnanlage

Reifendruck-

kontrolle

Regensensor

Lichtschalt-

modul

Heizungs-

bedienteil

Heizungs-

bedienteil

(Fond)

1-Achs-

Luftfeder

Bedienzentrum

Mittelkonsole

Anhänge-

modul

Kombi-

instrument

Sicherheits- u.

Informations-

modul

Fahrzeug-

zentrum

Mensch-

Maschine-

Interface

Park Distance

Control

Digitale Diesel

/Motor

Elektronik 1

Adaptive

Cruise

Control

Schaltzentrum

Lenksäule

A-Säule links

B-Säule links

A-Säule

rechts

B-Säule links

Tür vorne

links

Sitz Fahrer

Audio System

Kontroller

Tür vorne

rechts

Sitz hinten

Aktive Roll-

Stabilisierung

Dynamische

Stabilitäts-

kontrolle

Elektronische

Getriebe-

steuerung

Sitz Beifahrer Sitzmodul

Fahrer

Sitzmodul

Beifahrer

Antennentuner Multi Media

Changer

Audio-CD

Wechsler Videomodul

Bedienzentrum

Mittelkonsole

Fond

Adaptive Light

Control

Elektronische

Dämpfer-

kontrolle

Elektromech.

Feststell-

bremse

Drehraten-

sensor

(kein SG)

Sitzmodul

Beifahrer

hinten

Powermodul

Digitale Diesel

/Motor

Elektronik 2

Schiebehebe-

dach

Chassis

Integration

Module

Verstärker

Navigations-

system

Telefon-

interface

Spracheingabe-

system

Kopfhörer-

interface

Heckklappen-

lift

Sitzmodul

Fahrer hinten

Standheizung/

Zuheizung

Controller

Wischermodul

Series

optional

Diagnose-

Zugang

Zentrales

Gateway

Modul

Car Access

System

Türmodul

Beifahrer Türmodul

Fahrertür

Türmodul

Fahrerseite

hinten

Türmodul

Beifahrerseite

hinten

~17 Mio. Vehicles in the field ~4.000 dealerships in 90 countries, ~50.000 service people Up to 65 Electronic Control Units in a single BMW 1.000 individual, selectable Car Options >1 GByte Functional Software, 15 GByte Data onboard ~2.000 Customer relevant Software Functions ~12.000 Diagnostic Trouble Codes implemented in Onboard Diagnosis ~3.000 Metric Values in all ECUs in average per car ~ 10.500 Testmodules for all BMW series ~ 34.000 Schematics documents Up to 60.000 Diagnosis Sessions per day worldwide total size of DataWareHouse >> 30TByte

VEHICLE DIAGNOSTIC DATA TODAY. QUANTITY AND VARIETY OF ON- & OFFBOARD DIAGNOSIS


1 Contents




5 Conclusion



MATURIY LEVELS IN VEHICLE DATA ANALYTICS. EVEN SIMPLE QUANTIFICATIONS ARE VERY BENEFICIAL

Level 1: Count / Know

Level 2: Qualify / Compare

Level 3: Analyse / Understand

Level 4: Forecast / Predict

Level 5: Suggest / Advise

Count

Qualify

Analyse

Predict

Advice


PREDICTIVE ANALYTICS CHALLENGE: FEEDBACK DATA TO REALIZE COHERENCE AND CAUSALITY

Vehicle Design

Failure Avoidance

Test Strategy

Failure Appraisal

Customer Sensitivity

Quality Function Deployment

Production Optimisation

PartsQuality + Dimensioning

Customer Understanding

Diagnostic Trouble Codes Environmental Conditions

Symptoms, Testplans

Defect Codes

Testmodules, DiagnosisCodes

LabourCodes Replacement Parts

Vehicle-Identification

Repair Advice

ECU Metrics

coherence

causality


DATAMINING THE DIAGNOSIS PROCESS IN DETAIL. VISUALISATION OF THE OFFBOARD DIAGNOSIS


A-PRIORI ANALYTICS TO FIND ADVANCED CUSTOMERS USAGE AND FAILURE PATTERNS

Find the causal failure patterns in vehicles with specific critical defects using a Sequence Analysis.

A-priori datamining methods with SystemML™ in a BigData environment compute results near realtime.

Numerous „events“ during a vehicle‘s

Lifecycle (production, diagnosis, warranty, etc)

Millions of historic datasets of the BMW & Mini

fleet. Billions of individual attributes available.

© 2012 BMW & IBM Corporation

All chains of events for cars with a specific defect

All chains of events for all cars.


1 Contents




5 Conclusion

Page 13 Advanced Automotive Diagnostic Systems, 22.-24.04.2013


THE FACTS PROCESS AT BMW. FIELDDATA ANALYSIS FOR CUSTOMER SATISFACTION

Analytical Helpdesk (Tickets)

Data

assignment

Datasources

and interfaces

Support

of

professionals

(OnePager / project

description )

Vehicle

file

market

radar FBM-Viewer

Apps for internal

R&D experts (actually more than 120

Apps available)

Analytic-

Dashboards

and Applications

Tele- service

DMS DWH Parts

FBM

...

Internal Customer (Requirements)

Self-Service

... ... ... ... ... ... ... ... ... ...

... ... ... ... ... ... ... ... ... ... Repeat Visit

Repeat Repair Monitoring TÜV-Targets

Service-

history

Monitoring

Analysis of

Diagosis &

Flashupdates

... ... ... ... ... ... ... ... ... ...

... ... ... ... ... ... ... ... ... ... Satisfaction

[%] ?

What

helps … ?

Qualtiy after

Warranty ?

Field

penetration?

Problems in

Repair?

CoC

Making the data available group wide.

Experience in DataMining


http://icongal.com/gallery/icon/53635/256/server_ibm_backup

http://icongal.com/gallery/icon/54086/256/data_optical_media_devices

http://icongal.com/gallery/icon/75616/256/graph_chart_business_report_device


http://icongal.com/gallery/icon/48056/128/gear_wheel_cog_system


THE AGILE FACTS PROCESS. CRISP DATA MINING AND SCRUM COMBINED

BMW-

Data warehouse

1

Request /

Question

Evaluation

4

Data

Preparation

Calculation /

Modelling

3

Business

Understanding

Data

Understanding

2

Typical FACTSProcess Steps:

1 Question of Department X: Automatic

Detection of an important vehicle

annoyance in the field.

2 Balance of request: How can the question

be answered with specific data available

3 Initial concept (FACTS) and realization of

data load, modeling. Iterative („Scrum“)

enhancements with enquirer.

4 Presentation of Results, evaluation of

Business Case and definition of

Deployment.

5

Deployment in FACTS App-Store as

Webservice for self-service Realtime-

Analysis (defined users with specific

access rights).

FACTS Process - CRISP & SCRUM:

Deployment 5


PREDICTIVE ANALYTICS TOOLS CLASSICAL DATAMINNG TOOLS FOR EXPERTS ONLY.


THE TOOLCHAIN FOR DATA ANALYTICS. INTERACTIVE TOOLSET TO DISCOVER THE ISSUES


THE BMW FACTS ANALYTICAL APP STORE. PREDICTIVE ANALYTICS AS SELF SERVICE PROCESS

Welcome to BMW FACTS Analytical APP Store


1 Contents




5 Conclusion



Understanding the vehicle quality and realizing the customer impression in the field is a complex multidimensional task.

On- and off-board diagnosis play an essential role, but need interpretation by the engineers and developers.

FACTS delivers a process to answer many questions by combining the data available.

Predictive analytics is provided as a set of analytical apps, encapsulated and simplified to deliver results as an interactive self service process.

By enabling intensified usage of feedback from the field we understand and improve customer satisfaction.

FACTS DELIVERS INTERACTIVE, USER AND CUSTOMER CENTERED BUSINESS ANALYTICS AS SELF SERVICE


THANK YOU VERY MUCH FOR YOUR ATTENTION ! QUESTIONS ?

Page 21

Documents

ADVANCED DIAGNOSTICS AND PREDICTIVE ANALYTICS OF …iecon2013.org/files/IECON2013_IF4_01_Prenninger.pdf · advanced diagnostics and predictive analytics of vehicle data ... advanced