Quality & Warranty Analysis Tool - · PDF fileQuality & Warranty Analysis ToolQuality &...

Quality & Technical Support

Volvo Truck CorporationMicke Rydbeck, 25310, 20070523

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Quality & Warranty Analysis ToolQuality & Warranty Analysis Tool

Volvo Truck CorporationMicke Rydbeck



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Micke RydbeckProjects Management, Warranty Systems, Volvo Truck Corporation

Stockholm, May 23, 2007

Applying Analytics to Predict and Prevent Critical Warranty Issues



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Agenda

1. Volvo Truck Corporation

2. Why a new Tool

3. Improvements

4. Future



4

The Volvo Group Organisation

MackTrucks

RenaultTrucks

VolvoTrucks

Volvo Aero

FinancialServices

AB Volvo

BU

SIN

ES

S

AR

EA

SB

US

INE

SS

UN

ITS

Volvo 3P

Volvo Powertrain

Volvo Parts

Volvo Information Technology & Others

Buses ConstructionEquipment

VolvoPenta

Volvo Logistics



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Core Values

EnvironmentSafetyQuality



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Volvo Trucks in 2006

EmployeesDeliveries (units)

03

04

05

75,300

103,700

03

0420,800

05

19,000

21,000

97,300

06105,500

0621,400



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Importers, Dealers, Service PointsVolvo Truck Corporation 2006

Service Points

Europe1.000North America

350

South America130

Others380

Total 1 860

Europe270North America

250

South America130

Others400

Dealers

Total 1 050

Approximately 20.000 Mechanics



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Volvo Trucks Quality & Warranty focus

Truck UptimeTruck Uptime

Warranty cost Warranty cost

Fault frequencyFault frequency



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Agenda


2. Why a new Tool

3. Improvements

4. Future



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Why a new Quality & Warranty Analyse Tool?

Systems• Several systems and tools, using

multiple sources of data.

• Limited functionality for automatic processing of large amounts of data, e.g., trend analysis.

• Few pre-defined and automatically generated output reports/charts.

QMS STINS

TWS

Harry QMF



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Work Approach

• Large amounts of manual work

• Sample test analysis rather than large volume data analysis.

• Forecasting accuracy not good enough.



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1. Time and resource consuming work process,

2. Reactive rather than proactive problem solving,

3. Contradictory results and confusion,

4. Higher warranty costs than necessary,

5. Insufficient approach to warranty cost recovery.



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A business case for QWAT investment focuses on realizing direct savings, recoveries, and efficiency gains, as well as indirect cost avoidances

= “Soft” effects

Savings

• Identification of suspect claims

• Infrastructure

Savings

• Identification of suspect claims

• Infrastructure

Recoveries

• Increased supplier recoveries

Recoveries

• Increased supplier recoveries

Efficiency Gains

• Productivity increase

– Data access and reporting

– Analysis

Efficiency Gains

• Productivity increase

– Data access and reporting

– Analysis

Cost Avoidance

• Early identification of defect parts

”Soft” Effects*

• Increased customer satisfaction, both internally and externally

• Freeing up of capacity due to fewer warranty actions, both internally and at dealers

* NOT considered in the business case.

= Core effects – Direct warranty payments and costs

= Indirect effects – Cost avoidance



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Main ArgumentsMain Arguments

• To base the project on a (proven) pre-packaged solution

• Easy-to-use user interface

• Advanced functionality ensuring a more proactive approach

• SAS-solution meets future business demands.

• To base the project on a (proven) pre-packaged solution

• Easy-to-use user interface

• Advanced functionality ensuring a more proactive approach

• SAS-solution meets future business demands.

Why we chose SWA Solution



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Applying the SAS’ Emerging Issue Detection indicates substantial savings in lead time for issue detection

Actual – Jan ’03Discovered via dealer

site visit

SAS POC – Oct 02

BatteryClaim proportions for first 12 sales months

EXAMPLE

The Volvo Proof of Concept

• ”Norm line” calculated based on five years of historical data.

• Alerts created when production date failure rates exceed ”norm line”.

• Evaluation and prioritization using claims’ cost index.

In this example, a three months lead time reduction for the detection of the battery issue could have been realized

Source: SAS proof of concept on Volvo data in October 2003



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Agenda


2. Why a new Tool

3. Improvements

4. Future



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Improvement areas by SAS tool usage

Suspect claimsMore efficient Dealer Audits

Supplier Warranty RecoveryIncreased number of supplier penetration

Analysis and report quality, productivity and lead-timeAutomatically generated standard reports, reducedadministration and easier communication

Quality Cost avoidance – Early Warning DetectionImprove Product Quality Process, lead-time

InfrastructureDelete multiple data sources, analysis and report applications



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Product Quality Process

Fault Frequency

0,18

0,20 0,20

0,19

0,15

0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,35

Feb-

04M

ar-0

4Ap

r-04

May

-04

Jun-

04Ju

l-04

Aug-

04Se

p-04

Oct

-04

Nov-

04De

c-04

Jan-

05Fe

b-05

Mar

-05

Apr-0

5M

ay-0

5Ju

n-05

Jul-0

5Au

g-05

Sep-

05O

ct-0

5No

v-05

Dec-

05Ja

n-06

Feb-

06M

ar-0

6Ap

r-06

May

-06

Jun-

06Ju

l-06

Aug-

06Se

p-06

Oct

-06

Nov-

06De

c-06

Jan-

07Fe

b-07

Mar

-07

Apr-0

7M

ay-0

7Ju

n-07

Jul-0

7Au

g-07

Sep-

07O

ct-0

7No

v-07

Dec-

07

Assembly month

Claims/vehicle

3 months 6 months 12 months Forecast 3P Year End Commitment

FH Western Europe VMT 030Module team 030One common way to measure• Fault frequency• Unplanned stops

Standard Reports

Reduce manual work with reports



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Warranty Claim Handling

Monthly Warranty Reports

Indicate areas for targetedaudit

Market / Dealer performancefollow up

Payments per Truck



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Early Warnings

Emerging issues indication AutomatedSpecified watch lists

Root cause analysisDrill down functionality



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QWAT reduce the number of sources of information

QMS STINS

Before After

TWS

Harry

QWAT Tools

QMF

EUDID + Global DB

UCHP VDB GPS

VDA KOLA QJS

STINS



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Agenda


2. Why a new Tool

3. Improvements

4. Future



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A Global Tool being implemented at Volvo

MackTrucks

RenaultTrucks

VolvoTrucks

Volvo Aero

FinancialServices

AB Volvo

BU

SIN

ES

S

AR

EA

SB

US

INE

SS

UN

ITS

Volvo 3P

Volvo Powertrain

Volvo Parts

Volvo Information Technology & Others

Buses ConstructionEquipment

VolvoPenta

Volvo Logistics

QWAT ”USERS” (excl NAD)8 Power Users

92 Advanced Users79 Basic Users

Total 179



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QWAT focused issues 2007-2008

1. Data Quality

2. Develop Reports

3. Train Users

4. Integrate in processes



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Thank you for your attention !

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