KPI

Top Operational Key Performance Indicators for Truck

Handbook – 1st editionOMCD/E, January 2008

Author: OMCD/E, January 2008 1Daimler Trucks

Executive summary8 top operational Key Performance Indicators (KPIs) were selected for standardization within Daimler Truck. The

purpose of standardizing these selected KPIs in all operating units is to generate a common platform for steering

manufacturing operations and achieve company-wide transparency and a platform for good practice sharing in order

to ensure sustained continuous improvements in Daimler Truck manufacturing operational excellence

This report documents the KPI

standard definitions which were

derived with a project team

comprising representatives from all

Truck regions. The definitions were

approved by members of the

Manufacturing Leaders Council

(MLC) and Truck Executive

Committee (TEC).

A proposal for integration of the KPIs into the Truck Scorecard system was approved in January 2008. The following

chapters describe the steering goal, the calculation method, the measuring points and real plant examples for each

of the top operational KPIs. The approved proposal for integration into the Truck scorcard system and reporting lines

is also documented. In addition, a Truck wide IT platform for collection, consolidation and reporting of the KPI data

is presented.

Figure 1: 8 top operational KPIs for standardization throughout Daimler Truck manufacturing facilities

Top Operational KPIs•HPU (hours-per-unit)•Throughput time•Direct run•K-factor•Ratio•0-ppm supplier•On-time-delivery•APA* (delivery product audit)* Auslieferungsproduktaudit


Handbook list of contents

Top Operational KPI project team and region representatives

Top Operational KPIs – steering goals, calculation, measurement and examples

Hours-per-unit Ratio

Throughput time 0-ppm supplier

Direct run On-time-delivery

K-factor (aggregates), OEE (trucks) APA (trucks), 0-ppm Customer (aggregates)

KPI integration into Daimler Truck scorecards

Reporting and KPI IT platform

Performance dialogue and best practice exchange

Appendix: Important project decision milestones; contacts at OMCD

2

1

4

3

5

2.1

2.2

2.3

2.4

2.5

2.6

2.7

2.8

6


1. Top Operational KPI project team and region

representatives


Project team incorporated all Daimler Truck OUs and relevant CFUs to enable cross divisional standardization

MLC:

Project Leader

T. Jung

Project Core Team

Project support

P. Hoffmann

Dr. M. Dostal, Martin Daum, Roger Nielsen, Yoshitaka Taniyama, Ronald Linsmayer,

Hermann Doppler, Dr. Holger Steindorf, Werner Thurner, Dr. Christoph Siegel

Back-office

McKinsey

Truck EU

C. Hinsen

Truck NAFTA

G. Wootton

T. Pax-Slotto

Truck ASIA

M. Kogame

Y. Tokuda

Truck LA

G. Heinz

Subunit Axles/

Trans/Engines

M. Ried

Manufacturing

Planning TG

Dr. H. Cronjaeger

IT-System

A. Weichert /

W. Dischler

PARTICIPANTS AT KPI STANDARDIZATION CONFERENCE:From left to right: A.Corcoran (OMCD/E), H.Cronjäger (TGP/MMA), M.Ried (BCF/EA - Kassel), G.Heinz (TGE/BMQ – Brazil), M.Lenz (OMCD/E), G.Wootton (Freightliner), T.Jung (OMCD/E and Project Lead), Y.Tokuda (Mitsubishi-Fuso), K.Hasegawa (Mitsubishi-Fuso), N.Heide(ITC/TO – Wörth), P.Hoffmann (OMCD/E), R.Jung (TGP/TT – Rastatt), W.Dischler (OMCD/E), A.Knuettel (TGP/ENP – Mannheim), not in picture C.Hinsen (TGE/O – Wörth)

Figure 2: Top operational KPI standardization conference June 2007

1


Agreement on steering goals and definitions was the starting point for the KPI standardization

APA*

On Time Delivery

Throughput Time

Ratio

HPU

K-Factor/OEE

Direct Run (assy)

0-ppm Supplier

KPI DefinitionSteering goal of KPI

Audit forecast of how many defects the customer would find on the new vehicle

Focus production on final customer-related quality

Percentage of orders which achieved on time delivery (product released from production with

ready to ship status on delivery date)Planning and process stability

Measures the time from giving production number to completion of final product release

Reduce capital cost and handling time in the production process

Ratio of direct labor improvement (total actually improved hours to planned standard hours)

Direct labor productivity improvement

Average total hours worked (incl. all direct, indirect, salary) per production unit completed

Track total labor flexibility and efficiency

Overall equipment efficiency of a plant based on actual vs. planned output of units (i.e. bottleneck)

Line productivity based on bottleneck equipment

Ratio of units passing straight through final assembly without remaining defect or being taken

offline for reworkStability of manufacturing process

Number of defect parts out of 1 million for parts received in selected month

Supplier quality management

* Aggregates use 0-ppm customer instead of APA to reflect customer satisfaction

1


2. Top Operational KPIssteering goals, calculation,

measurement and examples


HPU (hours-per-unit)

Description: average hours-per-unit (engine, axle, transmission or truck) based on total labor hours including direct, indirect and salary functions

Steering goal: Labor efficiency, labor flexibility

Level 1 calculation model:

HPU = actual working hoursactual units produced

Implementation / Measurement points:

• Actual worked hours based on time-stamping (badging at FLLC) data. Where time-stamp data not available (e.g. salary functions) assumptions can be made

Base data required for KPI aggregation:

• Actual worked hours for direct, indirect and salary functions

• Actual number of units produced

Primary shopfloor levers:

Hierarchy relevance*:

Shopfloor KPI:

Abbreviation: HPU Applicability: x TM x TE x TN x TA

x E1 x E2 x E3 E4 E5

HPU

CI* activities Flexibility

Additional note:Hours-per-engine, hours-per-transmission and hours-per-axle will report according to heavy, medium and light duty categories. Truck is not required to report according to product or product category.

* Implies possible applicability to scorecard

x yes no

Tracking of KPI on shopfloor boards recommended (direct workers only)

Unit: hrs/unit

HPUFACTSHEET

DEFINITIONCALCULATION

MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Production volume

CI* continuous improvement

2.1


HPU*

(HPV,HPE,

HPT,HPA)

Actual number of units produced

Total paid worked hours per period

Actual paid direct hours worked

Actual paid indirect hours worked

Actual paid salary hours worked

- Assembly (body, paint, cab, final assembly)

- Machining (strategic content, e.g. 5c’s)

- Controlling/IT- Human Resources- Logistics- Maintenance- Planning/Organization- Purchasing indirect- Quality- Service Operations- Apprentices

*Definition based on the reference model of Harbour Consulting Inc., Quarterly report frequency – YTD-valuesRemark: paid working hours = actual worked hours (overtime effect not included)

Actual hours/monthe.g.ZEM@WEB

Actual units/monthe.g.TMC

2.1HPU

FACTSHEETDEFINITION

CALCULATIONMEASURE-

MENT POINTSSHOP FLOOR

LEVERSPLANT

EXAMPLE

HPU – calculation model for Truck operating units reached at MLC meeting in Tokyo on December 3rd 2007

For more detail on HPU definition, including details of what‘s considered and what‘s not considered, please referto the OMCD Harbour GuidelineContact: Ralf Hieber, [email protected]


Agreement on common HPU definition (MLC, Dec. 3rd)

NONONOYESYESHPU by segment (HD, MD, LD) or product and category HPV, HPE, HPT, HPA

INININININDIRECTS for manufacturing – body shop, paint, cab trim, final chassis/finish&test

ININININININDIRECTS directly supporting production –11 functional areas, e.g. logistics, mainten.

ININININININDIRECTS outsourced core functions –1.in-plant logistics, 2.maintenance, 3.production

OUTOUTOUTOUTOUTINDIRECTS outsourced (non-core functions) – e.g. canteen, janitorial, fire service

INININININSALARIES for series production (e.g. for series planning & engineering)

OUTOUTOUTOUTOUTSALARIES for future product planning & engineering

YESYESYESYESYESQuarterly report frequency –YTD-values

OUT

IN

IN

TRUCK TN

(IN –AGGR)

IN

IN

TRUCK TM

MLCAgreement

TRUCK TA

TRUCK TE

HARBOUR DEFINITION

OUTOUTOUT - VEHICLEDIRECTS for component manufacturing in plant (part machining or fabrications)

INININDIRECTS for internal major component transfer (e.g. door subassembly)

INININDIRECTS in series production

� concensus

�

�

�

�

�

�

�

�

�

�

�

HPUFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.1


Strategic product content: Manufacturing areas measured

VEHICLE ASSEMBLY

•Body Shop

•Paint Shop

•Cab Assembly

•Final Assembly & Test

AXLES

•Axle housing

•Drive shaft

•Carrier

•Planetary Gear

•Hub

•Front Knuckles

•Assembly and Test

ENGINE

•Cylinder Block

•Cylinder Head

•Camshaft

•Crankshaft

•Connecting Rods


TRANSMISSION

•Carriers & Cases

•Converters & Stampings

•Clutches & Gears

•Shafts

•Valve Body


Source: Harbour Consulting

HPUFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.1


Actionable levers to reduce HPU

3. Production volume

5.

2. Flexibility

4. Product (EHPU)

HPU

Reduction

1. Continuous Improvement (KVP)

• Improving the operating point (“Betriebspunktes”) by block breaks

• Flexibilisation of salary and indirect by new working models

• ...

• Reduction of variants• Production-oriented product design (serie and new type)• ...

• Production volume increase • Development of productions system towards “runner plant”

• ...

• Intensive the CI portion of T(e)-workers und GMK-AK• Realization of annual CI by indirect and salary people...

• Reduction of value adding (“Fertigungstiefe”) by outsourcing of production and service functions

• Reduction of actual working hours (“Anwesenheitsstunden”) of workers by automatization...

Outsourcing or

Automatisation*

Outsourcing/automation will affect HPU figure, but is not an improvement as targets will be readjusted accordingly

Supported byHPU simulationtool

HPUFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.1


Plant example - HPU split by functions and areas allows detailed analysis of current performance

Measure performance of labor productivity including all labor classifications (Direct, Indirect and Salary

Manufacturing

AreaBody

Paint

Cab Trim

Chassis Ass./

Final

11 Functional AreasAssembly (A)

Machining (M)- only Aggregates

Controlling, IT (C)

Human Resources (H)

Logsitics (L)

Maintenance (MA)

Planning//Engineering (P)

Purchasing indirect (PU)

Quality (Q)

Central Site Service

Operations (S) Apprentices

(AP)

AND…

Labor

ClassificationDirect Hourly

Indirect Hourly

Salary

Focus on all functions for series production

Assb. Logistic Quality

Maint-

enance Other Total

Body 15.1 2.1 1.4 0.6 0.2 19.3

Paint 20.1 2.8 1.8 0.8 0.3 25.8

Cab Trim 37.7 5.3 3.4 1.4 0.5 48.3

Chassis/Final 52.8 7.4 4.8 2.0 0.7 67.3

Total 125.7 17.7 11.3 4.8 1.6 161.1

(In add., e.g. Mercedes-Benz Cars have 50 measuring points of HPU to track, report and optimize – mainly center level)

HPUFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.1


Throughput time

Description: Measures the manufacturing lead time from giving production number to completion of final product release

Steering goal: Reduce capital cost and handling time in the production processes


TPT = final product release time –earliest time at which production number stamped to frame or cab


• Final product release stamp• Earliest time of production number stamping to vehicle frame / cab for Truck plants

• Final assembly begin for powertrain


• Sum of throughput times• Number of assembled units



Shopfloor KPI:

Abbreviation: TPT Applicability: x TM x TE x TN x TA

x E1 x E2 x E3 x E4 E5

Note:Throughput time for multiple lines to be based on weighted average.

x yes no

Throughputtime

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Unit: hours

Throughput Time

Direct Run

K-Factor

Change over time

Inventory level

Tracking of KPI on shopfloor boards recommended

2.2



Throughput time – calculation model agreed at KPI project standardization conference (June 2007)

Throughput

time (hrs)

Final product release

Date of giving production

number*

*Assignment of frame or cab number in Truck plants, assembly start for aggregate plantsSource: Standardization Conference

Throughputtime

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Key points

� Report only for assembly

lines at this time (Truck

and Powertrain plants)

� Measure throughput time

from giving production

number (assembly begin)

to final product release

� Measuring unit is working

time in hours (without

planned downtimes)

2.2


CAB PAINT

TPT for vehicle assembly begins at the earliest assembly start point and ends with final release

FRAME/CHASSIS ASSEMBLY FRAME PAINT FINAL ASSEMBLY

CAB TRIMLINECAB-IN-WHITE

VEHICLE TESTING

FINISH/OFFLINE

FINAL INSPECTION

Measurement start point in this instance at cab-in-white first fixturing as thisbegins earlier than frameassembly

Timeline

Measurement end pointdirectly after final inspection process (i.e. vehicle released)

Example of possible buffer points

Throughputtime

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.2


TPT for powertrain assembly begins at the earliest assemblystart point and ends with final release

Assembly stage 1

Measurement start point after loading of firstprimary part onto final assembly line – „assemblybegin“

Measurement end point directly after final inspection process (i.e. aggregate release)

Example of possible buffer points

Throughputtime

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Assembly stage 2 Assembly stage n Testing

Timeline

Example of possible exit points for rework

2.2


Throughput time actionable levers

Throughput

time

Direct Run OEE

KPI tree as

seen on

shop floor

Actionable

levers to

improve

KPI

Change over

time

Problem

follow-up

Dedicate machines

Separate manual/auto work content

Remove over-processing

Multi-barrel

Fix change system

…

Inventory

level

Problem

follow-up

Create escalation levels

Increase logistics frequency

Build to order

Change to flow layout

Strategic inventory layout

…

See Direct

Run..See OEE..

Throughputtime

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.2


Throughput time example – São Bernardo do Campo

Throughput Time

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Details

Representation: Bar chart

Calculation method:

Throughput Time (h) = Final product release - Date of giving production number*

Data source: IT-Systems CGEM (MS-application) and Mag-Agera (Mainframe application)

Focus: Improvement of the product delivery process

Process goal: Reduction of the manufacturing time

Legend:* Assignment of frame number in Truck plants, assembly start for aggregate plants

2.2


Implementation of throughput time in São Bernardo do Campo

Throughput Time

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

The throughput time is the total manufacturing time of an aggregate, measured between the beginning of the product assembly and the final release of the product, including the steps:

• Product Assembly in main lines• Process Test • Assembly Process in the lines after test • Final Release

If failures occur (product rework or fill up of parts) between the processes steps above, the respective overtime will be included in the calculation of the indicator.

Assembly Main

LinesTest

Process

Assembly After

Test LinesFinal

Release

Rework Rework Rework

Normal

Flow

Normal

Flow

Normal

Flow

Failures Failures Failures

2.2


Throughput Time

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Throughput time measured from beginning engine assembly to final aggregate release

Assembly Main Lines

Unit

1 cycle time period

Unit

1 cycle time period

Work Station

Beginning Final

Start of

Engine

Assembly

Point A Point B Point D

B - A = Engine Assembly Lead Time Engine Test Lead Time

Assembly After Test Lines

Unit

1 cycle time period

Unit

1 cycle time period

Work Station

Beginning Final

Point E Point F

F - E = Assembly Powerpack Lead Time

F – A = Product THROUGHPUT TIME

Final Release

of the

Aggregate

Test Process

Unit

2.2

Example São Bernardo do Campo: calculation model for throughput time


Throughput Time

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Point D

Engine Test

Point E

Paint ShopPoint F

Assembly Powerpack

Point A

Assembly Line beginningPoint B

Assembly Line Final

CarrinhoCarrinho CarrinhoCarrinhoCarrinho CarrinhoCarrinho CarrinhoCarrinho

CarrinhoCarrinhoCarrinho CarrinhoCarrinho CarrinhoCarrinho

São Bernardo do Campo – throughput time in the powerpack assembly (engine and gearbox)

Engine assembly start

=

Engine input data in

the IT-systems

Powerpack final release

=

powerpack data input in

the IT-systemsMag-Agera

CGEM

Powerpack

Assembly line

Engine

Test Bench

Engine

Assembly line

Points D, E & F:

Intermediary measurement points

for traceability additional purposes

2.2


Throughput time example for Kawasaki Plant

Details


Calculation method: Throughput time (Vehicle)= Cab welding lead time + Painting lead time +Trimming lead time + Assembly lead time(Refer to the structure)

Data source: Calculate from units per hour every month

Scope: Cab welding ON to vehicle assembly OFF.

Focus: Monitoring production lead time

Process goal: Reduction of manufacturing time

DIRECT RUNFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.2


Painting Trim

Througput time for the Kawasaki plant

DIRECT RUNFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Cab

welding

Painted

Cab

Storage

Final

Assembly

THROUGHPUT TIME OF VEHICLE

Cab welding Painting Trim Assembly

2.2


Direct run

Description: DIR is the percentage of units passing straight through final assembly without remaining defects or being taken offline for rework

Steering goal: Stability and robustness of manufacturing processes to avoid quality errors


DIR = number of units without offline defects*Total number of produced units

* Offline defect is a defect which cannot be repaired in the line and is discharged to rework area in order to carry out repair / rework


• Measured at discharge points in final assembly lines. For powertrain multiple discharge points, for Trucks single discharge point

• No multiple counts


•Number of produced units• Number of direct run violations



Shopfloor KPI:

Abbreviation: DIR Applicability: x TM x TE x TN x TA

x E1 x E2 x E3 x E4 x E5

Direct run

Employee training Defect reduction

Exceptions:

• Not measured for machining lines or subassembly lines at this time. To be installed on these lines later.x yes no

Unit: %

DIRECT RUNFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE


2.3



Direct run – calculation model agreed at KPI project standardization conference (June 2007)

Source: Standardization Conference

Direct

run

Number of units

without offline

defects

Total number of

units

Total number of

units

Units with offline

defectsOffline rejects

Offline reworks

(excl. finishing)

Missing parts

Units with …

• For vehicles, only measure defects remaining after finishing, since finishing should be considered normal process

• A Direct Run defect is a defect that can not be repaired in the line in cycle time and is thus discharged.

• Measure start point is start of final assembly

• Measure end point is after final assembly

Key points

DIRECT RUNFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.3


Measurement at every point at which the unit can be diverted from the main production line

Rework area

(z.B. Ausschleusepunkt)

End of line rework

area

Problem solved in line cycle time, direct run OK

Direct run ensures process stability in whole line. Only one violation count per unit. Q-Gate measurement points to be identified during KPI implementation phase

Assembly line

Unit

1 cycle time period 1 cycle time period

Problem NOT solved in line cycle time ⇒ violation of direct run

End of line finish

area

Any rework content at end of line is violation of direct run

××××��

Rework area

(z.B. Ausschleusepunkt)

DR ok DR not OK

��DR ok ××××DR not OK

Measure

here

DIRECT RUNFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.3


Direct run actionable levers on shop floor

Employee training

Defects*

Trained members on cell

Std work

sheet/auditSupplier Press Paint Assembly

Problem

follow-up

Problem

follow-up

Problem

follow-up

Problem

follow-up

Problem

follow-up

Problem

follow-up

Direct Run

Std work audit

Training school

Increase quality standardsvisualization on shop floor

Manpower planning

Sneaky checks

…

Stop at detection

Solve quality problems

Quality task force

Problem solving training

Quality alerts

Effective quality loops

…

KPI tree

as seen on

shop floor

Actionable

levers to

improve KPI

* All rejects and reworks not repaired in line in takt time

Indicates recommendation to track values at line/station level

DIRECT RUNFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.3


Direct run example Wörth plant

Details


Calculation method: Numer of vehicles without rework per period*Direct run % = --------------------------------------------------------------------------

Number of vehicles leaving assembly line in period*

Data source: ZWA system

Target value 07/08: Monitoring

Target responsibility: TE/OP, TE/OS, TM/ME

Focus: Improvement of process and product quality

Process goal: Reduce rework levels

Legend:* Period = day, month or year

DIRECT RUNFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.3


Custo

mer ord

er

Vehicle

delivery

RO LA

Bandabla

uf

BASEAZ, EP,

BP, AW

YardRepair shopBody reworketc.

YardRepair shopBody reworketc.

NA

Time line Cab-in-

white

Paint Trim Assembly Finish

Nacharbeit

SA

SLZV

Final

Inspection

Status NA is set in the FINISH system with an estimated final inspection target date and is passed to the next system.

SE

Wörth system adapted to distinguish between planned and unplanned finishing contentNew definition of the system status signals „BA“ and „NA“. „BA“ represents the vehicles which go through finish area with no quality issues outstanding (i.e. good direct run). NA represents the vehicles which go into finish area and require rework as well as other planned work (i.e. violation of direct run).

DIRECT RUNFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.3


Details


Calculation method: Number of products without rework per period*Direct run % = --------------------------------------------------------------------------

Number of products leaving assembly line in period*

Data source: CGEM (intern system) and Simsam


Process goal: Reduction of rework and offline complementation

Legend:* Period = day, month or year

DIRECT RUNFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Direct run plant example – São Bernardo do Campo plant

2.3


São Bernardo do Campo implementation of direct run

DIRECT RUNFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

CarrinhoCarrinho CarrinhoCarrinhoCarrinho CarrinhoCarrinho CarrinhoCarrinho

Point of Measurement

Assembly Line Release

Point of Measurement

Engine Test

Example of a Check-List

Measurement point is at the lastQuality Gate at the end of the assembly line or engine test

At the last Quality Gate acheck list is fulfilled and thequality data is recordedin the IT-Systems *

* reference for furtherinvestigation of root causes and performance statistics

Simsam

CGEM

2.3


Direct run – São Bernardo do Campo IT-system CGEM

DIRECT RUNFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Click – St

art

Definition of the problem type (assembly, missing part, etc.)

Indication of the parts affected

Registration of problem solving

2.3


DIRECT RUNFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Root Cause anaysis

Quality problem follow-up, IT-system CGEM enables quality problem tracking Quality performance

• per product

• per cost center

• per month / period

Top failures

Traceability

Missing parts pending

Others

2.3


K-Factor

Description: KFC is a metric for monitoring and improving the efficiency machining line bottlenecks

Steering goal: Improve machining line / plant productivity by identifying and addressing bottleneck equipment


KFC = good parts × planned cycle timeplanned production time

* Planned production time based on planned shift hours includingbreaks, TPM and group meeting times


• Measured for machining lines only• Line K-Factor is based on bottleneck machine• Plant K-Factor calculated by average K-Factor of bottleneck machines


• Number of bottleneck machines• Sum of K-Factor values for bottleneck machines



Shopfloor KPI:

Abbreviation: KFC Applicability: x TM TE TN TA


K-Factor

Equipment uptime Workrate Quality

Additional notes:

• Not applicable in truck/vehicle plants

x yes no

K-FACTORFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Unit: none


2.4



K-Factor – calculation model agreed at KPI project standardization conference (June 2007)

K-factor

Planned Production Time**

Actual output good parts

Total available time (24 hours/day)

Unscheduled time

Produced parts

Reject parts

Machine cycle time (TNG)

Key points

• Use for all machining

shops

• Planned production time

includes the time for team

meetings, lunch breaks

and planned TPM (i.e.

total scheduled time)

• K-factor is measured only

on bottleneck

• If many product lines,

report the average K-

factor for bottlenecks

Load/unload time

Machine auto cycle

*Unscheduled time is non-utilized shifts ** Gross running time incl. all breaksSource: Standardization Conference

K-FACTORFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.4


Machining

(5 C‘s)

K-Factor per line is based on the respective bottleneckmachine

K = 0,8 K = 0,7 K = 0,6 K = 0,5 K = 0,4K-Faktor plant machining area = average of bottlenecks, e.g. 0,6

⇒

K-Faktor reporting value is 0,6

K-Factor measurement based on bottleneck machines, aggregation to plant value by average

K-FACTORFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.4


K-Factor

Equipment availability

TPM time BreakdownChange-over

Problem follow-up

Problem follow-up

Problem follow-up

TPM scheduling

Solve breakdowns

Simplify machine design

SMED workshop SMED (Single minute exchange of dies)

Dedicate machines

New machinery

5s improvement

…

Member work rate

Absent-eeism

Trained members

Problem follow-up

Problem follow-up

STD work audit

Manpower planning

Flexible manpower system

Clean sheet bonus

Std work audit

Training / qualification

Re-balance work content

Accident alert

…

Quality

Rejects Reworks

Problem follow-up

Problem follow-up

Stop at defect


Containment

Std. work improvement

Quality alerts

Random checks

Design for quality

…

KPI tree as seen on shop floor

Actionable levers to improve KPI

K-Factor actionable levers


OEEFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

KAPITEL:

2.4


Mannheim example shows impact of optimizationmeasures on K-Factor

Stückzahlvorgabe:

35 FTE => 376 units (3 shifts)

K-Faktor: 0.52

376 units in 1440min ?

1. Before optimization

KFC = 376 units x 2.0min = 0,52

1440 min

K-Faktor: 0,75

35 AK => 540 Stk (3 Schichten)

540 Stück in 1440min

2. Optimization: AuF Mannheim

KFC = 540 Stk. x 2,0 min = 0,75

1440 min Before After Optimization

K-Faktor

0,52

0,75

+ 164 units in 3 shifts, e.g.

through utilization of the total

shifttime

K-FACTORFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.4


OEE – overall equipment effectivness

Description: OEE is a metric for monitoring and improving the efficiency of manufacturing processes

Steering goal: Improve assembly line / plant productivity by identifying and addressing bottleneck processes


OEE = good parts × planned cycle timeplanned production time*

* Planned production time based on planned shift hours excludingbreaks, TPM and group meeting times


• Measured for assembly lines only• Measure point is at end-of-assembly• If multiple lines, aggregate by weighted average


• Line / plant OEE values• Line / plant production volumes



Shopfloor KPI:

Abbreviation: OEE Applicability: TM x TE x TN x TA


OEE

Equipment uptime Workrate Quality

Exceptions:

• Powertrain plants will report K-Factor• Vehicle plants – for final assembly, trucks

leaving line are considered good partsx yes no

OEEFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Unit: %


2.4



OEE – calculation model agreed at KPI project standardization conference (June 2007)

OEE

Planned Production Time

Actual output good parts

Total available time (24 hours/day)

Lunch, breaks

Unscheduled time*

Team meetings

Planned TPM*

Planned downtime

Available time

Demand forecast (based on 1-yr Prod Plan)

Breakdown percent

Reject percent

Takt time

1

Planned loss

Planned cycle time

� Use OEE for

all assembly

lines

� If many lines

use weighted

average

� Planned loss

is planning

function to

derive

planned cycle

time, where

breakdown

and reject

percentage is

based on

historical

data.

Key points

*Unscheduled time is non-utilized shifts and non-utilized shift time, TPM = Total ProductiveMaintenance. Source: Standardization Conference, Top Operational KPI project, June 2007

OEEFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

KAPITEL:

2.4


OEE consists of three factors

OEE = AVAILABILITY ×××× PERFORMANCE ×××× QUALITY

1. AVAILABILITY

Availability takes into account down-time loss. That is, all events that stop planned production

2. PERFORMANCE

Performance takes into account speed loss, which includes all factors that cause the process to operate at less than

the maximum speed, e.g. equipment wear or operator inefficiency

3. QUALITY

Quality takes into account quality loss, which factors out produced pieces that do not meet quality standards

OEEFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

KAPITEL:

2.4


1. AVAILABILITY = operating time / planned production time

2. PERFORMANCE = (planned cycle time × total pieces produced) / operating time

3. QUALITY = good pieces / total pieces produced

For vehicle plants – all vehicles from end of line are considered good as qualityaspect is captured using direct run. Thus, quality factor = 1.

Performance factor will capture anydeviation in line cycle time fromintended cycle time

Captures any stillstands / downtimes

OEE = planned cycle time ×××× output / planned production time

The KPI calculation model for OEE is derived by:

OEEFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

KAPITEL:

2.4


Plant

OEE plant value = weighted average e.g. 0.8 if production volumes of all three lines equal

⇒

Measurement points: OEE per line measures the parts which leave the line (measurement point at the end of the assembly line)

OEE = 0.9 OEE = 0.8 OEE = 0.7

Plant OEE calculated based on weighted average according

to production volumes

Line 1 Line 2 Line 3

OEE measurement at end of assembly line, aggregation to plant value by weighted average

OEEFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

KAPITEL:

2.4


OEE

Equipment availability

TPM time BreakdownChange-over

Problem follow-up

Problem follow-up

Problem follow-up

TPM scheduling

Solve breakdowns

Simplify machine design

SMED workshop SMED (Single minute exchange of dies)

Dedicate machines

New machinery

5s improvement

…

Member work rate

Absent-eeism

Trained members

Problem follow-up

Problem follow-up

STD work audit

Manpower planning


Clean sheet bonus

Std work audit

Training / qualification


Accident alert

…

Quality

Rejects Reworks

Problem follow-up

Problem follow-up

Stop at defect


Containment


Quality alerts

Random checks

Design for quality

…



OEE actionable levers on shop floor


OEEFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

KAPITEL:

2.4


Ratio

Description: Ratio of total actual standard hours saved to planned standard hours based on actual production mix and volumes)

Steering goal: Direct labor productivity improvement


RAT = sum of standard hours saved to datetime allocation based on reference standard hours

for actual production program to date


• Standard hours documented in production plans• Improvements approved by industrial engineering


• Confirmed standard hours saved to date• Time allocation for actual production program

based on reference standard hours from 31st of December of previous year



Shopfloor KPI:

Abbreviation: RAT Applicability: x TM x TE x TN x TA

E1 x E2 x E3 x E4 E5

Ratio

CI* activities Design changes

Additional note:-

x yes no

Unit: % (year-to-date)

RATIOFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

CI* continuous improvement

2.5

Equipment upgrades




Ratio – calculation model for monthly values agreed at KPI project standardization conference (June 2007)

• Set reference standard

hours yearly, once, at the

beginning of the year

(31.12 previous year)

• Calculate actual

improved standard hours

against the reference

standard hours based on

the actual production

volumes

• Definition considers only

changes to standard

hours (TE)

• A set of reference

products, representative

for the full range, is ok

to use if it >90% coverage

Key points

Actual standard hour (TE)

improvement per unit

Actual produced units

(by product or representative)

Total actual standard

hours saved

Sum of planned stan-

dard hours

for production mix

Ratio

Standard hours (TE) at start of

year

Actual produced units

(by product or representative)

* Standard hour = standard planned time = Einheitenzeit TE

RATIOFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Note: Ratio evaluation in scorecards on the basis of year-to-date performance.

2.5


Ratio measurement assesses the impact of improvement activities on defined work processesIn plants where defined standard times per process / parts regulate the amount of direct labour required to manufacture / assemble a component, ratio is quantified based on approved and documented improvements in the work process. Approval is usually done by idustrial engineering.

Production planwith defined TE

Process optimisation, CI, TE improvement

Documentation and approval of improved process

Production planwith updated TE

RATIOFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Negative ratio: Part design changes or substitution of ”newer” parts can lead to negative changes in ratio – that means more standard time is required to fabricate / assemble the new part. Negative ratio effects due to design changes are not counted if the design change will be compensated by the customer paying a higher price for the product. For new parts / outsourced parts, reference time adjustment from month of introduction of new part or outsourcing

2.5


Ratio calculation based on TE changes of actual produced parts monthly

Ratio calculation – at the end of month X

what:

i = all parts based on parts numbers or individual representatives which were produced in month X

n = actual produced number of specific part number or representative in month X

*Premise: Representatives have to cover more than 90% of the actual produced parts spectrum

( ) ( )

1

100(%)

1

×

×

×−×=∑

i

plan

actualplan

actualnTE

nTEnTERatio

Source: TM Ratio Workshop – 2007-11-08

RATIOFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.5


Production Plant 1

cumulative (%) 2006 2007 2008 monthly ratio (%) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

target ##### ##### 3,4 target 0,5 1,1 1,6 2,1 2,7 3,2 3,7 4,2 4,8 5,3 5,8 6,4

Ratio improvement hours (tsd) 17368 Ratio improvement hours (tsd) 223 445 668 891 1113 1336 1559 1781 2004 2227 2449 2672

Standard hours (tsd) 504000 Standard hours (tsd) 42000 42000 42000 42000 42000 42000 42000 42000 42000 42000 42000 42000

actual ##### ##### 3,2 actual 0,6 1,1 1,4 1,4 3,0 3,4 3,9 3,9 4,9 5,6 5,6 #####

Ratio improvement hours 14700 Ratio improvement hours 240 460 600 600 1300 1400 1700 1700 2100 2300 2300

Standard hours (Basis 12/2007) 465000 Standard hours (Basis 12/2007) 43000 41000 43500 41500 43000 41000 43500 43500 43000 41000 41000

��

monthly values

0

1

2

3

4

5

6

7

8

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

%

actual

target

yearly values

0

1

2

3

4

5

6

7

8

2006 2007 2008

%

Ratio calculation based on month-by-month calculation with evaluation based on year-to-date performance

Compares sum of ratio hours until November with sum of standard hours on the basis of reference standard hours from 31st December of previous year

• 14700 = sum of saved standard hours = (240+460+…+2300)• 465,000 = allocated hours based on standard hours from

December of previous Year = (43000 + 41000 + …. + 41000 )

Color shows that although target reached in that month (3.0%), the year-to-date performance is not on track to reach the cumulative target of 3,4%.

RATIOFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.5

Example from TM scorecard

• 1700 = (TEACTUALAug) – (TEPLANDec) for all parts produced in August

• 43,500 = (ΣTEPLANDecember) for all parts produced in August


Freightliner example for Ratio calculation

Details


Calculation method: Benchmark improvement hours*Ratio % = ----------------------------------------------------------

Current standard hours* + benchmark hours*

Data source: VPS system within IMS

Focus: Direct labor productivity improvements

Process goal: To show the labor hour effect that CI events have in an area.

Legend:* Period = day, month or yearCI = continuous improvement

DIRECT RUNFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Benchmark pool improvement hours = ratio hoursStandard hours + benchmark hours = Reference standard hours from 31st December previous year for actual produced units

2.5


DIRECT RUNFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Plant performance with improvements from Web Focus reports

CI event at the plant

Reports generated

from VPS

=

At the end of the year the benchmark hours are purged from the standard

which sets a lower standard labor hour for the upcoming year.

Freightliner example for Ratio calculation

2.5


DIRECT RUNFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Gaggenau example for machining area shows planned continuous improvement activities to attain ratio target

2.5

EXAMPLE DATA

Kostenstelle Ratio Härte - Maßnahme - Projekt Einsatztermin Ratio Gesamt Ratio in 2007 Bereich Ratio Titel

Nummer Grad

291.5 421 5 Prozessoptimierung (Kopfkreis nicht mehr schleifen) Mrz 07 446 372 TT2 Grundlast

291.5 476 5 Optimierung Arbeitsorganisation (Bügelsäge vor Ort) Mrz 07 286 238 TT2 Projekt

148.5 467 5 Drehen Vorgelegerad mit zwei gegenüberliegenden Schneidplatten Mrz 07 320 267 TT2 Grundlast

143.5 478 5 Entfall Entgrat AVO durch Sauberkeitsstrahlen Mrz 07 165 138 TT2 Grundlast

135.5 562 5 Prozessoptimierung (PT Freigabenummer: 5532) Mrz 07 95 79 TT2 Grundlast

237.4 542 5 Entfall Entgratumfänge Mrz 07 2.388 1.990 TT2 Grundlast

290.5 561 5 Prozessoptimierung (Freigabenummer: 4313) Mrz 07 41 34 TT2 Grundlast

148.5 545 5 Entfall Hartbearbeitung einseitg GLK A3892624135 Mrz 07 40 33 TT2 Grundlast

255.5 388 5 A28 U-Stufe2 Mrz 07 482 402 TT2 Projekt

143.5 501 3 Optimierung Arbeitsorganisation (Doppelradschleifmaschine Buderus) Apr 07 701 526 TT2 Projekt

294.5 449 3 Ablauforganisation Hohlrad (Workshop Wertstrom) Apr 07 1.257 943 TT2 Grundlast

131.4 571 3 1. Schnittfräsen PT Freigabe 1438 Apr 07 36 27 TT2 Grundlast

143.5 564 3 Prozessoptimierung PT (Freigabenummer: 5099/509874892) Apr 07 237 178 TT2 Grundlast

136.5 573 3 Prozessoptimierung PT (Freigabenummer: 5915/5914) Apr 07 47 35 TT2 Grundlast

237.4 566 3 Umplanung GLK auf Trockenstossen Apr 07 180 135 TT2 Grundlast

294.5 446 3 Neumaschine Hohlrad (Hessapp/Workshop Wertstrom) Apr 07 100 75 TT2 Grundlast

294.5 470/471/473 3 Prozessoptimierung Hohlradfertigung (Workshop Wertstrom) Apr 07 500 375 TT2 Grundlast

131.4 574 3 Prozessoptimierung PT Freigabe (5782) Apr 07 309 232 TT2 Grundlast

290.5 469 3 Optimierung Arbeitsorganisation (Umplanung von VGW auf Stoßmaschine) Apr 07 800 600 TT2 Grundlast

290.5 567 3 Diverse Freigaben, Kostenstelle 290.5 Apr 07 34 26 TT2 Grundlast

257.5 451 3 Taktzeit Optimierung A21 Apr 07 500 375 TT2 Grundlast

255.5 388 3 A28 U-Stufe3 Apr 07 822 617 TT2 Projekt

135.4 559 3 Umplanung auf Hessapp Drehmaschinen Apr 07 184 138 TT2 Grundlast

Gaggenau 368 2 Neue Späneentsorgung Anpassung Verteilzeit Mai 07 1.000 667 TT2 Projekt

131.4 38 2 Umstellung auf Trockenfräsen Mai 07 400 267 TT2 Grundlast

255.5 578 2 Prozessoptimierung A28 PT (Freigabenr. 5262,5250,…) Mai 07 68 45 TT2 Grundlast

135.4 475 2 Werkzeugoptimierung U-Stufe2 (Wendeplatte Versuche) Mai 07 100 67 TT2 Grundlast

212.4 160 2 MOZA U-Stufe3 Umstellung auf System TE (Arbeitsorganisation) Mai 07 200 133 TT2 Grundlast

143.5 434 2 Bohrung Fertigdrehen entfall Bohrungsschleifen Mai 07 820 547 TT2 Grundlast

135.4 548 2 Ersatz f. Monforts durch 2 Hessapp Jun 07 2.800 1.633 TT2 Projekt148.5 506 2 Umplanen von Schleifen auf Hartdrehen Jun 07 500 292 TT2 Grundlast

253.5 569 2 Aufpackerhöhung auf 90 Stk an A16 bei allen Schiebemuffen Jun 07 500 292 TT2 Projekt

133.4 210 2 Ersatz Tetramill 2 BAZ Jul 07 1.200 600 TT2 Projekt

238.4 403 2 Umstellung von 2 auf 1 Schnitt Jul 07 670 335 TT2 Grundlast

136.5 539 2 Ersatz von 2 Reishauer AZA durch 1 RZ 400 Aug 07 800 333 TT2 Projekt

294.5 470/471 VV 030-05-05069: Hohlrad Okt 07 200 50 TT2 Grundlast

182.5 367 2 Optiemierung Waschkonzept (Workshop) Nov 07 600 100 TT2 Grundlast

131.4 550 2 Wera Entgrateinheit Nov 07 100 17 TT2 Projekt

122,4 577 2 Wera Hinterlegungsfräsmaschine (Kombimaschine) 2008 0 0 TT2 Projekt

290.5 2 Wälzfräsmaschine für VG-Welle 2008 0 0 TT2 Projekt

Summe 23.737 16.772

Härtegrade : 1 : Idee Neu umgesetzt Umgesetzte Titel

2 : Idee geplant und bewertet

3 : Idee umgesetzt Neue Titel

5: Maßnahme im Controlling Bestätigt


0-PPM supplier

Description: Number of defect parts out of 1 million for parts received from suppliers (Daimler internal and external) in selected month

Steering goal: Supplier quality management


0SU = # defect parts from supplier × 1,000,000Total number of parts received

Calculation method conform with CVD Quality Guideline 21


• All supplied units which are to be part of our products are regarded for calculation of 0-ppm

• PPM counting and rejecting policy to be conform with CVD Quality Guideline 21


• Number of non-conforming supplier parts• Total number of supplier parts received



Shopfloor KPI:

Abbreviation: 0SU Applicability: x TM x TE x TN x TA


0-ppm Supplier

Employee training Supplier management

Additional notes:

0-ppm supplier should report only delivered quality defects (i.e. the Q-part of the 0-ppm CVD Quality Guideline 21).x yes no

0-ppm supplier

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Unit: ppm


2.6



0-PPM supplier – calculation model agreed at KPI project standardization conference (June 2007)

0-ppm supplier

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

� O-PPM is already

measured in plants

� The reported figure

should be the total

PPM for the supply

base (total defects/

total parts)

• The 0-ppm figure

reported reflects only

the quality issues with

the delivered parts.

Source: Standardization Conference June 2007

0-PPM

Defect parts

× 1,000,000

Total received

parts

Found at gate

Found in plant

Found at gate

Found in plant

Found at gate

Found in plant

Reworked supplier

parts

Mislabeled supplier

parts

Rejected supplier

parts

Key points

ppm counting as per

CVD quality guideline 21*

* The CVD quality guideline 21 is currently being redrafted by TE/QM. Expected sign-off date for new version is Feb. 2008

2.6


Common PPM Concurrence letter forms basis for CVD quality guideline 21

“A common measure of quality is necessary in order to support the Board and EAC.“

PPM = x 1,000,000Nonconforming quantity

Received quantity

“…reflects the common understanding in the definition of the 0-km/0-miles PPM counting.“

The letter of agreement stipulates CVD guideline 21 for standarizationof 0ppm counting

0-ppm supplier

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

The CVD q

uality guid

eline 21 is

currently b

eing redra

fted by TE/

QM. Expe

cted sign-

off date for

new vers

ion is Feb.

2008

2.6


CVD guideline 21 outlines clear purpose and responsibilities for 0-ppm supplier counting

• CVD Guideline 21 outlines clear purpose and responsibilities

• The guideline also details the scope for 0-ppm counting

• The guideline clarifies the rules when parts are non-conforming / complaints

• CVD guideline 21 sets clear rules when units are to be counted in the ppm counting

Source: CVD Guideline 21 – method of counting ppm

0-ppmsupplier

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.6


Mercedes Benz special terms outlines rejecting policy with supplier

Inspection and Determination of the acceptance rate in the case of a lot return:

• In the event of inspection by the supplier, DC and the supplier agree to status feedback with initial test

results to DC within 10 working days of the supplier‘s receiving the goods

• If, after a maximum of 20 working days as of receipt of the parts by the supplier, no concluding inspection

result is available, the parts pertaining to this test report are regarded as accepted (periods may be

extended by mutual agreement).

Source: Mercedes-Benz Special Terms 18/02 – excerpt from Section 2.3

Delivery LinePreliminary 0ppm Report 100 NC

100 units 0ppm Report

First 30 parts defect –assembler rejects whole

box

Supplier has 20 working days to prove that not all 100 units are defect

Supplier inspection period

0-ppm supplier

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.6


The counting for PPM starts when the part contractspecifies Daimler ownership

Two delivery schemes are possible:• Supply ex-factory – ownership transfers to Daimler when parts leave supplier premises• Frei Haus (free shipping) – ownership transfers to Daimler upon delivery

PPM counting includes non-conformancies found at the gate (i.e. upon delivery) and found at the production lines

0-ppm supplier

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.6


0-PPM supplier – actionable levers

Member training Defects

Trained members on cell

Std work audit

Supplier Press Paint Assembly

Problem follow-up

Problem follow-up

Prob-lem fol-low-up

PPM*

Manpower planning


Clean sheet bonus

Std work audit

Training school


Accident alert

…

Stop at detect

Solve quality problems

Quality task force


Design for quality

Supplier development

Change supplier

…



Reject Rework Reject Rework Rework Rework Reject Rework

Prob-lem fol-low-up

Prob-lem fol-low-up

Prob-lem fol-low-up

Prob-lem fol-low-up

Prob-lem fol-low-up

Prob-lem fol-low-up

Prob-lem fol-low-up

* PPM as a general, both supplier and customer view


0-ppm supplier

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.6


Definition


Calculation method: Defect parts x 1,000,000PPM Supplier = ------------------------------------------------

Total received parts

Data source: SIGEQUALI System (IT system developed by MBBras)


Process goal: Reduction of defect parts received from suppliers

PPM SupplierFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

0-ppm supplier plant example – São Bernardo do Campo

2.6


São Bernardo do Campo – measurement for 0-ppm supplier through receiving inspection and ongoing analysis



MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

INPUT

National Parts

Evaluation &Measurement

by

- Sample quality analysis of supplied parts

TE/BTM

(TCL - Supplier Management– Trucks MBBras)

TE/BT

(TC - Production Trucks MBBras)

- On going quality analysis of the supplied parts used in the vehicles’ assembly

- Defects informed to TE/BTM to beconsidered in the ppm-Supplier

Qualityfeedbackabout

defect partsby

2.6




MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

São Bernardo do Campo – 0-ppm supplier gate inspection

Incoming goods areaBGE/BTM check Receipt bill

Data collection into the

IT corporate logistic systems

Quality database for the

registration of defect parts received *

* reference for further investigationof root causes and rejection statistics

IT-System SIGEQUALI

2.6




MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

São Bernardo do Campo – 0-ppm supplier IT-systemSIGEQUALI Data Source:

- PPM Daily Situation- On line update- PPM National

National suppliers ppm (cumulative)

PPM Monthly – national suppliers

Details about the rejection:- # Item- Supplier- Reason for reclaimation- Quantity- Others

2.6


OTD (on-time-delivery to the customer)

Description: OTD is the percentage of orders which achieved on-time-delivery from the customer persepective

Steering goal: Planning and process stability, customer satisfaction


OTD = number of units delivered on-time*Total number of units delivered

* on-time-delivery window is defined as -4 / +0 days for Truck, window for aggregates agreed between Truck plant and aggregates supplier


• For trucks, measured after completion of final inspection, i.e. ready-to-ship status approved

• For aggregates, measured against on-time-delivery at truck plants


•Number of late deliveries•Total number of deliveries



Shopfloor KPI:

Abbreviation: OTD Applicability: x TM x TE x TN x TA


OTD

OEE Direct run

Additional notes:

• For trucks, the tolerance for reaching OTD status is that the truck have ready-to-ship tolerance of -4/+0 days

• For aggregates, the tolerance is agreed with the customer truck plant

x yes no

Unit: %

OTDFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE


Throughput time

2.7



OTD (to customer)Calculation model

On-time Delivery

(percent)

Number of orders finished on

Committed delivery date

(finished product release)

Total number of finished

orders (ready to ship)

for truck plants

for aggregate and part plants

On-time Delivery

(percent)

Number of orders delivered on

committed delivery time (based

On call off)

Total number of delivered

orders

Key points

� Use freeze of production

plan as start point

� Use finish product release

as end point

� Common tolerance for

Truck plants -4 / +0 days

(approved in PEC

15.01.08)

� Granularity: calendar day

Source: Standardization Conference June 2007

� Only measure for "not in

plant" customer

� Use "call-off" as start

measure point

� Delivering time as end

measure point

OTDFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.7


Variances in 2007:

EULA = - 0/+3 working days

FLLC = <5 working days in offline

FUSO = - 0/+1 working days

production

planned

finish date

startchassis

Vehicle released by production for shipment

distribution

planning period

planning

fixedplanning

of finish

date

on time missed

Variance

Current OTD plant values:

Werk Wörth = 79,2% (Nov. 2007) source TMC

Mount Holly = 79.3% (Dec. 2007) source COGNOS

Kawasaki = 75.6% (Oct. 2007) source production office FUSO

Set ready-to-ship status:

EULA = 20 working days before

FLLC = 26 days before

FUSO = 7 working days before

OTD Reporting e.g. TMC

examples

examples examples

Measurement points: variances between on-time and missed days

OTDFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Variances for 2008:

ALL = - 4/+0 working days

2.7


OEE Direct RunThroughput

time

KPI tree

as seen on

shop floor

Actionable

levers to

improve

KPI

OTD actionable levers on shop floor

See Direct Run..See OEE..

See through-put time..

OTD

Ratio

OTDFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.7


APA – Auslieferungsprodukt Audit–customer Audit

Description: Audit forecast of how many defects the customer would find on the new vehicle

Steering goal: Focus production on final customer-related quality


APA = Σ (1s×0.01)+(3s×0.1)+(5s×0.4)+(9s×0.8)Total number of vehicles audited

Calculation method conform with CVD Quality Guideline 23


• Vehicles subjected to APA audit just before final inspection.

• Content of audit documented in APA handbook


• Sum of all APA scores• Number of vehicles audited



Shopfloor KPI:

Abbreviation: APA Applicability: TM x TE x TN x TA


APA

Employee training Quality control

Additional notes:

• Powertrain plants will report 0-ppm customer• Categorization of 1s, 3,s etc. region specific• Freightliner currently will not use the “0” scorex yes no

APAFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Unit: faults/vehicle


Absenteeism

2.8



APA – calculation model agreed at KPI project standardization conference (June 2007)

APA*

APA

(0+1+3+5+9)

Number of

audits

Index 0.01

Number of 1s

Index 0.8

Number of 9s

Index 0.4

Number of 5s

Index 0.1

Number of 3s

∑

Level 1

Level 9

Level 5

Level 3

Level 0Index 0.00

Number of 0s

• 0's measured

• 0, 1, 3, 5, 9 measured

with indices

• APA substitutes current

5's and 9's reporting

• Market defines what is

0, 1, 3, 5, 9

• Freightliner currently

will not use the “0”

score and will maintain

their current process as

they do not use a

separate Product Audit.

Key points

*Currently IPQ is reported in TG scorecardSource: Standardization Conference

APAFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Compliant with CVD Quality Guideline 23

2.8


APA measurement point is when the vehicle is ready fordelivery

Vehicle ready for delivery

Assembly processSection InspectionMB Trucks

BPA Final InspectionReworkif necessary

70% APA

Dealer

Finish

30 % APA Plant

Assembly process Off lineFTL

APA

Final InspectionQuality Inspectors End of Line Audit Rework

Finish

Assembly process7 Quality Gate CheckRework

Final Inspection

APA

Fuso

Source: Dr. J. Hoffmann – „Quality Reporting TG KPIs – Status Report“ – Feb. 9th 2007

APAFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.8


Scope and testing measures are fixed in the APA manual

APA Manual CV Delivery – Product – Audit Commercial Vehicles Edition: January 2006

APA Manual CV Delivery – Product – Audit Commercial Vehicles Edition: January 2006

Contents:

Clutch Inspect: visual inspection of the tank from the outside:

• fluid level

hydropneumatic gear change (HPS)

Inspect: visual inspection of the tank from the outside: • fluid level Cab must be tilted!

Scale:

Fluid level of the hydraulic clutch mechanism Minimum fluid level: The fluid level must lie at the upper mark (1) (max.). Tolerance: ± 3.0 mm Brake fluid, hydropneumatic gear change

Minimum fluid level The fluid level must lie at the upper mark (max.). Tolerance: ± 3.0 mm

Approx. 900 pages

Customer feedback affects the contents and measures of the APA-Manual over the APA Coreteam. Thus it is guaranteed that from current customer view is examined.

Source: APA Presentation / Dr. A. Fritz QCV / OF / 06-05-18

APAFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.8


APA

Employee participation

Absenteeism Trained members

Problem follow-up

Problem follow-up

STD work audit

Manpower planning


Clean sheet bonus

Std work audit

Training school


Accident alert

…

Quality

No 0’s No 1’s

Problem follow-up

Problem follow-up

Stop at defect


Containment


Quality alerts

Ensure quality loops

Design for quality

…



APA actionable levers

No 3’s

Problem follow-up

No 5’s

Problem follow-up

No 9’s

Problem follow-up


APAFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.8

Author: OMCD/E, January 2008 73Daimler TrucksSource: APA Presentation / Dr. A. Fritz QCV / OF / 06-05-18

APA score MBTruck calculated based on number of faults* multiplied by APA index

NQ

FEF = 15 faults/veh.

5

9

3

1

80 %

40 %

10 %

1 % 4 faults/veh. x 0.01 = 0.04 faults/veh.

5 faults/veh. x 0.1 = 0.50 faults/veh.



FEF = 15 faults*/veh., of which:

APA = 2.54 faults/veh.

FEF sub-divided in NQ- Groups

2.54 faults/veh.

0 0 % 2 faults/veh. x 0.00 = 0.00 faults/veh.

Plant

Dealer

GNQ

ForecastCustomers

APAFACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

*Faults relates to a condition that will discover and complain (if asked) at a new vehicle up to 6 weeks after delivery.

2.8


0-PPM customer

Description: Number of defect parts out of 1 million for parts delivered in selected month to customers

Steering goal: Focus production on final customer-related quality


0CU = shipped defect parts × 1,000,000Total shipped parts to all customers


• Defect measurement based on direct feedback from customer plants

• Measured for plant internal and plant externalfinal powertrain product customers


• Number of complaints from customer• Number of delivered units



Shopfloor KPI:

Abbreviation: 0CU Applicability: x TM TE TN TA


0-ppm Customer

Employee training Quality

Additional notes:

• Vehicle plants report APA to reflect customer satisfaction

• QZA audit will be maintained as internal product audit for powertrain

x yes no

0-ppm customer

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

Unit: ppm


2.8



0-PPM customer – calculation model agreed at KPI project standardization conference (June 2007)

Customer satisfaction index for aggregate and parts plants – PPM

0-PPM

Shipped defect parts

× 1,000,000

Total shipped parts to all customers

• Keep QZA, but report O-

PPM from customer

Key points

Source: Standardization conference defect parts = Nonconforming quantity

0-ppm customer

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.8


0-PPM Customer is measured by customer and reported back to aggregate plant

• 0-ppm customer complaints are based on reclamations from vehicle plants regarding aggregate units supplied to them

• 0-ppm customer should include feedback from aggregates supplied to all customers, Daimler internal and external.

• 0-ppm customer gives a direct and real indication of customer satisfaction levels based on aggregate quality

0-ppm customer

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE

0-ppm reclamations

0-ppm reclamations

0-ppm reclamations

Engine plant

Vehicle plant

Vehicle plant

Vehicle plant

2.8


0-ppm Customer

Member availability

AbsenteeismTrained members

Problem follow-up

Problem follow-up

STD work audit

Manpower planning


Clean sheet bonus

Std work audit

Training school


Accident alert

…

Quality

Defect a Defect b

Problem follow-up

Problem follow-up


Containment


Quality alerts

Re-align quality standards

Design for quality

…



0-PPM customer – actionable levers

Defect c

Problem follow-up

Defect …

Problem follow-up

Defect n

Problem follow-up

Indicates recommendation to track values at line level

0-ppm customer

FACTSHEET


MEASURE-MENT POINTS

SHOP FLOOR LEVERS

PLANT EXAMPLE 2.8


3. KPI integration intoDaimler Truck scorecards


On-Time-Delivery, Direct Run and Throughput Time KPIs shall be integrated in T-Scorecard in 2008, HPU and APA already in T-SC

Net Production Material Cost

Savings

%

Annual funding ** € mill.

HPV h/veh.

Manufacturing cost € mill.

Aftersales RoS %

CSI pts

Inverntory turnrate (new vehicles)

factor

Inventory turnrate (used vehicles)

factor

Program

spending **

Opera

tional Excellence

13

Material cost

Productivity

15

16

Inverntory

turnrate (new

vehicles)

Aftersales

performance

(internal view)Aftersales

performance

(external view)

Inventory

turnrate (used

vehicles)

14

10

11

12

9

APA (IPQ)defects/ vehicle

Fixed First Visit %

Limes Brand QualityPts. (1-

1000)

Total cost of ownership

Score

Warranty expense at 12 MIS

€/vehicle

Cost of

ownership

Warranty

performance

Superior Pro

ducts

& C

usto

mer

Experience

Quality (internal)

Quality

(external)

Customer

satisfaction,

Consumer

4

3

5

1

2

Net Production Material Cost

Savings

%

Annual funding ** € mill.

HPV h/veh.

13 Direct run %

14 Throughput-time h/veh.

Manufacturing cost € mill.

Aftersales RoS %

CSI pts

Inverntory turnrate (new vehicles)

factor

Inventory turnrate factor

Productivity

Program

spending **

Opera

tional Excellence

16

Material cost

18

19

Inverntory

turnrate (new

vehicles)

Aftersales

performance

(internal view)Aftersales

performance

(external view)

Inventory

turnrate (used

17

11

12

15

10

APA (IPQ)defects/

vehicle

Fixed First Visit %

Limes Brand QualityPts. (1-1000)

4 On-time delivery %

Total cost of ownership

Score

Warranty expense at 12 MIS

€/vehicle

Customer

satisfaction,

Consumer

perception

Cost of

ownership

Warranty

performance

Superior Pro

ducts

& C

usto

mer Experience Quality (internal)

Quality

(external)

5

3

6

1

2

Additional

KPI:

On-time delivery

Additional

KPI:

• Direct run• Throughput-

time

Standard

definition:APA

Standard

definition:HPV

New KPIs to be integrated in Focus Pillars according to Scorecard logic: only figures for vehicle OUs -TE, TN, TA- and Daimler Trucks. Total number of KPIs in T-SC is 28.

Reporting

begin

Feb 2008

new

new

new

3


Goal of policy deployment of the TOP operational KPI is to cascade objectives and achieve continuous improvement

Scorecard

To Reach the Targets

DAIMLER

MBC

MB Trucks

Coordination & Cadence

DT DFS MBV

FLC FUSO TM

W60 W575W164W154 W20W152 W34

…

…

1. HPV

2. APA

3. Direct run

4. Throughput time

5. OTD

6. Ratio

7. OEE/K-Factor

8. 0-ppm Supplier

BENEFITS

Policy

Deployment

Transparent status of corporate business objectives, understanding and

accountability at all levels of the organization, identification of roadblocks inhibiting the attainment of objectives

Regular & C

onsistent T

arget R

eviews2

5

8

Indicates the number of Top Operational KPIs to be reported at each level

3


Top operational KPIs for Truck Scorecard use existing reporting organization with clear responsibilities

TN FTLT. Marks (CPMO)

All TAplants

TRUCK Scorecard – C. Bosmann / O. Haakshorst (S/T)

EnginesA. Knuettel

AxlesM. Ried

TransI. Seitz

All TNplants

Enginesdata

EnginesDDC

P. Gamache (DDC)

Truck Score-card TA

A. Schmitz-Justen (S/T)

TMScorecardM. Ried (BCF/EPA)

Truck Score-card TE

S. Salzmann (S/TM)

TMplants

Aksaray PBS

WörthC.Hinsen

Vehiclesdata

QualityCockpitJ. Hoffmann

(TE/QM)

APA TE, TN, TA

DAIMLER Scorecard – H. Rudolph (S/P)

8 Operational KPIs reportedto plant level

5 operat.KPIs in T-SC

2 operational KPIs in D-SC

TM/TE MBBras

H. Araujo (TM/EBE)C. Dias (TE/BMQ)

Aggregatesdata

Vehiclesdata

Vehiclesdata

Aggregates

FusoUlrich. Schmid (Controlling)

TA FusoG.Noda (DCPS-Office)

Truck Score-card TN

T. Pax-Slotto (CPMO)

3

Status: January 2008


4. Reporting and KPI IT platform


4

Management systemfor top operational

KPIs

Cognos FLC

NAFTAASIA

TMC

E1

E3

E4

E1

E2

E3

E4

E5

Top -KPI

EULA

Top - K

PI

E2

CONCEPT

• KPI-data are collected separately using existing interfaces or file transfer for NAFTA (Cognos FLC) andEULA (TMC).

• EULA-data are transferred via interface to Cognos FL

• Top Management see all TOP Operational KPIs within CognosFL using existing Cognosreport templates

Project team proposal: Top level reporting operational KPIs in FLC COGNOS system

TEC Decision:COGNOS as mandatory system if any OU decides to implement new IT tool for KPI

Most practical IT solution for Truck-wide KPI platform incorporates hybrid solution with COGNOS frontend


zem@web

Excel AccessSAP Automotive

Cognos FLCTMC

E1

E3

E4

E1

E2

E3

E4

E5

Top -KPI

Top Management

Top - K

PI

E2

data exchange

once per month

Origin data sources

+ SISAM WEB, SAP Log, Q-SYS, MLS,…

file transfer of TOP KPI data to TMC for EULA and ASIA

file transfer of TOP KPI data to Cognosfor NAFTA

files have to be generated manually in Step 1 using different data sources

Data sources for TOP operational KPIs are linked back in manifold systems

4

85Daimler Trucks

Timeline:

1. up to 16th every month ?: Delivery of data files to TMC

(FileUpload, including data transfer Cognos -> TMC for level Trucks NAFTA!)

2. 17th every month ?: Calculate roll up in TMC

3. 18th every month ?: Transfer data file TMC -> Cognos

Definitions:

1. 19th to 21rd of every month: Write comments or tasks in Cognos by managers or reporting persons

2. 22th every month: Official reporting in Cognos for current month

Proposal for Cycle and Rules of Monthly Reporting (Release 2)

4


Rules:

1. Every file includes all data from January to reporting month and overwrites the old data of files before(changes are only allowed inside of the current reporting year)

2. All delivered data are visible in Cognos

3. Reporting persons are responsible for data content and delivery in time

4. Data files are delivered to Cognos without checkup of completeness

5. The delivery of data files to TMC (Point 1 of timeline) is a fixed due date (hour and date: 16th of every month,

MEZ 24.00). At this time all available data are processed as provided (a file which does not correspond to thedefined rules will be completely rejected)

6. It is necessary to deliver both targets and actuals for all KPI; otherwise the calculated targets would bemisleading. If targets are not available to the reporting responsible, the targets have to be deliveredcorresponding to the actuals

Proposal for Cycle and Rules of Monthly Reporting (Release 2)

4


Levels of Reporting TOP KPI

1 2 3 4 HPUOEE /

K-

Factor

RAT OTD TPT DIR 0SU

APA

/

0CU

Truck

BSC Node

ass

emb

l /

pow

ertr.

Data

TMCLevel

Responsible Person Top

Management (B -> E2)EOD

Responsible Person for

Reporting

Daimler Trucks 1 n/a n/a 1 1 1 n/a 1 (APA 23 K0001 A BS Andreas Renschler T

Trucks Europe / Latin America (Mercedes-Benz)1 ? ? 1 1 1 ? 1 23 K0002 A OU Hubertus Troska TE Christian Hinsen

MB Trucks Brazil 1 1 1 1 1 1 1 4 n/a K0003 A y PL Dr. Gero Herrmann TE/B Charles Dias

MB Trucks Wörth & Turkey 1 1 1 1 1 1 1 1 n/a K0004 A PL Martin Daum TE/O Christian Hinsen

MB Trucks Wörth 1 1 1 1 1 1 1 3 n/a K0005 A y PL Ernst Wünstel TE/OP Christian Hinsen

MB Special Vehicles Wörth 1 1 1 1 1 1 1 3 n/a K0006 A y PL Walter Eisele TE/OV Christian Hinsen

MB Trucks Turkey 1 1 1 1 1 1 1 3 n/a K0007 A y PL Hans-Ulrich Maik TE/OA Christian Hinsen

Trucks Asia (Fuso) 1 ? ? 1 1 1 ? 1 23 K0008 A OU Harald Boelstler TA Genta Noda

Fuso Trucks & Buses 1 1 1 1 1 1 1 1 n/a K0009 A PL Yoshitaka Taniyama TA/O Genta Noda

FUSO Trucks & Buses Domestic 1 1 1 1 1 1 1 1 n/a K0010 A PL Masashi Kogame TA/OA Genta Noda

Trucks Kawasaki ? 1 1 1 1 1 1 3 ? n/a K0011 A y PL Genta Noda

Trucks Nagoya ? 1 1 1 1 1 1 ? n/a K0012 A y PL Genta Noda

Buses Toyama ? 1 1 1 1 1 1 3 ? n/a K0015 A y PL Genta Noda

Light Trucks Tramagal (Portugal) ? 1 1 1 1 1 1 ? n/a K0016 A y PL Genta Noda

Trucks Phantumthani (Thailand) ? 1 1 1 1 1 1 ? n/a K0017 A y PL Genta Noda

Trucks NAFTA (Freightliner, Sterling, Western Star)1 ? ? 1 1 1 ? 1 23 K0018 A OU Chris Patterson TN Tom Marks

Production Trucks NAFTA 1 1 1 1 1 1 1 1 n/a K0019 A SU Roger Nielsen TN/O Tom Marks

Production Trucks NAFTA & Portland 1 1 1 1 1 1 1 8 n/a K0020 A n PL Alan Mayne TN/O Rob Hopf

Trucks Cleveland ? 1 1 1 1 1 1 3 ? n/a K0021 A n PL John Pacillas TN/OC Mike Puncochar

Trucks Gaffney ? 1 1 1 1 1 1 1 n/a K0022 A n PL Robert Harbin TN/OF Bernie McNamee

Parts Gastonia ? 1 1 1 1 1 1 n/a n/a K0023 A n PL Erik Johnson (E3) TN/OUG David Buswell

Trucks Mt Holly ? 1 1 1 1 1 1 2 ? n/a K0024 A n PL Mike McCurry TN/OHA Ted Ingold

Trucks Portland ? 1 1 1 1 1 1 2 ? n/a K0025 A n PL Paul Erdy (E3) TN/O Tom Gertz

Trucks Santiago (Mexico) ? 1 1 1 1 1 1 5 ? n/a K0026 A n PL Knut Anderson TN/OM Lisy Rubio

Trucks St Thomas ? 1 1 1 1 1 1 2 ? n/a K0027 A n PL Robert Correll Jr. TN/OT David Kuchma

Thomas Built Buses (TBB) ? 1 1 1 1 1 1 1 n/a K0028 A n PL John O`Leary TN/OB Jenny Curry

Draft: Reporting Structure TOP KPI 1/2

4


Levels of Reporting TOP KPI

1 2 3 4 HPUOEE /

K-

Factor

RAT OTD TPT DIR 0SU

APA

/

0CU

Truck

BSC Node

ass

emb

l /

pow

ertr.

Data

TMCLevel

Responsible Person Top

Management (B -> E2)EOD

Responsible Person for

Reporting

n/a Truck Powertrain Production & Manufacturing Engineeringn/a 1 1 1 n/a 1 1 1 n/a K0029 P OU Dr. Michael Dostal TM Matthias Ried

n/a Engines Trucks 1+3 1 1 1 1 1 1 1 n/a K0030 P SU Hermann Doppler TM/E Angelika Knüttel

n/a Engines Mannheim & FUSO 1+3 1 1 1 1 1 1 1 n/a K0031 P PL Dr. Peter Vaughan Schmidt TM/EM Thorsten Speelmann

n/a Engines Mannheim 1+3 1 1 1 1 1 1 1 n/a K0032 P y PL Thorsten Speelmann

n/a Engines FUSO 1+3 1 1 1 1 1 1 1 n/a K0033 P y PL Genta Noda

n/a Engines MBBras 1+3 1 1 1 1 1 1 1 n/a K0034 P y PL Bart Laton TM/EB Jessica Passos

n/a Engines DDC 1+3 1 1 1 1 1 1 1 n/a K0035 P y PL Dr. Henning Oeltjenbruns TM/ER Patrick A. Gamache

n/a Foundries Mannheim and South Africa 1 1 1 1 1 1 1 1 n/a K0036 P PL Ralph Wegener TM/EF Thorsten Speelmann

n/a Foundry Mannheim 1 1 1 1 1 1 1 1 n/a K0037 P y PL Thorsten Speelmann

n/a Atlantis Foundries (South Africa) n/a 1 1 1 1 1 1 1 n/a K0038 P y PL Thorsten Speelmann ?

n/a Axles / Transmissions Trucks & Vans 2+7 1 1 1 1 1 1 1 n/a K0039 P SU Dr. Holger Steindorf TM/T Matthias Ried

n/a Transmissions worldwide 1+3 1 1 1 1 1 1 1 n/a K0040 P PL Hans-Joachim Vogt TM/TT Reinhard Jung

n/a Transmissions Gaggenau 1+3 1 1 1 1 1 1 1 n/a K0041 P y PL Reinhard Jung

n/a Transmissions MBBras 1 1 1 1 1 1 1 1 n/a K0042 P y PL Jessica Passos

n/a Transmissions FUSO 3 ? 1 1 1 1 1 1 1 n/a K0043 P y PL Genta Noda

n/a Axles FUSO 3 ? 1 1 1 1 1 1 1 n/a K0044 P y PL Genta Noda

n/a Product Units Gaggenau n/a 1 1 1 1 1 1 1 n/a K0045 P y PL Andreas Moch TM/TP Reinhard Jung ?

n/a Axles Trucks / Vans 1+3 1 1 1 1 1 1 1 n/a K0046 P PL Ludwig Pauss TM/TA Matthias Ried

n/a Axles Kassel 1+4 1 1 1 1 1 1 1 n/a K0047 P y PL Matthias Ried

n/a Axles Gaggenau 1 1 1 1 1 1 1 1 n/a K0048 P y PL Daniel Thiess

n/a Axles MBBras 1+3 1 1 1 1 1 1 1 n/a K0049 P y PL Jessica Passos

n/a Axles AAC n/a 1 1 1 1 1 1 1 n/a K0050 P y PL Soenke Scheffer (E3) ?

n/a Trailer Axle Systems 1 1 1 1 1 1 1 1 n/a K0051 P y PLDr. Holger Steindorf /

Norbert Rehbein (E3)TM/TAS Matthias Ried

Legend:

Data input (Arbitrary node types, f.e. Cost centers, EOD Nodes...)

Data export Cognos (NAFTA) -> TMC

Reporting node (always EOD)

Reporting node

not consolidated

BS: Business Segment

OU: Operating Unit

SU: Sub Unit

PL: Plant

HPU: number of partitions

Cluster: As: Assembly; Ax: Axles; E: Engines; T: Transmissions; O: Others

4


Security Structure Release 3 (1)

Renschler (1)

Boelstler (8)Dr. Dostal

(29)Patterson

(18)Troska (2)

Dr. Herrmann (3)

Linsmeier

BastianMoreira

TEC-Members

Daum (4)

Wünstel (5) Maik (7)Eisele (6) Burkart

Taniyama (9)

Kogame (10)

Kawasaki (11)

Nagoya (12)

Toyama (15)

Tramagal -Portugal (16)

Phantumthani –

Thailand (17)

Johnson Nielsen (19)

Mayne (20)

Cleveland (21)

Gaffney (22)

Gastonia (23)

Mt Holly (24)

Portland (25)

Santiago (26)

St Thomas (27)

TBB (28)

next page

1/2

1

2 34

5

67 8

Rules

1: Mr. Renschler see all nodes

2, 3, 4, TEC- members see nodes 1, 2, 8, 18, 295, 11: and detail- nodes of his own Operating Unit

6: All Top- Managers of TE see nodes 2 – 7

7: All Top- Managers of TA see nodes 8 –17

8: All Top- Managers of TN see nodes 18–28

9: All Top- Managers of TM/E see nodes 29–38

10: All Top- Managers of TM/T see nodes 29 and 39-51

4


Security Structure Release 3 (2)

Renschler (1)

Dr. Dostal (29)

TEC-Members

Doppler (30)Dr. Steindorf

(39)

Dr. Schmidt (31)

LatonMBBras (34)

Wegener Foundries (36)

OeltjenbrunsDDC (35)

Vogt (40)

Engines MA (32)

EnginesFUSO (33)

Foundry MA (37)

Atlantis

Foundries (38)

Moch (45) Pauss (46) Rehbein (51)

Transmissions

MBBras (42)

Axles FUSO (44)

Transmissions

Gaggenau (41)

Transmissions

FUSO (43)

Axles Gaggenau

(48)

Axles AAC (50)

Axles Kassel (47)

Axles MBBras(49)

Dr. Kirchmann

WeibergBuchner

2/2

Lemmermeier Thiel

9

10

11

5

4


* Reporting by monthly values; calculation of KPI based on year to date (YTD; sum of counter and denominator from January until current month)

** Consolidation of these KPIs to TM level does not yield meaningful information or values that can be tracked objectively. Individual scoring for engines, axles and transmissions shall in the TGP scorecard.

OU( Σ PPM defects / Σ supplier units received ) × 1million7. 0-ppm Supplier (0SU)

Daimler Trucks /

TM: Sub-unit**

Σ (throughput time per plant x units produced by plant) /

Σ units produced all plants

6. Throughput Time

(hours) (TPT)

Daimler Trucks / TM[1 - ( Σ offline defect units / Σ units assembled) ] × 1005. Direct Run (%)(DIR)

Daimler Trucks / TM[1 - ( Σ late deliveries / Σ units delivered) ] × 1003. On Time Delivery (%)

(OTD)

Daimler Trucks (APA)

TM (0CU)

ΣΣΣΣ (APA per model ×××× units produced per model) / ΣΣΣΣ units produced

(Σ PPM complaints / Σ delivered units ) × 1million (0CU)

1. APA (APA)

2. O-ppm Customer(0CU)

OUΣ Ratio improvement hours / Σ standard hours × based on actual

production program in month concluded10. Ratio (%) (RAT)

OUΣ OEE indices / Σ assembly lines (OEE)

Σ K-Factor indices / Σ bottleneck machines (K-Factor)

8. OEE (OEE)

9. K-Factor (KFC)

Daimler Trucks /

TM: Sub-unit**

Σ ( attendance time per model × units produced per model) /

Σ units produced all models4. HPU (hours) (HPU)

KPI (Abbreviation)Highest sensible

aggregation levelConsolidation method (targets and actuals)

Methods for KPI consolidation and aggregation levels TM (Powertrain) is not consolidated in Truck KPI !!!

4


TMC-Datenbank

Primäre Datenquellen (EULA und ASIA)

Dateneigner (Truck EULA, TRUCK Asia, Powertrain)

Cognos-Visualisierung

Cognos-Datenbank

Standard-DatenfomatTMC�Cognos (MQ)(to be defined)

Standard-DatenfomatDatenlieferant->TMC (FileUpload)(to be defined - csv-Datei)

BSC TGP(temporär)H. Ried

Extract Powertrain

Export aus TMCin csv-Datei fürweitere Verwendung

Mittelfristig alternative Option für primäre Dateneigner: Manuelle Erfassung über TMC(nur bei kleinem Datenvolumen praktisch relevant, offen: Security)

Data flow between TMC and Cognos

4


Example csv-file Mannheim for input in TMC

Ro

w_

Nr

TM

C_

Nr

KP

I_R

ow

Node_I

DP_ID Value_ID KPI Node_Text

Product_

TextValue_Description Year

Annual_

ValueM_01 M_02 M_03 M_04 M_05 M_06

1 1 1 K0032 PR01 ACTUAL_A HPU Engines Mannheim Light Duty actual attendance time 2007 50708 49840 57830 52148 54194 534922 1 2 K0032 PR01 ACTUAL_B HPU Engines Mannheim Light Duty actual number of produced units 2007 17560 17740 20772 18293 19031 190883 1 3 K0032 PR01 TARGET_A HPU Engines Mannheim Light Duty target attendance time 2007 621048 51754 51754 51754 51754 51754 517544 1 4 K0032 PR01 TARGET_B HPU Engines Mannheim Light Duty target number of produced units 2007 207016 17251 17251 17251 17251 17251 172515 1 5 K0032 PR02 ACTUAL_A HPU Engines Mannheim Medium Duty actual attendance time 2007 89581 84254 104572 92343 95293 951866 1 6 K0032 PR02 ACTUAL_B HPU Engines Mannheim Medium Duty actual number of produced units 2007 5846 5957 8461 7973 7963 76497 1 7 K0032 PR02 TARGET_A HPU Engines Mannheim Medium Duty target attendance time 2007 1015162 84597 84597 84597 84597 84597 845978 1 8 K0032 PR02 TARGET_B HPU Engines Mannheim Medium Duty target number of produced units 2007 86766 7231 7231 7231 7231 7231 72319 1 9 K0032 PR03 ACTUAL_A HPU Engines Mannheim Heavy Duty actual attendance time 2007 138191 132645 162086 138077 150425 152516

10 1 10 K0032 PR03 ACTUAL_B HPU Engines Mannheim Heavy Duty actual number of produced units 2007 8269 7964 9463 7740 8498 881811 1 11 K0032 PR03 TARGET_A HPU Engines Mannheim Heavy Duty target attendance time 2007 1936545 161379 161379 161379 161379 161379 16137912 1 12 K0032 PR03 TARGET_B HPU Engines Mannheim Heavy Duty target number of produced units 2007 105247 8771 8771 8771 8771 8771 877113 3 1 K0032 G ACTUAL_A KFC Engines Mannheim Global actual sum of k-indices of bottleneck machines 2007 13,081 13,104 13,100 13,150 12,980 12,95014 3 2 K0032 G ACTUAL_B KFC Engines Mannheim Global actual number of bottleneck machines 2007 16 16 16 16 16 1615 3 3 K0032 G TARGET_A KFC Engines Mannheim Global target sum of k-indices of bottleneck machines 2007 13,600 13,600 13,600 13,600 13,600 13,600 13,60016 3 4 K0032 G TARGET_B KFC Engines Mannheim Global target number of bottleneck machines 2007 16 16 16 16 16 16 1617 4 1 K0032 G ACTUAL_A RAT Engines Mannheim Global actual ratio improvement hours 2007 12157 7724 9445 7524 4060 1590318 4 2 K0032 G ACTUAL_B RAT Engines Mannheim Global actual standard hours 2007 127081 127081 127081 127081 127081 12708119 4 3 K0032 G TARGET_A RAT Engines Mannheim Global target ratio improvement hours 2007 114373 9531 9531 9531 9531 9531 953120 4 4 K0032 G TARGET_B RAT Engines Mannheim Global target standard hours 2007 1524973 127081 127081 127081 127081 127081 12708121 5 1 K0032 G ACTUAL_A OTD Engines Mannheim Global actual number of complained products 2007 50 66 52,5 74 112,5 9322 5 2 K0032 G ACTUAL_B OTD Engines Mannheim Global actual number of delivered products 2007 8108 7256 8688 7562 8257 830023 5 3 K0032 G TARGET_A OTD Engines Mannheim Global target number of complained products 2007 888 74 74 74 74 74 7424 5 4 K0032 G TARGET_B OTD Engines Mannheim Global target number of delivered products 2007 90744 7562 7562 7562 7562 7562 756225 6 1 K0032 G ACTUAL_A TPT Engines Mannheim Global actual sum of throughput times 2007 54,028 56,095 56,843 62,588 58,177 57,11726 6 2 K0032 G ACTUAL_B TPT Engines Mannheim Global actual number of assembled units 2007 4 4 4 4 4 427 6 3 K0032 G TARGET_A TPT Engines Mannheim Global target sum of throughput times 2007 54,917 54,917 54,917 54,917 54,917 54,917 54,91728 6 4 K0032 G TARGET_B TPT Engines Mannheim Global target number of assembled units 2007 4 4 4 4 4 4 429 7 1 K0032 G ACTUAL_A DIR Engines Mannheim Global actual number of units with offline defects 2007 3334 3334 3334 2434 4061 353230 7 2 K0032 G ACTUAL_B DIR Engines Mannheim Global actual number of produced units 2007 17967 17967 17967 16028 35688 3520331 7 3 K0032 G TARGET_A DIR Engines Mannheim Global target number of units with offline defects 2007 40002 3334 3334 3334 3334 3334 333432 7 4 K0032 G TARGET_B DIR Engines Mannheim Global target number of produced units 2007 337302 28109 28109 28109 28109 28109 2810933 9 1 K0032 G ACTUAL_A 0CU Engines Mannheim Global actual number of defect products 2007 89 107 114 76 99 7734 9 2 K0032 G ACTUAL_B 0CU Engines Mannheim Global actual number of delivered products 2007 26892 26708 33189 28050 30152 3076735 9 3 K0032 G TARGET_A 0CU Engines Mannheim Global target number of defect products 2007 1441 120 120 120 120 120 12036 9 4 K0032 G TARGET_B 0CU Engines Mannheim Global target number of delivered products 2007 413911 34493 34493 34493 34493 34493 3449337 10 1 K0032 G ACTUAL_A 0SU Engines Mannheim Global actual number of defect parts 2007 6147 33151 3447 20190 33000 1940938 10 2 K0032 G ACTUAL_B 0SU Engines Mannheim Global actual number of delivered products 2007 28896573 27603125 32247519 29484697 29695000 2892600039 10 3 K0032 G TARGET_A 0SU Engines Mannheim Global target number of defect parts 2007 165000 13750 13750 13750 13750 13750 13750

40 10 4 K0032 G TARGET_B 0SU Engines Mannheim Global target number of delivered products 2007 300000000 25000000 25000000 25000000 25000000 25000000 25000000

4


5. Performance dialogueand best-practice

exchange


The Performance Dialogue generates value for line-, plant-, SU- and OU-managers through good practice transfer

� Through the Performance Dialogue process managers have the opportunity to find cross regional and BU-independent good practices to improve their performance on basis of the standardized KPIs

� The Performance Dialogue depends on the lean principles

� Share openly and borrow proudly

� Go and see

4 5

7 8

3

6

9

21Take the long view

– Invest in tomorrow’s

profits today

Keep it simpleRespect, support and

challenge your

partners and suppliers

Choose the process

focus

Learn quickly from

triumphs and from

tragedies

Share openly

and borrow proudly

Imagine you were

your customerGo and See

Only empowered people

produce powerful

performance

9 Lean Principles

5


Standardized KPIs enables efficient peer to peer exchange and good practice sharing

Peer to Peer ReviewTarget Agreement

•Discuss issues and root causes openly and honestly with peers in other OUs

•Learning and exchange oriented

•No target setting, no league table

•Set individual targets and

challenges to each plant

•Align with other KPI

processes (e.g. financials,

customer requirements

etc.)

Sharing

Target agreement

Operating

unit

Plant

Base of standardized KPIs

DT

Operatingunit

Plant


DT

Shop floor

PERFORMANCE DIALOGUE

Performance review

• Top-down Steering

• Target deviation discussion

•Clear definition of roles and

scorecard responsibilities

Steering

Operatingunit

Plant


DT

5


Structured process for identification facilitates matching and transfer of good practices

MatchingAnalysis plant DecisionAnalysis SU/OU

Good Practices

Line, Center, Plant

Analysis of KPIs on Level line, center, plant

OpportunityFields

Good Practices Line, Center, Plant

Transferable Good

PracticesOpportunity

Fields

Transferable Good

PracticesOpportunity

Fields

Matching list

Matching list Priorization

Transfer of good practice and evaluation of transfer

Input

Processpart

Output

3-month cycle

KPI coordinatorplant

Responsiblefor Output

KPI coordinator SU/OU/region, OMCD



5


To facilitate the Peer to Peer review and the exchange of good practices a suitable platform is required

On-going KPI analysis

and identification of above average KPI improvement and performance

Identification of good practices and selection

Selection of a appropriate

partner for a good practice transfer regarding KPI performance

Good practice experience

exchange and implementation in target plants

Follow-up tracking of KPI

improvement due to good practice share - ensure sustainability

KPI-Coordinator in line/center/

plant

Plant Manager,good practice

Expert

SU scorecard manager

Selection of possible good practice processes

Analysis of good practice and selection of opportunity

Implementation and tracking of good practices at target plants

Presentation of good practices proposals with savings potential estimation for production leaders

e.g. MLC

Decision/ Presentation

KPI-responsibles,

OMCD

KPI-responsibles,

OMCD

5


Good practice transfer creates a ‘win-win’ situation for all involved parties

• Confirmation of good practice process performance

• Possibility of further improvement of this good practice

Good Practice Owner

• Benefits through improvement in processes

• Achievement of savings

• Better performance situation with positive effects on KPIs

Opportunity Plant

• Operational Excellence

• Standardized processes adjusted to local circumstances

• Common understanding of processes

Daimler Trucks

5


6. Appendix


Summary of important decision milestones for Top Operational KPI project

• March 2007 Assignment from TEC to standardize top operational KPIs for all OUs

• June 2007 KPI standardization conference with participants for all OUs#

• July 2007 Approval of KPI definitions by MLC (meetings Brazil, Portland)

• October 2007 Preliminary approval of KPI definitions by TEC(some details regarding HPU outstanding)

• December 2007 MLC finalise HPU definition for all OUs

• January 2008 Approval by PEC to integrate 5 top operational KPIs into T-scorecard

Roadmap for Top Operational KPI project – please see next slide.

6


TOP operational KPI Roadmap supports the Lean Transformation of DAIMLER Trucks

Performance-

driven CI

dialogue DTs

Today

Approval standard op. KPIs / Integration in SCs TEC 15.01.08

Global implementation of TOP op. KPIs

Alignment of KPIs within DT Scorecards(Portfolio-Analysis)

Continuous training of Top Op.KPIs from DTs to GEMBA

Standardization TOP op. KPIs in indirect areas(e.g. develop. by eHPV)

Provide IT-system by Cognos/TMC

Final Alignment in global MLC,Tokyo 03.12.2007

Start of Pilot Implementation in plants (TM 07/07)

Discussion TOP Operational KPIs

in plants, lighthouses, OUs, exe. councils

TOP Operational KPI Kick-off and project assignment (15.05.07)


Top Operational KPIs - contact persons at OMCD/E

Contact Telephone Email

• Thomas Jung (Project Lead) +49 711 17 54574 [email protected]

• Peter Hoffmann +49 711 17 32302 [email protected]

• Ralf Hieber +49 711 17 55976 [email protected]

• Michael Lenz +49 711 17 56336 [email protected]

• Wolfgang Dischler +49 7271 71 5407 [email protected]

• Wolfgang Danner +49 711 17 38023 [email protected]

• Alex Corcoran +49 711 17 38024 [email protected]

6

KPI

Documents

Transcript of KPI