Post on 04-Jan-2016
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
Author: OMCD/E, January 2008 2Daimler Trucks
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
Author: OMCD/E, January 2008 3Daimler Trucks
1. Top Operational KPI project team and region
representatives
Author: OMCD/E, January 2008 4Daimler Trucks
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
Author: OMCD/E, January 2008 5Daimler Trucks
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
Author: OMCD/E, January 2008 6Daimler Trucks
2. Top Operational KPIssteering goals, calculation,
measurement and examples
Author: OMCD/E, January 2008 7Daimler Trucks
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
Author: OMCD/E, January 2008 8Daimler Trucks
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, ralf.hieber@daimler.com
Author: OMCD/E, January 2008 9Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.1
Author: OMCD/E, January 2008 10Daimler Trucks
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
•Assembly and Test
TRANSMISSION
•Carriers & Cases
•Converters & Stampings
•Clutches & Gears
•Shafts
•Valve Body
•Assembly and Test
Source: Harbour Consulting
HPUFACTSHEET
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.1
Author: OMCD/E, January 2008 11Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.1
Author: OMCD/E, January 2008 12Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.1
Author: OMCD/E, January 2008 13Daimler Trucks
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
Level 1 calculation model:
TPT = final product release time –earliest time at which production number stamped to frame or cab
Implementation / Measurement points:
• Final product release stamp• Earliest time of production number stamping to vehicle frame / cab for Truck plants
• Final assembly begin for powertrain
Base data required for KPI aggregation:
• Sum of throughput times• Number of assembled units
Primary shopfloor levers:
Hierarchy relevance*:
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
DEFINITIONCALCULATION
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
* Implies possible applicability to scorecard
Author: OMCD/E, January 2008 14Daimler Trucks
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
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 15Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.2
Author: OMCD/E, January 2008 16Daimler Trucks
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
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 17Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.2
Author: OMCD/E, January 2008 18Daimler Trucks
Throughput time example – São Bernardo do Campo
Throughput Time
FACTSHEET
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 19Daimler Trucks
Implementation of throughput time in São Bernardo do Campo
Throughput Time
FACTSHEET
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 20Daimler Trucks
Throughput Time
FACTSHEET
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 21Daimler Trucks
Throughput Time
FACTSHEET
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 22Daimler Trucks
Throughput time example for Kawasaki Plant
Details
Representation: Bar chart
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.2
Author: OMCD/E, January 2008 23Daimler Trucks
Painting Trim
Througput time for the Kawasaki plant
DIRECT RUNFACTSHEET
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 24Daimler Trucks
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
Level 1 calculation model:
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
Implementation / Measurement points:
• Measured at discharge points in final assembly lines. For powertrain multiple discharge points, for Trucks single discharge point
• No multiple counts
Base data required for KPI aggregation:
•Number of produced units• Number of direct run violations
Primary shopfloor levers:
Hierarchy relevance*:
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE
Tracking of KPI on shopfloor boards recommended
2.3
* Implies possible applicability to scorecard
Author: OMCD/E, January 2008 25Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.3
Author: OMCD/E, January 2008 26Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.3
Author: OMCD/E, January 2008 27Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.3
Author: OMCD/E, January 2008 28Daimler Trucks
Direct run example Wörth plant
Details
Representation: Bar chart
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.3
Author: OMCD/E, January 2008 29Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.3
Author: OMCD/E, January 2008 30Daimler Trucks
Details
Representation: Bar chart
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
Focus: Improvement of process and product quality
Process goal: Reduction of rework and offline complementation
Legend:* Period = day, month or year
DIRECT RUNFACTSHEET
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE
Direct run plant example – São Bernardo do Campo plant
2.3
Author: OMCD/E, January 2008 31Daimler Trucks
São Bernardo do Campo implementation of direct run
DIRECT RUNFACTSHEET
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 32Daimler Trucks
Direct run – São Bernardo do Campo IT-system CGEM
DIRECT RUNFACTSHEET
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 33Daimler Trucks
DIRECT RUNFACTSHEET
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 34Daimler Trucks
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
Level 1 calculation model:
KFC = good parts × planned cycle timeplanned production time
* Planned production time based on planned shift hours includingbreaks, TPM and group meeting times
Implementation / Measurement points:
• Measured for machining lines only• Line K-Factor is based on bottleneck machine• Plant K-Factor calculated by average K-Factor of bottleneck machines
Base data required for KPI aggregation:
• Number of bottleneck machines• Sum of K-Factor values for bottleneck machines
Primary shopfloor levers:
Hierarchy relevance*:
Shopfloor KPI:
Abbreviation: KFC Applicability: x TM TE TN TA
x E1 x E2 x E3 x E4 x E5
K-Factor
Equipment uptime Workrate Quality
Additional notes:
• Not applicable in truck/vehicle plants
x yes no
K-FACTORFACTSHEET
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE
Unit: none
Tracking of KPI on shopfloor boards recommended
2.4
* Implies possible applicability to scorecard
Author: OMCD/E, January 2008 35Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.4
Author: OMCD/E, January 2008 36Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.4
Author: OMCD/E, January 2008 37Daimler Trucks
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
Problem solving training
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
Indicates recommendation to track values at line/station level
OEEFACTSHEET
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE
KAPITEL:
2.4
Author: OMCD/E, January 2008 38Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.4
Author: OMCD/E, January 2008 39Daimler Trucks
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
Level 1 calculation model:
OEE = good parts × planned cycle timeplanned production time*
* Planned production time based on planned shift hours excludingbreaks, TPM and group meeting times
Implementation / Measurement points:
• Measured for assembly lines only• Measure point is at end-of-assembly• If multiple lines, aggregate by weighted average
Base data required for KPI aggregation:
• Line / plant OEE values• Line / plant production volumes
Primary shopfloor levers:
Hierarchy relevance*:
Shopfloor KPI:
Abbreviation: OEE Applicability: TM x TE x TN x TA
x E1 x E2 x E3 x E4 x E5
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE
Unit: %
Tracking of KPI on shopfloor boards recommended
2.4
* Implies possible applicability to scorecard
Author: OMCD/E, January 2008 40Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE
KAPITEL:
2.4
Author: OMCD/E, January 2008 41Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE
KAPITEL:
2.4
Author: OMCD/E, January 2008 42Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE
KAPITEL:
2.4
Author: OMCD/E, January 2008 43Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE
KAPITEL:
2.4
Author: OMCD/E, January 2008 44Daimler Trucks
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
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
Problem solving training
Containment
Std. work improvement
Quality alerts
Random checks
Design for quality
…
KPI tree as seen on shop floor
Actionable levers to improve KPI
OEE actionable levers on shop floor
Indicates recommendation to track values at line/station level
OEEFACTSHEET
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE
KAPITEL:
2.4
Author: OMCD/E, January 2008 45Daimler Trucks
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
Level 1 calculation model:
RAT = sum of standard hours saved to datetime allocation based on reference standard hours
for actual production program to date
Implementation / Measurement points:
• Standard hours documented in production plans• Improvements approved by industrial engineering
Base data required for KPI aggregation:
• Confirmed standard hours saved to date• Time allocation for actual production program
based on reference standard hours from 31st of December of previous year
Primary shopfloor levers:
Hierarchy relevance*:
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE
CI* continuous improvement
2.5
Equipment upgrades
Tracking of KPI on shopfloor boards recommended
* Implies possible applicability to scorecard
Author: OMCD/E, January 2008 46Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE
Note: Ratio evaluation in scorecards on the basis of year-to-date performance.
2.5
Author: OMCD/E, January 2008 47Daimler Trucks
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
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 48Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.5
Author: OMCD/E, January 2008 49Daimler Trucks
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
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 50Daimler Trucks
Freightliner example for Ratio calculation
Details
Representation: Bar chart
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
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 51Daimler Trucks
DIRECT RUNFACTSHEET
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 52Daimler Trucks
DIRECT RUNFACTSHEET
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 53Daimler Trucks
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
Level 1 calculation model:
0SU = # defect parts from supplier × 1,000,000Total number of parts received
Calculation method conform with CVD Quality Guideline 21
Implementation / Measurement points:
• 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
Base data required for KPI aggregation:
• Number of non-conforming supplier parts• Total number of supplier parts received
Primary shopfloor levers:
Hierarchy relevance*:
Shopfloor KPI:
Abbreviation: 0SU Applicability: x TM x TE x TN x TA
x E1 x E2 x E3 x E4 E5
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE
Unit: ppm
Tracking of KPI on shopfloor boards recommended
2.6
* Implies possible applicability to scorecard
Author: OMCD/E, January 2008 54Daimler Trucks
0-PPM supplier – calculation model agreed at KPI project standardization conference (June 2007)
0-ppm supplier
FACTSHEET
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 55Daimler Trucks
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
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 56Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.6
Author: OMCD/E, January 2008 57Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.6
Author: OMCD/E, January 2008 58Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.6
Author: OMCD/E, January 2008 59Daimler Trucks
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
Flexible manpower system
Clean sheet bonus
Std work audit
Training school
Re-balance work content
Accident alert
…
Stop at detect
Solve quality problems
Quality task force
Problem solving training
Design for quality
Supplier development
Change supplier
…
KPI tree as seen on shop floor
Actionable levers to improve KPI
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
Indicates recommendation to track values at line/station level
0-ppm supplier
FACTSHEET
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.6
Author: OMCD/E, January 2008 60Daimler Trucks
Definition
Representation: Bar chart
Calculation method: Defect parts x 1,000,000PPM Supplier = ------------------------------------------------
Total received parts
Data source: SIGEQUALI System (IT system developed by MBBras)
Focus: Improvement of process and product quality
Process goal: Reduction of defect parts received from suppliers
PPM SupplierFACTSHEET
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE
0-ppm supplier plant example – São Bernardo do Campo
2.6
Author: OMCD/E, January 2008 61Daimler Trucks
São Bernardo do Campo – measurement for 0-ppm supplier through receiving inspection and ongoing analysis
PPM SupplierFACTSHEET
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 62Daimler Trucks
PPM SupplierFACTSHEET
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 63Daimler Trucks
PPM SupplierFACTSHEET
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 64Daimler Trucks
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
Level 1 calculation model:
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
Implementation / Measurement points:
• 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
Base data required for KPI aggregation:
•Number of late deliveries•Total number of deliveries
Primary shopfloor levers:
Hierarchy relevance*:
Shopfloor KPI:
Abbreviation: OTD Applicability: x TM x TE x TN x TA
x E1 x E2 x E3 E4 E5
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE
Tracking of KPI on shopfloor boards recommended
Throughput time
2.7
* Implies possible applicability to scorecard
Author: OMCD/E, January 2008 65Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.7
Author: OMCD/E, January 2008 66Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE
Variances for 2008:
ALL = - 4/+0 working days
2.7
Author: OMCD/E, January 2008 67Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.7
Author: OMCD/E, January 2008 68Daimler Trucks
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
Level 1 calculation model:
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
Implementation / Measurement points:
• Vehicles subjected to APA audit just before final inspection.
• Content of audit documented in APA handbook
Base data required for KPI aggregation:
• Sum of all APA scores• Number of vehicles audited
Primary shopfloor levers:
Hierarchy relevance*:
Shopfloor KPI:
Abbreviation: APA Applicability: TM x TE x TN x TA
x E1 x E2 x E3 E4 E5
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE
Unit: faults/vehicle
Tracking of KPI on shopfloor boards recommended
Absenteeism
2.8
* Implies possible applicability to scorecard
Author: OMCD/E, January 2008 69Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE
Compliant with CVD Quality Guideline 23
2.8
Author: OMCD/E, January 2008 70Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.8
Author: OMCD/E, January 2008 71Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.8
Author: OMCD/E, January 2008 72Daimler Trucks
APA
Employee participation
Absenteeism Trained members
Problem follow-up
Problem follow-up
STD work audit
Manpower planning
Flexible manpower system
Clean sheet bonus
Std work audit
Training school
Re-balance work content
Accident alert
…
Quality
No 0’s No 1’s
Problem follow-up
Problem follow-up
Stop at defect
Problem solving training
Containment
Std. work improvement
Quality alerts
Ensure quality loops
Design for quality
…
KPI tree as seen on shop floor
Actionable levers to improve KPI
APA actionable levers
No 3’s
Problem follow-up
No 5’s
Problem follow-up
No 9’s
Problem follow-up
Indicates recommendation to track values at line/station level
APAFACTSHEET
DEFINITIONCALCULATION
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.
3 faults/veh. x 0.4 = 1.20 faults/veh.
1 faults/veh. x 0.8 = 0.80 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
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 74Daimler Trucks
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
Level 1 calculation model:
0CU = shipped defect parts × 1,000,000Total shipped parts to all customers
Implementation / Measurement points:
• Defect measurement based on direct feedback from customer plants
• Measured for plant internal and plant externalfinal powertrain product customers
Base data required for KPI aggregation:
• Number of complaints from customer• Number of delivered units
Primary shopfloor levers:
Hierarchy relevance*:
Shopfloor KPI:
Abbreviation: 0CU Applicability: x TM TE TN TA
x E1 x E2 x E3 x E4 E5
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE
Unit: ppm
Tracking of KPI on shopfloor boards recommended
2.8
* Implies possible applicability to scorecard
Author: OMCD/E, January 2008 75Daimler Trucks
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.8
Author: OMCD/E, January 2008 76Daimler Trucks
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
DEFINITIONCALCULATION
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
Author: OMCD/E, January 2008 77Daimler Trucks
0-ppm Customer
Member availability
AbsenteeismTrained members
Problem follow-up
Problem follow-up
STD work audit
Manpower planning
Flexible manpower system
Clean sheet bonus
Std work audit
Training school
Re-balance work content
Accident alert
…
Quality
Defect a Defect b
Problem follow-up
Problem follow-up
Problem solving training
Containment
Std. work improvement
Quality alerts
Re-align quality standards
Design for quality
…
KPI tree as seen on shop floor
Actionable levers to improve KPI
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
DEFINITIONCALCULATION
MEASURE-MENT POINTS
SHOP FLOOR LEVERS
PLANT EXAMPLE 2.8
Author: OMCD/E, January 2008 78Daimler Trucks
3. KPI integration intoDaimler Truck scorecards
Author: OMCD/E, January 2008 79Daimler Trucks
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
Author: OMCD/E, January 2008 80Daimler Trucks
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
Author: OMCD/E, January 2008 81Daimler Trucks
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
Author: OMCD/E, January 2008 82Daimler Trucks
4. Reporting and KPI IT platform
Author: OMCD/E, January 2008 83Daimler Trucks
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
Author: OMCD/E, January 2008 84Daimler Trucks
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
Author: OMCD/E, January 2008 86Daimler Trucks
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
Author: OMCD/E, January 2008 87Daimler Trucks
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
Author: OMCD/E, January 2008 88Daimler Trucks
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
Author: OMCD/E, January 2008 89Daimler Trucks
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
Author: OMCD/E, January 2008 90Daimler Trucks
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
Author: OMCD/E, January 2008 91Daimler Trucks
* 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
Author: OMCD/E, January 2008 92Daimler Trucks
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
Author: OMCD/E, January 2008 93Daimler Trucks
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
Author: OMCD/E, January 2008 94Daimler Trucks
5. Performance dialogueand best-practice
exchange
Author: OMCD/E, January 2008 95Daimler Trucks
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
Author: OMCD/E, January 2008 96Daimler Trucks
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
Base of standardized KPIs
DT
Shop floor
PERFORMANCE DIALOGUE
Performance review
• Top-down Steering
• Target deviation discussion
•Clear definition of roles and
scorecard responsibilities
Steering
Operatingunit
Plant
Base of standardized KPIs
DT
5
Author: OMCD/E, January 2008 97Daimler Trucks
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
KPI coordinator SU/OU/region, OMCD
KPI coordinator SU/OU/region, OMCD
5
Author: OMCD/E, January 2008 98Daimler Trucks
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
Author: OMCD/E, January 2008 99Daimler Trucks
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
Author: OMCD/E, January 2008 100Daimler Trucks
6. Appendix
Author: OMCD/E, January 2008 101Daimler Trucks
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
Author: OMCD/E, January 2008 102Daimler Trucks
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)
Author: OMCD/E, January 2008 103Daimler Trucks
Top Operational KPIs - contact persons at OMCD/E
Contact Telephone Email
• Thomas Jung (Project Lead) +49 711 17 54574 thomas.j.jung@daimler.com
• Peter Hoffmann +49 711 17 32302 peter.p.hoffmann@daimler.com
• Ralf Hieber +49 711 17 55976 ralf.hieber@daimler.com
• Michael Lenz +49 711 17 56336 michael.lenz@daimler.com
• Wolfgang Dischler +49 7271 71 5407 wolfgang.dischler@daimler.com
• Wolfgang Danner +49 711 17 38023 wolfgang.danner@daimler.com
• Alex Corcoran +49 711 17 38024 alex.corcoran@daimler.com
6