Expanding Six Sigma to Suppliers

Elizabeth CudneyCQE, SSBB

December 5, 2005

The Definition of a Lean Enterprise

A group of individuals, functions, which are sometimes separate but operationally synchronized organizations.

The objectives of the lean enterprise are:

• “Correctly specify value for the customer”

• “Identify all the action required to bring a product from concept to launch, from order to delivery, and from raw material into the hands of the customer and on through its useful life.”

• “Remove any actions which do not create value and make those actions which do not create value proceed in continuous flow as pulled by the customer.”

• “Analyze the results and start the evaluation process over again.”

Source: Womack, James P. and Jones, Daniel T., Lean Thinking: Banish Waste and Create Wealth in Your Corporation, Simon & Schuster, New York, NY, 1996.

What is Lean?

• Lean Manufacturing focuses on eliminating waste and improving flow using various Lean principles and their respective approaches.

• VSM, standard work, 5S, SMED, visual management, etc.

Lean Overview

• Lean emphasizes the elimination and prevention of waste.

• Lean is focused on the customer by addressing what is value added and what is non-value added.

• Products and services are delivered Just-in-Time meaning in the right amounts, at the right time and in the right condition.

• Products and services are produced only when a signal is received from the customer and are pulled through the system.

• A lean system allows for an efficient response to fluctuating customer demands and requirements.

Lean Benefits

• Eliminate waste

• Reduce non-value added activities

• Improve process flow

What is Six Sigma?

• Strategy to minimize variation towards the goal of 3.4 defects per million.

• A philosophy to promote excellence in all business processes.

• A 5 phase methodology for continuous improvement.

• A statistic which describes the amount of variation in a process.

• A tool to reduce or eliminate variation.

Six Sigma Overview• Six Sigma is a customer focused continuous

improvement strategy and discipline that minimizes defects and variation towards an achievement of 3.4 defects per million opportunities in product design, production, and administrative processes.

• It is focused on customer satisfaction and cost reduction by reducing variation in processes.

• Six Sigma is also a methodology using a metric based on standard deviation.

• Six sigma targets aggressive goals.

Six Sigma Benefits

• Stronger knowledge of products and processes

• Reduction in defects

• Increased customer satisfaction level that generates business growth and improves profitability

• Increased communication and teamwork

• Common set of tools

Why should we combine them?

• By combining the Six Sigma DMAIC methodology with lean manufacturing tools, companies have a more appropriate toolkit to address all types of process problems and can reap even more dramatic gains.

Lean vs. Six Sigma

Broad trainingLearn by doing

Specific trainingLearn by doing

Training

Dedicated resourcesAd-hoc – kaizen basedInfrastructure

Long-term cyclical improvementShort-term focusLength of Projects

Various approachesDriven by Value Stream MappingProject Selection

Generic problem solving approach using statistics

Lean technique specificBasic principles and best practices

Approach

All business processesMainly manufacturing processesApplication

Corporate cultureOperations level (at minimum)Culture

StrategicProject orientedOperations level

Business Scope

Reduce variationImprove process capability

Create flowEliminate waste

Goal

Six SigmaLean

Lean, Six Sigma, or Both?

• Which is better?

• What do we first?

• Can the two approaches be combined?

• How do we reap the biggest reward?

Systematic Approach

Standard Work

DEFINE

MEASURE

ANALYZE

IMPROVE

CONTROL

Create flow

Eliminate Variation

Quadratic Loss Function

Quality Characteristic

Design of Experiments

Quadratic Loss Function

Quality Characteristic

DMAIC Approach to Lean and Six Sigma

D

M

A

I

C

Voice of the CustomerValue Stream Mapping

SPC, Standard Work, Control Plan

Kanban, Visual Management, Heijunka, Poke-Yoke,Design of Experiments

TAKT Time, Cause and Effect Diagram, FMEA,Hypothesis Testing

5S, Capability Analysis, Measurement System Analysis, Spaghetti Diagram, Process Flow Diagram

Project Selection

Understand the process and identify

potential factors

Confirm the vitalfew factors

Optimize and implement solutions

Sustain results

Phase Deliverables

Define

• Value Stream Mapping

Source: Rother, Mike and Shook, John, Learning to See: Value Stream Mapping to Add Value and Eliminate Muda, The Lean Enterprise Institute, Brookline, MA, 1998.

Value Stream Mapping

• Value Stream Mapping is the first building block to integrating Lean and Six Sigma.

• The purpose of Value Stream Mapping is to understand the big picture.

• The current value stream consists of all actions necessary to deliver a product including value added and non-value added.

• Value stream mapping must be conducted first to provide an effective blueprint for implementing an improvement strategy.

• A key step in creating the current state map is to calculate TAKT time.

Measure• Quality Loss Function

• Specifications

Loss (L) (L) = k (µ - T)2

Targety (response

value)

Where, •k is a monetary constant,•

,•µ is the mean, and•T is the target.

20

0

∆=

Ak

EquallyGoodBad Bad

LSL USL

EVERYTHING IS NOT EQUALLY GOOD

Beware of the “Goalpost” Mentality

• The value of manufacturing specifications to the customer is only important when they receive a product that is defective.

• Specifications create “goalposts” for product acceptance.

• To the customer, the specifications should be created based on their expectations and requirements.

• A benefit of using the quadratic loss function is that it is in monetary units.

Analyze

• Design of Experiments– Structured method to determine the

relationship between factors (Xs) that affect a process and the output of the process (Y).

Improve

Eliminate variationImprove flow

Control

• Standard work– A lean tool that defines and documents the interaction

between people and their environment.Operation From: Raw Material STANDARD WORK SHEET Part No. Sequence To: Finished Material Part Name:

7

+

6

+5

+4

+3

+

2

+1

+ RM 13

8

+

9

+10

+11

+12

+ 14

15 16 FM Quality Check Safety Standard WIP # Pieces WIP TAKT Time Cycle Time +

10 474 944

Operator 1

Operator 2

Case Study

• Six Sigma project performed on the casting process at a casting supplier to reduce center line shrinkage.

Extended Value Stream

Raw Material Casting Supplier

Machining &

AssemblyCustomer Consumer/

End User

Value ChainCasting Supplier

Manufacturing&

Assembly

CustomerQDC MetricsRipple effect throughout the entire value chain

Casting process capability and variation

Manufacturing and assembly variation

QDC – Quality, Delivery, Cost

Customer Satisfaction!!!!

Customer/End User

Variation in product performance in the hands of the customer

Objective

• The objective of this case study was to utilize the Six Sigma DMAIC methodology in conjunction with lean manufacturing techniques to meet customer requirements in terms of both the level of quality performance and production requirements.

Introduction

• Objectives* More Efficient

Process* Reduce Costs* Reduce Quality

Defects* Improve Delivery

• Performance Measures* Production Numbers* Scrap Numbers* On-time Delivery

Goals

• Reduce internal PPM from 23,309 to 5,827 (75% reduction)

• Reduce annual COPQ from $200,100 to $50,025 (75% reduction)

• PPM savings of 17,482

• COPQ annual savings of $150,075

Casting Porosity

R20.0008 =

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

Jan

Feb

Mar

Apr

May Jun

Jul

Aug

Sep

Oct

Nov

Dec Jan

Feb

Mar

Apr

May Jun

Jul

Aug

Month

PP

M

PPM

PPMPPM GoalLinear (PPM)

PPM

Changed suppliers

Casting Porosity

R20.0297 =

$0

$20,000

$40,000

$60,000

$80,000

$100,000

$120,000

$140,000

Jan

Feb

Mar

Apr

May Jun

Jul

Aug

Sep

Oct

Nov

Dec Jan

Feb

Mar

Apr

May Jun

Jul

Aug

Month

COPQ

/Kit

COPQ

COPQCOPQ GoalLinear (COPQ)

COPQ

Changed suppliers

Variation Reduction Kaizen

• One week kaizen format used to kickoff the Six Sigma project.

• Kickoff the Six Sigma Black Belt project by applying Process Flow, Cause and Effect with CNX/SOP to reduce casting centerline shrinkage.

• Goal was to change the number of noise variables to constants by 50%.

Process Flow Diagrams

• Process flow diagrams for all relevant supplier processes were documented.

Sand Mullor Process Flow Diagram

Custom mix (Clay) Water Returned sand

Mull

Discharge fortesting

System adjustsfor last

5 readings

Using recipedetermine

charge

Add slagcoagulant

Molding Machine Process Flow Diagram

Sand droppedfrom hopper

Flask rollsback over

Flask comes up and seals

Flask rollsover

Fill drag side

Feed bottomboard

Hopper carmoves out

Flask car movesout/dischargesprevious mold

A

A

B

Excess sandcollected asreturned sand

Hopper cardrawn back

Fills cope

Molding Machine Process Flow Diagram Cont’d

B

Flask carpulled back

Cope and dragsqueezed

Is moldgood? Mold scrapped

No

Yes

Add cores andfilters as needed

Jacket added

Wait in transfersystem for hot

metal

Blow out drag, cores, filters

C

C

A

Melting Process Flow DiagramReceiving inspection

of ferro alloys

Receiving inspection of raw materials

Collect scrap/ returns

Put into bins1) Steel2) Pig iron

Using recipeDetermine

charge

Load onto scale

Load into preheater

Dump into one of 3 furnaces

Add alloys

Melt

A

Temperaturetaken

At 2750°F? Continue

heating

B

No

Yes

Melting Process Flow Diagram Cont’d

Sample pulled for LA test

Increase KW totap temperature

Add slagcoagulant

Remove slag

Tap intotransfer ladle

SampleGood?

Adjust by Adding steel and silicon

No

Yes

B

Pouring Process Flow Diagram

Add alloy totreatment ladle

Weigh iron

Take to pouring zone via monorail

Distribute into oneof 3 pouring ladles

and inoculate

Receive ironin treatment ladle

Remove slag

Fill coupon (test slug)

Follow lastmold

Check formodularity

Begin pouring

Pour test bars eachshift for each class

of iron

Empty pouringladle completely

A

A

B

B

Sand Mullor Cause and Effect Diagram

Measurement Method Machine

Manpower Materials Environment

Centerline Shrinkage

(N) Failed moisture test

(N) Failed permeability

(N) Failed green strength

(N) Failed compactibility

(N) Temperature of sand

(N) Failed sieve analysis

(N) Time on conveyor

(N) Missed a manual test

(N) Poor Gage R&R

(N) Failed clay wash

(N) Manual test Gage R&R

(N) Mullor ran manually

(N) Improperly mulled sand

(N) PLC control fails

(N) Mullor fails

(N) Hoppers not cleaned

(N) Untrained operator

(N) Temperature of sand

(N) Contaminated materials

(N) Shop Temperature

(N) Humidity

Molding Machine Cause and Effect Diagram

Measurement Method Machine

Manpower Materials Environment

Center Line Shrinkage

(C) Squeeze pressure of mold machine

(N) Sand temperature

(N) Shake out time

(N) Cope (not enough sand)

(N) Drag (not enough sand)

(N) Window location (relative to shrinkage)

(N) Lack of support on top of casting

(N) Swell

(N) Cracked mold

(N) Storage conveyor temperature

(N) PLC control fails

(N) Weight Distribution

(N) Mold not inspected

(N) First mold not inspected

(N) Chills not set properly

(N) Chills not set at all

(N) Operator not trained

(N) Mold not blown out

(C) Pattern preparation

(C) Improper set-up

(C) Wet sand

(N) Wrong size filter

(N) Defective filter

(N) Dust (dry sand)

(N) Pattern not clean

(C) Green sand strength(N) Shop temperature

(C) Mold hardness

(N) Shop humidity

Melting Cause and Effect DiagramMeasurement Method

Manpower Materials

Center Line Shrinkage

(N) Temperature of furnace

(C) Carbon equivalent

(N) Preheat temperature

(N) Preheat too short

(N) Scale

(N) Carbide tendency

(N) Lab test gage R&R

(N) Lab test error

(N) Improper slag removal

(N) Material falloff

(N) Melt too cold

(N) Transfer time

(N) Temperature control error

(N) Charge makeup error

(N) Training

(C) Alloys incorrect

(C) Chemistry out of balance

(N) Manganese Content

(N) Materials mixed

(N) % of returns used

(N) Material cleanliness

(N) Chemical composition

(N) Material size

Pouring Cause and Effect Diagram

Measurement Method Machine

Manpower Materials Environment

Center Line Shrinkage

(N) Zero scale weight

(N) Failed nodularity test

(N) Spectrometer gage R&R

(N) Temperature of sand

(N) Incorrect weighing

(N) Pouring temperature

(C) Holding time

(N) Pouring time

(N) Runout

(N) Ladle not empty at start

(N) Failed ductile iron

(C) Weight of jacket/cleanliness

(N) Ladle not preheated

(N) Mold not clean (sand in sprue hole)

(N) Slag buildup on ladle

(N) Reverse taper sprue

(N) Ladle lip changes

(N) Sprue design

(N) Pouring time

(N) Turbulence of pour

(N) Short pour

(N) Operator not trained

(N) Velocity of pour material

(N) Proper temperature

(N) Proper inoculation

(N) Too much in treatment ladle

(N) Too little in treatment ladle

(N) Filter missing

(N) Failure to remove slag

(N) Shop temperature

(N) Shop humidity

Noises to Constants

• Action plan created to change noises to constants

• i.e. Pattern Preparation and Set-up– Check sheet on Manufacturing Order– Check sheet used at every job changeover– Procedure established for molding machine setup– Standard gating procedure for pattern PM

Process FMEA

483Visual inspection2Wrong material used

963Visual inspection4Charge hanging up in bucket

723Visual inspection3Operator error when adding charge material

1127PM2Scales out of calibration

8Chemistry out of spec

324Visual inspection4Charge hanging up in bucket

183Visual, scales3Operator error when adding charge material

287PM2Scales out of calibration

2Furnace too empty

273Visual, scales3Operator error when adding charge material

427PM2Scales out of calibration

3Furnace too fullIncorrect weight of charge material

Melting

Controlsof FailureVof FailureModeRequirements

ProcessMechanism(s)EEffect(s)FailureFunction

RPNDetec.CurrentOccPotential Cause(s)/ClassSPotentialPotentialProcess

Core Team:_____________________________________

Key Date_________________________________Model Year(s)/ Vehicle___________________________

Process Responsibility______________________Item _Melting______________________________________

PROCESS FMEA

POTENTIAL FAILURE MODE AND EFFECTS

ANALYSIS

Design of Experiments

Casting Process

Pouring Temperature2650 - 2400°F

Squeeze Pressure/Mold Hardness1200 - 800

Silicon Content2.80 – 2.20

Shrink Free Part

INPUT PROCESS OUTPUT

DOE Setup

80024002.208120024002.20780026502.206

120026502.20580024002.804

120024002.80380026502.802

120026502.801

Squeeze Pressure

Pour TempSi TargetRun

DOE

• Optimal settings for pouring temperature, silicon content and squeeze pressure determined.

Results

• PPM at the start of the project: 23,309• PPM at the end of the project: 221• Results are a 99.1% reduction in internal PPM

• COPQ at the start of the project: $200,100• COPQ at the end of the project: $238• Results are a 99.5% reduction in COPQ

Key Points

• Build relationships with suppliers

• Train your suppliers

• You are only as good as your suppliers

Thank you