Project Title

GB or BB name: XYZ

Define Phase

D M A I C

Deployment D M A I C

Project Charter D M A I C

Project Logo or SOA

Date:

1.2. Department & Machine involved 1.4. Weekly Meeting on: (day & time)

Planning

Plan / DMA: ?? Do/ I: ??

Check / C: ?? Act / C: ??

7. Team and Stakeholder Signatures 6. Controller Verification of Savings

5. Quantitative Objectives of the Project (to be achieved with the full implementation of all countermeasures)

6. Potential Savings (000$/year)

3. Project Description: (methods/tools to be used)

4. Project KPIs

2.1. Team members involved (names) 2.2. Internal and / or External Customer

Project Title

1.1. Project Title1.3. Problem description (What problem / Why is it a problem)

Team D M A I C

Name Function Role In the team In charge of…

Gantt Chart D M A I C

Framing Worksheet5W+2H (Operational Definition) [Plant Name][Project Name][Brief Project Description][Date]

Description of Problem

IS IS NOT

WhoCustomer Name

Location

WhatProductProcessSystem

WhenFirst Seen

When else seen(dates, events)When seen in

product life cycleWhere

On objectGeographically

WhySupportive Data

HowProcess Conditions

How Many# of Defects

# of Parts# of Concerns

Trends

D M A I C

Customer Requirements CTQ’s

VOC

for example:

Key Issues Customer CTQs

Measurable Requirements

1st level

Customer CTQs if needed

2nd level

1 When I’m staying in a hotel I like a good bath

right temperature Temperature > 30 degrees

< 36 degrees

Fills up quickly time to fill < 5 mins

2

3

D M A I C

SIPOC

Suppliers Inputs PROCESS Outputs CustomersUse nouns Use verbs Use nouns

Start point

Arrival point

For example

D M A I C

Measure phase

MD A I C

D M A I C

Current process map

Include some initial map of your process

Process Mapping [Plant Name][Project Name][Brief Project Description][Date]

START

END

STEP 1

NO

YES

STEP 2

STEP 2B

TESTRESULTS

D M A I C

Ys behaviorD M A I C

I-MR Control Chart [Plant Name][Project Name][Brief Project Description][Date]

Quality Characteristic Individual value of T3 - 2010Sample Size, n 1

k 3

CL, 2.278

UCL, 3.805

LCL, 0.751

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

5.5

6

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Ind

ivid

ua

l v

alu

e o

f T

3 -

20

10

Sample #

CL, 0.574

UCL, 1.877

LCL, 0.0000.000

0.500

1.000

1.500

2.000

2.500

3.000

3.500

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Ra

ng

e

Sample #

Cause & effect diagram to find potential Xs

Brainstorming - Fishbone analysis [Plant Name][Project Name][Brief Project Description]

[Date]

5 5 5

1 1 1

6 6 6

2 2 27 7 7

3 3 3

8 8 8

4 4 4

1 1 1

5 5 5

2 2 2

6 6 6

3 3 3

7 7 7

4 4 4

8 8 8

trouble

MAN METHODS MACHINES

PROBLEM STATEMENT

MATERIAL MOTHER NATURE MEASURES

what, who, where, when, how much, how

Methods

Measures

Machines

MaterialsMother Nature

Man

DEFECT

D M A I C

Data collectionD M A I C

Check Sheet [Plant Name][Project Name][Brief Project Description][Date]

Name:

Date:

Shift:

Defect

Stones

Blisters

Blank Tears

Baffle Match

Pressure Break

Totals

Shop 11 Shop 12

5

Shop 22 Shop 31 Shop 32Shop 21 Totals

5

Check sheet Pareto

Spaghetti Diagram (Flow analysis) [Plant Name][Project Name][Brief Project Description][Date]

Data collection planD M A I C

What How Who WhereMeasure Operational

definitionType of

measure – Y or Xs

Type of Data

Measurement tools

Sampling scheme and Frequency

Who is collecting the data

On which document - form

Measurement System Analysis

Potential source(s) of measurement variation checklist Yes/No Evidence

Is my measurement system repeatable? _______Will I get the same results if I make the measurement more than once?

Is my measurement system reproducible? _______ Will someone else be able to complete the same measurement & get the same results?

Is my measurement system accurate? _______Will the results from the study match the actual value or expert data?

The appropriate analysis tool to quantify the amount of variation due to the measurement system is

_______ Very simple assessment_______ Discrete data analysis tool (for repeatability, reproducibility & accuracy)_______ Gage R&R - ANOVA method_______ Gage R&R - Short method

Only if issues on Measuring system

Is the Measurement System adequate ______ Yes/No

D M A I C

Measurement System Analysis – Gage R&RD M A I C

Baseline process sigma

Number of units processed N = __________

Total number of defects made (include defects made and later fixed) D = __________

Number of defect opportunities per unit (equate to CTQs) O = __________

Calculate # defects per million opportunities DPMO = 1,000,000 x ( )

= 1,000,000 x

= __________

Look up process sigma in Sigma = __________ sigma conversion table

DN x O

( )

( ) ( )

(method 1)D M A I C

Baseline process sigma (method 2 – using Jmp)D M A I C

short term sigma = 0.74long term sigma value = 2.35

Stable or unstable ?

Analyse phase

MD A I C

D M A I C

Cause & effect diagram for Experience Door without data collection plan

D M A I C

Brainstorming - Fishbone analysis [Plant Name][Project Name][Brief Project Description]

[Date]

5 5 5

1 1 1

6 6 6

2 2 27 7 7

3 3 3

8 8 8

4 4 4

1 1 1

5 5 5

2 2 2

6 6 6

3 3 3

7 7 7

4 4 4

8 8 8

trouble

MAN METHODS MACHINES

PROBLEM STATEMENT

MATERIAL MOTHER NATURE MEASURES

what, who, where, when, how much, how

Methods

Measures

Machines

MaterialsMother Nature

Man

DEFECT

5 Whys Analysis for Experience Door without data collection plan

Catalyst Consulting Ltd. 2006

D M A I C

Brainstorming - 5 whys[Project Name][Brief Project Description]

[Date]

what, who, where, when, how much, how

Cause Why 1 Why 2 Why 3 Why 4 Why 5

1

2

3

4

5

6

7

8

9

10

PLAN

PROBLEM STATEMENT: Seal Star issues causing rework and overmanning

Statistical Analysis

Catalyst Consulting Ltd. 2006

D M A I C

Box plotScatterplotSimple regressionFit Y by XAnovaScreeningPartitioning…

Y=f(Xi) – Statistical ModelD M A I C

Vital few Causes

Critical X

1

2

3

4

D M A I C

Improve phase

ID M A C

D M A I C

Proposed solution D M A I C

Proposed solution D M A I C

add additional slides to elaborate on actions using pictures and summary activities

Control phase

CD M A I

D M A I C

32

D M A I C

ONE POINT LESSON (OPL)

Facility:Date Created: OPL Number:Author:OPL Category: Approver:Area in Facility: Approver Title:

OPL Description:

OPL

Control PlanD M A I C

Quality process control plan [Plant Name][Project Name][Brief Project Description][Date]

Indicators By whom?

Quality process control plan

When?Out of control actionwho is in charge?Control range

Final process sigma

Number of units processed N = __________

Total number of defects made (include defects made and later fixed) D = __________

Number of defect opportunities per unit (equate to CTQs) O = __________

Calculate # defects per million

opportunities DPMO = 1,000,000 x ( )

= 1,000,000 x

= __________

Look up process sigma in sigma conversion table Sigma = __________

DN x O

( )

( ) ( )

(method 1)D M A I C

Final process sigma (method 2)D M A I C

BEFORE AFTER

ROSS Control – the final outcome

Baseline Final

Performance

Project Y ZST

ZLT

Financial benefits

Cost ££

Revenue £

Cash £

Implementation costs £

Net Benefit £

D M A I C