Poisson

Binominal
For in-control processes to detect small shiAs from target

Equally weighted <- previous data -> exponen$ally weighted

6-Panel Corrective & Preventive Actions
a) What is the Voice of the Customer and how does it
link to your business objectives (Safety, Quality,
Delivery, Cost, etc.)?
b) What is important to the customer?
CTQ (Critical to Quality)?
c) Which Outputs (Ys) affect CTQ most?
d) What is: The defect? Cost of poor quality? Scope?
Goal?
e) Do you have Management Support and a CrossFunctional Team?
Project Charter
f) What is the problem statement? Linkage to Key
Business Plan Objectives (KPI)? Defect Definition /
CTQ (measurable)?
g) What is the Project Scope, and how contributes it to
Business Objectives? COPQ? Business Case?
h) What resources assist with the project (Enablers)
i) What is the Performance Metric(s)? Present/
Expected?
j) Who are the members on your team? Champion?
Process Owner? MBB? Contract signed?
Process Defined and High Level Process Map
k) Are the critical processes defined and decision
points identified?
l) Are all the key attributes of the process defined?
m)Do you have a high level process map?
General Questions (all phases)
n) Are there any issues/barriers that prevent you from
completing this phase?
o) Do you have adequate resources to complete the
project?
p) Have you prepared the 6-Panel report?
CT Matrix (a,b)
Process Mapping (k,l,m)
SIPOC (b, c, m)
Project Selection/Pareto Analysis (a, b, c)
Project Charter (a-j)
Pareto Analysis (d)
Lean 7(+2) wastes (d)

-> To test if a par$cular distribu$on (model) is a good t for a popula$on

6-Panel Corrective & Preventive Actions

a) Which Factors (Xs) seem to affect Outputs (Ys) most?
b) Is your ability to measure/detect Good Enough (MSA)?
c) Is your process stable and in control?
d) What is your current process performance
(capability)?
e) What actions are taken to protect the customer
(containment)? Have escape points been identified?
Identify critical Xs and potential failure modes
f) Is the as is Process Map created? Decision points and
data collection points identified?
g) Are all process Xs causing problems identified?
h) Are the vital few Xs (Critical Xs) selected?
i) Are risks of failure modes caused by Critical Xs assessed?
j) Is the measurement system acceptable?
k) Has the Problem Statement changed? COPQ?
Stability Assessment
l) Is the process stable?
m) Are the special causes of unstable processes identified
and fixed?
Capability Assessment
o) What is the short-term (Cp, Cpk) and long-term (Pp,
Ppk) capability of the process?
p) What is the problem, one of centering, spread or some
combination?

pppp
PPPP

Chi Square Goodness of Fit

Cover/Define Panel (a-j)

Project Charter (a-j)
Team Members (e)
Process Map high level (k,l,m)
Performance Metrics (c,g,i)
Lean Opportunities (a,c,d,g)
Stakeholder Analysis (e)
All Phases:
Project Plan (h,j,n,o,p)
Issues and Barriers (n)

KEY QUESTIONS

Process Mapping (f)

Fishbone Diagram (f,g)
Cause & Effect (XY) Matrix (a,h,i)
FMEA (a,h,i)
MSA (b,j)

Measure Panel (a-e,j,o,p)

Detailed (Level 2) Process Map IS (f)
Vital Few Xs (Critical Xs) (h)
Data Collection Plan (f)
MSA (incl.GR&R) (b,j)
Process Stability (c,l,m)
Baseline Performance/Capability (d,o)

Graphical Techniques (Dot Plot, Box Plot, Jitter Plot,

Time series) (a,g,h,l,m)
Process Stability/Capability studies (c,d,l,o,p)

KEY QUESTIONS

6-Panel Corrective & Preventive Actions

a) Which Factors (Xs) affect the Outputs (Ys) most (with
data)?
b) How many samples do you need to draw conclusions?
c) What level of confidence do you have in your conclusions?
Define Performance Objectives Graphical Analysis
d) Is existing data laid out graphically?
e) Is the response discrete or continuous?
f) Is it a Mean or a variance problem or both?
Document Potential Xs Root Cause Exploration
g) Are there a reduced number of potential Xs?
h) Are the number of likely Xs reduced to a practical number for analysis?
i) What is the statement of Statistical Problem?
j) Does the process owner buy into these Root Causes?
Analyze Sources of Variability Statistical Tests
k) Are there completed Hypothesis Tests?
l) Is there an updated FMEA?

Process Mapping (a, g)

Value Analysis, & Cycle Time Analysis (a, g)
Multi-Vari studies (X-Sifting) (a, g)

Analyze Panel (a-l)

Detailed Process Map IS (Level 3) (a, g)
Data Demographics (d, e, f, g, h)
Hypothesis tests (for statistical significance) (e, f, g, h,
I,k)
Vital few Xs & Root Cause Verification (a, g, h, i, k)
Strategy to reduce Xs (a, g, h, I, k)
Updated FMEA (l)

Classes of distributions (Normal, Skewness (left, right),

Kurtosis (leptokurtic (peaked), platykurtic (flat)), Multi
Mode, Granular) (d, e, f)
Inferential Statistics (Sampling, Centr.Limit Theorem) (b,
e,f)
Hypothesis Testing (Normal, Non-Normal, Attribute.Data) (a, b, c, e, f, g, h, i, k)
Graphical Techniques (Histogram, Box Plot, Individual
Value Plot) (d)
Lean Tools standardized work (a)
Process FMEA (P-Diagram) (l)
Contribution Analysis

TOOLS
DELIVERABLES

KEY QUESTIONS
TOOLS
DELIVERABLES

6-Panel Corrective & Preventive Actions

a) What is the optimal Y=f(X) solution? Against which
noise factors?
b) What is the proof that the solution works? How many
trials?
c) What is the work plan to implement and validate the
solution?
Experimental Optimization of Vital Few Xs
d) Are the potential Xs measurable and controllable for an
experiment?
e) Are they of statistically significance and practical significance?
f) How much of the problem have you explained with
these Xs?
g) Have you clearly justified the need for conducting a
Designed Experiment?
h) Have you validated the fix (Permanent Corrective Action
(PCA))?

Brainstorming Alternative Improvements (a)

Correlation Analysis (f)
Simple Linear Regression (one X, one Y) (f)
Multiple Linear Regression (two or more X, one Y) (f)

Improve Panel (a-h)

Process Map Should be (a)
Generated & Selected Alternatives (a)
FMEA improvements (c)
Experiments: Justification, Plan, Objective & Results (a,
d, e, f, g)
Pilot improvements (b)
Process Capability study improvements (a, b, h)
Cost/Benefits (a)

Non-Linear Regression (quadratic, cubic, exponential,

logarithm, inverse) (f)
Residual Analysis (a, f)
Confidence and Predictive Intervals (a, f)
Transforming Process Data (Box Cox) (a, e)
Fractional Factorials (Screening DOEs) (a, d,e, f, g)
Full Factorials (Blocking, Center Points) (a, d, e, f, g)
Response Surface Methods (RSM) (a, d, e, f, g)
Cost/Benefits Analysis (a)

KEY QUESTIONS
TOOLS
DELIVERABLES

6-Panel Corrective & Preventive Actions

a) Can you demonstrate the improvement is sustainable
over time?
b) Is the process in control?
c) How do you keep it that way?
Process Enhancement and Control Results
d) How do the results of the improvement(s) match the
requirements of the business case and improvement
goals?
e) What are the vital few Xs? How to control, redesign?
f) Is there a process Control Plan in place?
g) Has the Control Plan been handed off to the process
owner?
Capability Analysis for X and Y Process Capability
h) How are you monitoring the Ys?
Standardization and Continuous Improvement
i) How are you going to ensure that this problem does not
return?
j) Is there a project documentation file?
k) How is this referenced in process procedures and product drawings?
l) What is the mechanism to ensure this is not reinvented
in the future?

Process or Design FMEAs (b-l)

Control Plans for Process and Gage (a, b, c, e, f, g, h, i)
Statistical Process Control (SPC) (a, b, c, e, f, g, h, i)
Standard Operating Procedures (SOP) (i, j, k, l)
Visual Factory (h, i, l)
Preventative Maintenance (c, i, k)
Poka Yoke / Error/Mistake Proofing (c, i)

KEY QUESTIONS
TOOLS

Document special cause actions (Global 8-D), as necessary.

Control Panel (a-g)

Capability of Improved Process (a, b)
Control Strategy (incl. Lean Controls/Error Proofing) (b,
c, e, f, g, h, i, j, k, l)
Control Plan (Monitoring Plan) (a, b, e, f, g, h)
Reaction Plan (Response Plan) (a, b, e, f, g, h)
Training Plan (c, i)
Documentation Plan (Prevent Recurrence) (c, j, k, l)

DELIVERABLES

contd ->

4. Select the Input (independent) Variables

5. Choose the Levels for the Input Variables
6. Select the Experimental Design
7. Execute the experiment and Collect Data
8. Analyze data from experiment, draw Sta$s$cal Conclusions
9. Draw Prac$cal Solu$ons
10.Validate the experimental results
11.Implement Solu$ons

TOOLS

DOE Methodology:
1. Dene the Prac$cal Problem
2. Establish the Experimental Objec$ve
3. Select the Output (response) Variable

STEPS: The same as by Normal data except:

5. Run the appropriate Attribute Test.

DELIVERABLES

Z
= lt
3

Advanced Process Modelling Regression:

1. Create Sca:er Plot
2. Determine Correla$on: Pearsons Correla$on (r)>80% and pvalue<0.05)
3. Run Fi:ed Line Plot choosing linear op$on
4. Run Regression
contd ->

5. Evaluate R2, R2 adjusted and P-values

6. Run Non-linear Regression if necessary
7. Analyze residuals to validate assump$ons

6 slt

(USL LSL )
5. Check for NON-Normality and conduct the test.

KEY QUESTIONS

Ppk
=

STEPS: The same as by Normal data except:

1. State the Practical Problem

TOOLS

C pk

Z
= st
3

Calculate DPU
Look up DPU value on the Z(lt)-table ; (Zst = Zlt + 1,5)
Find the Z(lt)-score
Covert Z-score to Cpk, Ppk

6s st

(USL LSL )

2 Meas

STEPS:

DELIVERABLES

Visit the Consumer Driven 6-Sigma Web site at

https://comm.extsp.ford.com/sites/6SigmaPTS/Pages/Default.aspx

REVISION 1.3
1.
2.
3.
4.

Capability (attributive data):

Process potential: Cp =
Process capability:

Capability (continuous data):

2 Parts

2. State the statistical problem

2 tailed: Ho: equal, Ha: not equal
1 tailed: Ho: larger/smaller or equal, Ha: smaller/larger
3. Select the appropriate statistical test & risk levels
a) =? (default 0,05)
b) =? (default 0,1)
4. Establish sample size required to detect the difference.
5. Asses Normality and conduct the test.
6. State the Statistical Solution
7. State the Practical Solution.

2 Total
The Standard Problem Solving & Process Improvement
Methodology at Ford Motor Company (see FAP07-004)

FMEA Prioritization (of Recommended Actions):

1. Severity (S)
2. Criticality = S x O (Occcurence)
3. Risk Priority Number (RPN) = S x O x D (Detection)

6-Panel Corrective & Preventive Actions

a) Who else at Ford can benefit from the project findings?
b) What has been done to update the corporate
knowledge?
c) (Six months later) Is the improvement sustained?
Replication
d) Are areas where the project findings can be quickly
replicated (eg, same part on sister or other vehicle
line?) identified?
Corporate Memory Updates
e) Are Prevent Recurrence actions for each critical X
within the requirements (SDS/VDS: Trustmark,
GAP, Specifications), Foundation FMEAs, CETP,
MDS, Control Plans, LQOS, etc. identified
f) Are prevent recurrence actions cascaded throughout the supply chain?
Warranty Savings Opportunities
g) Are warranty costs associated with the issue?
h) Is causal part on QB top spend pareto and/or IFR
list?

Replicate Panel (a-h)

Warranty Savings Checklist (g, h)

Process/Tools to update Corporate Memory and

drive Replication: Instructions, Corporate Memory
Documents List, FAQs, Contacts (b, d, e, f)

Health Chart template available at http://

www.quality.ford.com/warranty/html/gcl_pr.htm
(b, e, f)

Global Corporate Learning & Prevent Action Health

Chart Process via eTracker
(http://www.etracker.ford.com/apps/AddIssues/
AddIssue.asp?ProjectID=GCORPLRN) (b, e, f)

Corporate Memory Updates (SDS/VDS, Trustmark,

GAP, Specifications, Foundation FMEAs, CETP,
MDS, Control Plans, LQOS, etc.) (b, e, f)

6-Panel attached to eTracker to aid Corporate memory SME (b, e, f)

Warranty Savings checklist (if causal part is on QBs

top parts lists) (g, h)