AUTOMOTIVE CORE
TOOLS;
SPC, MSA, FMEA,
APQP/CONTROL PLAN
 CQI Wessex - 11 December 2012
 John Skinner
rdaconsultancy.com
1
AUTOMOTIVE PROGRESS SINCE
1990
Best selling car in the UK in 1990 –
Ford Fiesta – sold in EU
1.4, 1.6 CVH engines were very harsh and
had early failures (valve guide wear,
dropping valve seats damaging the engine).
Rust was still a problem, though better than
the 1970’s & 80’s.
Radio-cassette, some speaker adjustments, maybe electric windows. No a/c
and definitely no climate control. No airbags, little in the way of crumple
zones. Central locking on higher end models. Door mirrors had ‘remote
adjustment’ on top models. Security was very poor – cars like the XR2 were
being stolen by joyriders on a regular basis (epidemic levels in some areas).
Car insurance costs on ‘hot’ models went through the roof. No ABS, stability
control etc.
Cost – around £8500 – roughly equivalent to £15000 in today’s prices
WHAT CHANGED?
 Improvements demanded by legislation (emissions, safety),
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safety (NCAP), competition (i.e. VW/Audi), consumer
demand (phone compatibility, convenience features etc.)
A thorough focus on improved product quality achieved
through; computer modelling/simulation, enhanced testing
techniques (bench and road), consumer feedback (JD
Power), supplier capability, effective corrective action (8D)
Increased use of electronics (particularly powertrain)
Need to improve product reliability (reducing warranty/
product recall costs)
Application of ISO/TS16949 and mandated use of
Automotive Core Tools ?
ISO/TS16949
 Initiated as QS9000 in 1995, based on the requirements
of ISO9001, but adds many automotive industry specific
requirements (though only one additional documented
procedure from ISO9001)
 Produced and controlled by the International
Automotive Task Force (IATF)
 Members include; Ford, GM, VW/Audi, PSA, BMW,
Chrysler, Renault, Daimler and major trade
organisations across the globe
 Recognised and required as a prerequisite for becoming
an ‘approved supplier’ to the respective automotive
customers
AUTOMOTIVE REQUIREMENTS
 APQP; Advanced Product Quality Planning
 FMEA; Failure Mode & Effect Analysis
 Control Plan
 SPC; Statistical Process Control
 MSA; Measurement System Analysis
 These require a team approach (cross functional teams
with management commitment)
 Automotive Industry Action Group (AIAG) manuals
define basic requirements for application
 There are other requirements, based on the customer
Advanced Product Quality Planning
(APQP)
ISO9001 requires Planning of Product Realisation;
The Automotive industry goes further;
‘Some customers refer to project management or
APQP as a means to achieve product realization. APQP
embodies the concepts of error prevention and
continual improvement as contrasted with error
detection and is based on a multidisciplinary
approach’.
(extract from ISO/TS)
Advanced Product Quality Planning
 Why plan?
 What gets in the way of planning?
Concept
Initiation
/Approval
Product Quality
Planning Timing Chart
Program
Approval Prototype Pilot Launch
Planning
Planning
Product design
Process design
Validation
Production
Feedback assessment & corrective action
Plan & Define
Programme
Product Design
& Development
Verification
Product &
Process
Validation
Feedback Assessment
& Corrective Action
APQP – Project Scope
 2011 model year Range Rover – minor changes
APQP – Project Scope
 2012/13 model year Range Rover - major project.
 New design, technologies, material – aluminium, using
self piercing rivets and aerospace sourced epoxy adhesive
Advanced Product Quality Planning
(APQP)

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Advantages;
Thorough planning and improved decision making
Shorter development timescales
Simultaneous engineering (design & manufacturing)
Early procurement of long lead time tooling/facilities
Defined objectives, measured as project stages are achieved
Defined project gateways, with key deliverables
Improved use of resources
Significant cost savings (known impact on company
finances)
 Effective feedback & corrective action (enhanced with use
of computer systems)
Failure Mode & Effect Analysis
(FMEA)
 Typically used at design (DFMEA) and manufacturing
process planning (PFMEA) stages
 FMEA - a systematic set of activities intended to:
a) Recognise and evaluate the potential failure of a
product/process and the consequential effects of failure
(risk management)
b) Identify actions that could eliminate or reduce the
chance of the potential failure occurring (improvement)
c) Document the entire process
d) Needs a ‘team approach’ to be successful
DFMEA
DFMEA
System
FMEA Team:
xxxxxxxx
Team Leader:
xxxxxxxx
FMEA Number: 001
FMEA Date:
(Original) xxxxxxxxxx
Subsystem
X
Component
xxxxxxx
(Revised)
Detection
RPN
225
Responsibility and
Target Completion Action Taken
Date
Occurrence
5
Recommended
Action
Severity
Current
Controls Detection
RPN
5
Current
Controls Prevention
Detection
9
Potential
Cause(s)/
Mechanism(
s) of Failure
Occurrence
Potential
Potential
Effect(s) of
Failure Mode
Failure
Class
Item and
Function/
Requirements
Severity
Action Results
9
3
3
81
DFMEA
DFMEA
System
Wheel bolts; Support Bolts fail after
wheel & tyre
wheel impact
Transmit loads to stub with kerb
axle/vehicle
suspension
Loss of
wheel,loss of
control of
vehicle,
possible
fatalities,
resulting legal
action
Potential
Cause(s)/
Mechanism(s)
of Failure
Incorrect
material grade
(new hub nut
design)
10
Current Controls Current Controls
- Prevention
-Detection
Design
calculations
7
Wheel hub
RPN
Potential Failure
Mode
Potential
Effect(s) of
Failure
Component
Detection
Item and Function/
Requirements
X
Occurrence
xxxxxxxx
Class
Team Leader:
Subsystem
CC
xxxxxxxx
Severity
FMEA Team:
5
350
Pre design freeze
test to failure
vaidation
DFMEA
FMEA Number: 001
FMEA Date: (Original) xxxxxxxxxx
(Revised)
RPN
Conduct a full virtual
PTO engineering; Q1
analysis using design FEA 2013
& simulation software
(proven performance)
Action Taken
Detection
Responsibility and
Target Completion Date
Occurrence
Recommended Action
Severity
Action Results
10
7
2
140
Virtual anlysis
completed; results
acceptable to spec.
xxxx
DFMEA
 Ignores manufacturing issues; i.e. manufacturing

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producing/using parts that are to specification
Can direct design effort to critical/significant characteristics
and improve design validation/ verification testing results,
avoiding late design changes
Identifies special characteristics that need to be controlled in
manufacturing to assure product quality
Provides a documented record of the analysis which can be
used into the future (many vehicle recalls could have been
prevented by effective DFMEA)
Needs to be maintained as a live document; continual
improvement
PFMEA
 A PFMEA will follow the stages defined for the
manufacturing route from material receipt, through
the manufacturing stages to despatch
 Typically the manufacturing route will be defined on a
process flow diagramme, including locations,
machines, operation sequences etc.
PFMEA
PFMEA
System
Bearing Ø
oversize
Potential Effect(s) of
Failure
Bearing wear (with
warning), loss of wheel,
loss of control of
vehicle, possible
fatalities, resulting legal
action.
100% of product may
be scrapped
Potential Cause(s)/
Mechanism(s) of
Failure
Incorrect tooling
set up
9
Current Controls - Current Controls Prevention
Detection
Pre-set tooling
used
5
Wheel hub/new
design
RPN
OP 70; Finish machine
bearing bores (CNC)/
dimensions to
specification
Potential
Failure Mode
Component
Detection
Item and Function/
Requirements
X
Occurrence
xxxxxxxx
Class
Team Leader:
Subsystem
CC
xxxxxxxx
Severity
FMEA Team:
6
270
Post operation
gauging - 10%
PFMEA
FMEA Number: 001
FMEA Date: (Original) xxxxxxxxxx
(Revised)
RPN
PTO engineering; Q1 2013
Action Taken
Detection
Install in-station gauging as part of
machine upgrade
Responsibility and Target
Completion Date
Occurrence
Recommended Action
Severity
Action Results
9
5
3
135
in-station gauging integrated
into machine; auto lockout on
detection
PFMEA
 Focuses on potential for non-conforming product (in use
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and impact on manufacturing process including employee
safety) and mistake proofing techniques
Identification/prioritisation of potential failure modes and
implementation of preventive/corrective action
Focus on special characteristics
Continual improvement
Assumes product as designed will meet intent
Should be extended to other areas; receiving, storage,
transport, despatch etc. (complete process)
Provide feedback to design (mistake proofing features etc.)
Control Plan
 A documented description of the systems and
processes required for controlling product
 This is a key output once the DFMEA and PFMEA
analysis has been completed
 Applies to distinct stages; Prototype, Pre-launch and
Production.
 Each part must have a control plan, but family control
plans can be used where justified (e.g. a foundry
producing many different castings)
Control Plan
Control Plan
Part #:
N/A
Prepared By:
Part Name/Description:
Wheel Hub / new design
Core Team:
Latest Change Level:
#REF!
Supplier/Plant App./Date:
Vendor ID:
#REF!
Other Approval/Date:
#REF!
Oper. #
Process Description
Machine/Device/Jig/Tools
XXX CNC machining centre
OP 70; Finish
machine bearing
bores (CNC)
Notes:
Production Control Plan
Supplier Plant/Code:
Characteristics
Item#
70
xxxx
xxx, xxx, aaa,
bbb, ccc
Product
Bearing Inner
Bore diameter
CC
Process
Finish
machine;
25mm/min,
CBN tip (XYZ)
SC
CC
Process/Pdt. Spec./Tolerance
75 +0.008 -0.000 mm
0.003 mm run out max
G.ID
In cycle
gauging.
Control Plan
xxxxx
Date (Original):
Customer Engg. Appr./Date (Opt):
Cust. Quality Appr./Date (Opt):
Other Approval/Date (Optional):
Control Plan No.:
CP001
Methods
Eval. Mst. Technique
In cycle gauging.
Sample Size
Sample Frequency
100%
Control Method
100% Machine control
datalogger
Reaction Plan
Lock out; setter informed, machine checked and
re-set. Suspect material quarantined; (Corrective
Action Report - CAR)
Control Plan
 Identifies the controls required to ensure product
quality with a focus on special characteristics
 Defines the reaction plans required to be implemented
where non-conformance is identified (containment of
product, 100% inspection to ensure process becomes
stable and capable)
 Is an output from the FMEA process
Statistical Process Control
 Traditional inspection techniques (patrol inspection,
batch sampling etc.) rely on detection, which is
wasteful as time and resources are put into producing
parts that are not always useable
 Prevention verses detection; i.e. not producing the
non-conforming parts in the first place is an obvious
preferred situation
 If we can predict the process output, then we may be
able to ensure conforming parts
 Statistical techniques can be used for process control
Process Control System Model with
Feedback
Statistical Process
Control (SPC)
People
Product
Equipment
Materials
Methods
Environment
Manufacturing
Process
Customers
Identifying
changing
expectations;
direct feedback
on product quality
Inputs
Feedback from Customers
Goals of SPC

To achieve a state of statistical control (stability)

To maintain a state of statistical control (stability over
time; prevention verses detection)

To improve process capability
Statistical Process Control
 Taking action on the result of the output of a process
(traditional inspection techniques) permits waste –
rejected/reworked product, wasted resources,
potential for rejects to ‘escape’ the process
 Understanding the variation of the process and
applying statistical techniques allows for predictable
process output (capability)
 To do this, we need to understand the types of
variation present in the process
Statistical Process Control
 Machining process; part
dimensions vary from
each other
Size

If the output is stable (only
common cause variation),
the results form a pattern
that can be described as
distribution
Size
Statistical Process Control
 Common cause variation; inherent in the process –
backlash/clearances, coolant feed, machine tolerances
Special cause variation
(or assignable cause) –
machine set up, material
change, environment
Special Cause Variation
Target line
Predictable ?
Time
Size
If special causes of variation are present, the process output is not
stable over time and is not generally predictable; we cannot
always use sampling and SPC to control the process.
Common Cause Variation
Target line
Time
Size
If only common causes of variation are present, the output of
a process forms a distribution that is stable over time and is
predictable; we can then monitor the process using sampling
and SPC charts
Statistical Process Control
 _
 X – Range Control chart
(AIAG SPC manual)
General Rules for Interpretation
 A point outside a control limit
 7 points in a row on one side of the centreline
 6 points in a row steadily increasing or decreasing
 2 out of 3 points more than 2 standard deviations
from the centreline (same side)
 4 out of 5 points less than one standard deviation
from the centreline (same side)
Process Capability
 Capability indices are able to summarise process
performance as a number to reflect how well the process
will meet customer requirements (specification).
 They will indicate;
-
How variable the process is (i.e. spread of results)
-
Where the process output is in relation to
the specification limits.
Process Capability
Upper
specification
Lower
specification
Process variation
or spread
Tolerance
Capability Indices
 Process capabilities are an index produced by
comparing the observed process variation or spread
against the required tolerance. Examples include;
 Capability Index Cp = USL - LSL

6 δ (process variation)

_
_
 Capability Index Cpk = USL – x OR x - LSL
 (largest of)
3δ
3δ
 i.e. Worst case result
 Cpk will indicate the position of the process relative to
the specification (i.e. centering)
Capability Indices
 If the process data has a normal distribution, the
following can be used to interpret Cpk:
Cpk
Approximate proportion out of spec
1.33
63/1,000,000
1.67
0.6/1,000,000
2.0
0.02/1,000,000
(Where the process is centred between the specification limits)
Attribute Charting
 Attribute data is the result of inspection or testing that
produce a fixed result and cannot be measured using
measurement equipment e.g. number of paint defects
on a door panel, number of rejected units from a
functional test batch, number of weld failures on a
floor-pan assembly
 Attributes can also be monitored using control charts
with control limits to determine long term stability
What are the Benefits of SPC?
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Properly used, control charts and SPC can:
Distinguish special from the common causes of variation,
as an aid to improvement in capability
Enable the process perform consistently and predictably
Provide a common language for discussing the
performance of the process (capability indices)
Be used by employees for on-going control of a process
Measurement System Analysis (MSA)
 As measurement data is often used to make decisions with
regard to manufacturing (and test) activities then the ‘quality’
of this data needs to be assured
 No measurement system is ‘perfect’ (i.e. measures exactly with
reference to known standards each time); some variation will
be evident in all systems, including human influences
 A series of analytical techniques can be used to ensure that
the inherent variation in measurement systems can be
determined and the effects understood i.e. possibility for
accepting ‘bad’ parts and rejecting ‘good’ parts
 In essence, we need to understand the variation and
limitations of the measurement systems we are using to enable
confidence in those results (for equipment on the control
plan)
Measurement System Analysis
Variable Gauge R&R study
 Gauge repeatability and reproducibility data sheet used for the
numerical analysis of the study data (MSA software is also
available).
 10 parts used to represent variability of the process; 3 appraisers.
 Typically 3 trials per appraiser
 Complete the study using usual equipment and individuals
(random presentation of parts to avoid influence on the results)
Gauge R&R

Extract from the AIAG MSA manual
Variable Gauge R&R study
 The study estimates the variation and percentage
of process variation for the measurement system
(Gauge R&R) and its components

- Repeatability
- Reproducibility
- Part to part variation (how representative the
parts are; this will influence the results).
Gauge R&R
 Acceptable Gauge R&R% results;
 Up to 10% - generally acceptable
 10 to 30% - may be acceptable based on importance of
measurement feature, cost of better equipment, cost of
refurbishment/repair of equipment, OR the skill level
of the appraisers
 Over 30% - would be considered un-acceptable and
improvement is required
 Where results are not acceptable, check the data,
calculations etc. to determine if there are any errors
Use of Graphical Techniques
 There are many different methods for presenting data
for analysis
 ‘A picture paints a thousand words’.
 The AIAG MSA manual strongly recommends the use
of both calculated methods and graphical techniques.
 Other methods are available for specific situations and
where more detail is required – Analysis of Variance
(ANOVA), gauge performance curves, regression
analysis etc.
Attribute Studies
 Go/No-go gauging systems (acceptance gauging, gap
gauges etc.)
 A series of comparative techniques are available to
evaluate the effectiveness of attribute gauging systems,
again using several appraisers and trials
Product Part Approval Process
(PPAP)
 The intent of PPAP is to validate that products made
from production tools/processes meet engineering
requirements (specifications), that the processes are
capable (Cpk, SPC data) and are capable of producing
acceptable product consistently over time.
 The type and format of submission will depend on the
customer requirements, but the AIAG PPAP manual
has defined formats
PPAP
 To support this, appropriate data has to be completed
and be made available for review by the customer;
 Part Submission Warrant (PSW), DFMEA, PFMEA,
Control Plan, MSA data, initial process capability
results, material certification, marked up drawing/
dimensional results, engineering change documents,
material/performance test results, qualified laboratory
documentation, appearance approval report (if
applicable), sample product
 Approval may require full or partial submission of the
information (invariably depending on supplier
approval status) reviewed at the customer location or
supplier site
PPAP
 Acceptance of the PPAP detail is key for several
possible events;
 Authority to ship production parts
 Meeting customer timing requirements for the project
 Support the supplier approval rating (i.e. PSW
submission on time)
 Trigger tooling payments to the supplier (tooling will
typically be owned by the customer)
AUTOMOTIVE PROGRESS SINCE
1990
Best selling car in the UK 2012 (to date) Ford Fiesta
ex. Zetec 1.2 - £12495 OTR price – 3 year warranty,
plus breakdown cover – sold in EU & USA
Airbags x2, side airbags, knee airbag, anti-whiplash head restraints,
optional curtain airbags
ABS, brake force distribution, stability control, traction assist, auto brake
assist, auto hazard warning lights
High strength steels, active seat belts, anti-submarine seats, Halogen
projector head lights
Immobiliser/alarm, deadlock doors
Heated, electric remote door mirrors, auto wipers with rain sensor, alloy
wheels
Radio/CD,, AUX connection for phones, IPODs, A/C etc.
4 way adjustable front seats
Electronic power assist steering, advanced engines up to 85 mpg possible
with some models
Summary
 In truth, many factors have influenced the improvement
in product quality over the past 20 odd years, but the use
of APQP and core tools have provided a focus on
improved process capability and product quality/
reliability throughout the automotive supply chain.
 The aerospace industry are now utilizing many of these
tools to improve supplier performance
 Questions
 Thank you