AUTOMOTIVE CORE TOOLS;

SPC, MSA, FMEA, APQP/CONTROL PLAN

CQI Wessex - 11 December 2012John 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), 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/TS16949Initiated 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 REQUIREMENTSAPQP; Advanced Product Quality PlanningFMEA; Failure Mode & Effect AnalysisControl PlanSPC; Statistical Process ControlMSA; Measurement System AnalysisThese require a team approach (cross functional

teams with management commitment)Automotive Industry Action Group (AIAG) manuals

define basic requirements for applicationThere 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?

Product Quality Planning Timing Chart

Planning

Product design

Validation

Production

Process design

Feedback assessment & corrective action

Planning

Concept Initiation/Approval Program

Approval Prototype LaunchPilot

Plan & Define Programme

Product Design & DevelopmentVerification

Product & Process Validation

Feedback Assessment & Corrective Action

APQP – Project Scope2011 model year Range Rover – minor

changes

APQP – Project Scope2012/13 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)

Advantages;Thorough planning and improved decision makingShorter development timescalesSimultaneous engineering (design & manufacturing)Early procurement of long lead time tooling/facilitiesDefined objectives, measured as project stages are

achievedDefined project gateways, with key deliverablesImproved use of resourcesSignificant 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 processd)Needs a ‘team approach’ to be successful

DFMEA

DFMEA

DFMEA

DFMEAIgnores manufacturing issues; i.e. manufacturing

producing/using parts that are to specificationCan 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

PFMEAA 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

PFMEAFocuses on potential for non-conforming product (in

use 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 characteristicsContinual improvementAssumes product as designed will meet intentShould be extended to other areas; receiving,

storage, transport, despatch etc. (complete process)Provide feedback to design (mistake proofing

features etc.)

Control PlanA documented description of the systems and

processes required for controlling productThis is a key output once the DFMEA and

PFMEA analysis has been completedApplies 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 PlanControl Plan            Part #:   N/A Prepared By: xxxx    

Part Name/Description: Wheel Hub / new design Core Team:

xxx, xxx, aaa, bbb, ccc   Notes:  

Latest Change Level: #REF! Supplier/Plant App./Date:     Production Control Plan

Vendor ID:   #REF! Other Approval/Date:    

    #REF! Supplier Plant/Code:        

                 

Oper. # Process Description Machine/Device/Jig/Tools Characteristics CC    

      Item# Product Process SC Process/Pdt. Spec./Tolerance G.ID

                 70 OP 70; Finish

machine bearing bores (CNC)

XXX CNC machining centre

  Bearing Inner Bore diameter

Finish machine; 25mm/min, CBN tip (XYZ)

CC 75 +0.008 -0.000 mm0.003 mm run out max

In cycle gauging.

                 

                                  

Control Plan  Date (Original): xxxxx

  Customer Engg. Appr./Date (Opt):  

  Cust. Quality Appr./Date (Opt):  

  Other Approval/Date (Optional):  

  Control Plan No.: CP001

           

Methods          

Eval. Mst. Technique Sample Size Sample Frequency Control Method Reaction Plan  

         In cycle gauging. 100% 100%Machine control

dataloggerLock out; setter informed, machine checked and re-set. Suspect material quarantined; (Corrective Action Report - CAR)

         

                  

Control PlanIdentifies 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 ControlTraditional 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

ManufacturingProcess

People

Equipment

Materials

Methods

Environment

Statistical Process Control (SPC)

Customers

Identifying changing

expectations; direct feedback

on product quality

Product

Feedback from CustomersInputs

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 ControlTaking 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

Machining process; part dimensions vary from each other

Statistical Process Control

If the output is stable (only common cause variation), the results form a pattern that can be described as distribution

Size

Size

Statistical Process ControlCommon 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

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.

Size

Target line

Time

Predictable ?

Common Cause Variation

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

Size

Target line

Time

Statistical Process Control

_ X – Range Control chart (AIAG SPC manual)

A point outside a control limit7 points in a row on one side of the

centreline 6 points in a row steadily increasing or

decreasing2 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)

General Rules for Interpretation

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

Process CapabilityLower

specificationUpper specification

Process variation or spread

Tolerance

Capability IndicesProcess 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) 3 δ 3 δ

i.e. Worst case resultCpk will indicate the position of the process relative

to the specification (i.e. centering)

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)

Capability Indices

Attribute ChartingAttribute 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? 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

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)

Variable Gauge R&R study

Extract from the AIAG MSA manual

Gauge R&R

Variable Gauge R&R studyThe 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&RAcceptable Gauge R&R% results;

Up to 10% - generally acceptable10 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

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.

Use of Graphical Techniques

Attribute StudiesGo/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

PPAPTo 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

PPAPAcceptance of the PPAP detail is key for

several possible events;

Authority to ship production partsMeeting customer timing requirements for

the projectSupport 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

Airbags x2, side airbags, knee airbag, anti-whiplash head restraints, optional curtain airbagsABS, brake force distribution, stability control, traction assist, auto brake assist, auto hazard warning lightsHigh strength steels, active seat belts, anti-submarine seats, Halogen projector head lightsImmobiliser/alarm, deadlock doorsHeated, electric remote door mirrors, auto wipers with rain sensor, alloy wheelsRadio/CD,, AUX connection for phones, IPODs, A/C etc.4 way adjustable front seatsElectronic power assist steering, advanced engines up to 85 mpg possible with some models

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

SummaryIn 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