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Automotive Core Tools 1

Automotive Core Tools Advanced Product Quality Planning (APQP)

Failure Mode and Effects Analysis (FMEA) Control Plan Production Part Approval Process ( P PA P )

Statistical Process Control (SPC) Measurement System Analysis (MSA) 2

Automotive Core Tools Examples: AIAG “Blue Book” Manuals

Automotive Core Tools Examples: Other Manuals

Core Tools in IATF 16949:2016

APQP: 8.3.2.1

FMEA: 8.3.2.1, 8.3.5.2 Control Plan: 8.5.1.1, Annex A

Product Approval Process (PPAP): 7.3.6.3 SPC: 9.1.1.2, 9.1.1.3 MSA: 7.1.5.1.1 5

APQP Advanced Product Quality Planning

APQP What is it? Management of product development

Why do we use it? To understand what our customer wants and fulfill those wants

Advanced Product Quality Planning CONCEPT INITIATION/ APPROVAL

PROGRAM APPROVAL

PROTOTYPE

PILOT

LAUNCH

PLANNING

PRODUCT DESIGN AND DEV. PROCESS DESIGN AND DEVELOPMENT PRODUCT & PROCESS VALIDA TION PRODUCTION FEEDBACK AS SESSMENT AND CO RRECTIVE ACTION

Planning INPUTS | Planning OUTPUTS

Product Design & Dev. INPUTS | Product Design & Dev. OUTPUTS

Process Design & Dev. INPUTS | Process Design & Dev. OUTPUTS

Product & Process Validation INPUTS | Product & Process Validation OUTPUTS

Feedback, Assessment & Corrective Action INPUTS | Feedback, Assessment & Corrective Action OUTPUTS

APQP Plan a n d D e fin e Ph a s e

Concept Initiation/Approval

Inputs: • Voice of the Customer • Market Research (Including OEM Vehicle Timing and Volume Expectations • Historical Warranty and Quality Information

• Team Experience • Business Plan/Marketing Strategy • Product/Process Benchmark Data • Product/Process Assumptions • Product Reliability Studies • Customer Inputs

APQP Plan a n d D e fin e Ph a s e

Concept Initiation/Approval

Outputs: • Design Goals • Reliability and Quality Goals • Preliminary Bill of Materials • Preliminary Process Flow Chart • Preliminary Listing of Special Product and Process Characteristics • Product Assurance Plan

• Management Support

APQP P r o d u c t D e s ig n a n d D e v e l o p m e n t Ph ase

Program Approval

Design Outputs:

APQP Outputs:

• Design Failure Mode and Effects Analysis (DFMEA)

• New Equipment, Tooling and Facilities Requirements

• Design for Manufacturability and Assembly

• Special Product and Process Characteristics

• Design Verification

• Gages / Testing Equipment Requirements

• Design Reviews • Prototype Build — Control Plan

• Team Feasibility Commitment & Management Support

• Engineering Drawings (Including Math Data) • Engineering Specifications • Material Specifications • Drawing and Specification Changes 13

APQP P r o c e s s D e s ig n a n d D e v e l o p m e n t Ph a s e

Prototype

Outputs: • Packaging Standards and Specifications

• Product/Process Quality System Review • Process Flow Chart • Floor Plan Layout

• Process Failure Mode and Effects Analysis (PFMEA) • Characteristics Matrix • Pre-Launch Control Plan

• Process Instructions • Measurement System Analysis Plan • Management Support

• Preliminary Process Capability Study Plan 14

APQP P r o d u c t a n d P r o c e s s Va l i d a t i o n Ph a s e

Pilot

Outputs: • Significant Production Run • Measurement Systems Evaluation • Preliminary Process Capability Study • Production Part Approval • Production Validation Testing • Packaging Evaluation • Production Control Plan • Quality Planning Sign-Off and Management Support

APQP F e e d b a c k , A s s e s s m e n t a n d C o r r e c t i v e A c t i o n Ph a s e

Launch

Outputs: • Reduced Variation • Improved Customer Satisfaction • Improved Delivery and Service

• Effective Use of Lessons Learned/Best Practice

ADVANCED PRODUCT QUALITY PLANNING

Pitfalls • APQP treated as a “Quality Department Responsibility” • APQP a separate process, not integrated into product development • Key stakeholders brought in late (quality, production, suppliers) • Milestones and deliverables ignored • No top management involvement/support

FMEA Failure Mode and Effects Analysis

FMEA What is it? A risk analysis of a part or process Why do we use it?

To find and fix a problem before something breaks or someone gets hurt

Types of FMEAs

Design FMEA Process FMEA

Types of FMEAs Others: System FMEA Concept FMEA Environmental FMEA Machinery FMEA Software FMEA

FMEA Process Subsystem

Function Requirements

Potential Failure Mode

Potential Effect(s) of Failure

What are the Effects?

C Potential O S l Cause(s)/ c e a Mechanism(s) c v s of Failure u s r

D e

Current Controls Prevention

Detection

e c

R. Recommended t Responsibility & Target P. Action(s) N. Completion Date

What can be done?

How bad is it?

–Design Changes

What are the Functions, Features or Requirements?

– Process Changes – Special Controls

What can go wrong?

What are the Cause(s)?

– Changes to Standards, Procedures, or guides

How often does it happen?

–No function – Partial / Over /Degraded Function – Intermittent Function

How can this be prevented and detected?

– Unintended Function

How good is this method at detecting it?

Action Results Actions S O D R. Taken e c e P. v c t N.

Risk Action Strategies

1st Priority is Severity. Severity has a direct impact on the customer. 2nd Priority is Criticality (Severity times Occurrence: S x O). Criticality evaluates the risk that an event with a high impact on the customer

will occur. 3rd Priority is RPN. RPN evaluates the ability to detect and contain poor quality.

Failure Mode and Effects Analysis

Pitfalls • FMEA started late in the development process (just in time for PPAP!) • FMEA never updated after release • FMEA not updated from nonconformity corrective actions • Right side (action area) is blank • RPN thresholds • FMEA written by one person • FMEA treated as a “Quality Department Responsibility”

Control Plan

Control Plan What is it? A summary of controls used to make sure my customer gets good product

Why do we use it? To make sure controls are used and stay in place

Control Plan CONTROLPLAN Prototype Control Plan Number

Pre-Launch

Production Key Contact/Phone

Date (Orig.)

Date (Rev.)

Part Number/Latest Change Level

Core Team

Customer Engineering Approval/Date (If Req’d.)

Part Name/Description

Supplier/Plant Approval/Date

Customer Quality Approval/Date (If Req’d.)

Other Approval/Date (If Req’d.)

Supplier/Plant

Supplier Code

MACHINE, PART/ PROCESSNAME/ DEVICE, JIG,TOOLS, PROCESS OPERATION FOR MFG. NUMBER DESCRIPTION

CHARACTERISTICS NO.

METHODS SPECIAL CHAR. PRODUCT/PROCESS EVALUATION/ SAMPLE SPECIFICATION/ MEASUREMENT CLASS SIZE FREQ. PRODUCT PROCESS TOLERANCE TECHNIQUE

CONTROL METHOD

REACTION PLAN

Control Plan Elements IATF 16949 Annex A A.2 Elements of the control plan The organization shall develop a control plan that includes, as a minimum, the following contents. a) General data ⎯control plan number,

c) Process control

⎯ issue date and revision date, if any,

⎯ process parameters,

⎯ customer information (see customer requirements),

⎯ process-related special characteristics,

⎯ organization’s name/site designation,

⎯ machines, jigs, fixtures, tools for manufacturing.

⎯ part number(s),

d) Methods

⎯ part name/description,

⎯ evaluation measurement technique,

⎯ engineering change level,

⎯ error-proofing,

⎯ phase covered (prototype, pre-launch, production),

⎯ sample size and frequency,

⎯ key contact,

⎯ control method.

⎯ part/process step number, ⎯ process name/operation description.

e) Reaction plan and corrective actions

b) Product control

⎯ corrective action.

⎯ reaction plan (include or reference),

⎯ product-related special characteristics, ⎯ other characteristics for control (number, product or process), ⎯ specification/tolerance.

Control Plan

Pitfalls • Control plan and PFMEA not aligned • Control plan and operator instructions not aligned • Control plan out of date • Control plan not updated from nonconformity corrective actions

PPAP Production Part Approval Process

PPAP What is it? Requirements for approval of production parts. Why do we use it? To make sure that I understand all my customer requirements, and that I can meet them under actual production conditions.

PPAP 1

Design Records

Authorized Engineering Change Documents

Customer Engineering Approval

Design FMEA

Process Flow Diagrams

Process FMEA

Control Plan

8 9 10

Measurement System Analysis Studies Dimensional Results

Initial Process Study

Qualified Laboratory Documentation

Appearance Approval Report

Sample Production Parts

Master Samples

Checking Aids

Customer-Specific Requirements (Records)

Part Submission Warrant Bulk Material Requirements Checklist

Material / Performance Test Results

Production Part Approval Process

Pitfalls • PPAP is treated as a separate process, rather than integrated into product development • Incomplete PPAP • Assuming that submission levels are what’s required, rather than what’s submitted

SPC Statistical Process Control

SPC What is it? A collection of statistical methods, especially control charts, used to analyze and control a process

Why do we use it? To know when processes change and respond accordingly 37

Variation

Distributions can vary in Location Location (Center): 3 key measures

Mean = Average or

Median = Middle (by count)

Mode = Most often

Distributions can vary in Spread

Spread: 3 key measures Range = R

 or s

Standard Deviation =

Variance =



Distributions can vary in Shape

Normal Distribution 68.25%

95.46%

99.73%

 3

 2





2

3

Control vs. Capability

C o m m o n a n d S p e c i a l C a u s es

If only common causes of variation are present, the output of a process forms a distribution that is stable over time and is predictable If special causes of variation are present, the process output is not stable over time

Control vs. Capability

Statistical Control

Variation

In- Control

Out-of-Control

(Common Cause)

(Special Cause)

Acceptable

Case 1

Case 3

Unacceptable

Case 2

Case 4

(Capability)

Cp, Cpk, Pp & Ppk

Cp / Pp: can the car fit into the garage?

Cpk / Ppk: does the car fit into the garage?

Measures of Process Capability (Capability Index)

Overall Variation

Within Subgroup Variation

Overall Variation

Within Subgroup Variation

Overall

Within

if stable

Performance

Capability If centered

Ppk

Cpk

Kenneth J Kortge 45

Capability Metrics – Acceptance Criteria Typical:

Index  1.67

Acceptable

1.33 ≤ Index ≤ 1.67

May Be Acceptable May require an improvement plan

Index  1.33

Not Acceptable

2 Types of Data

Va r i a b l e

Attribute 47

Variables Charts Typical: Chart Type

X-Bar & R

Median

Individual & Moving Range (MR)

Primary Usage

Routine monitoring of manufacturing processes

Usually used as a monitoring tool for product or processes

Used when only one sample is possible

What Is Charted

Plots the average size and the range of the part sizes

Plots the individual sizes of the parts and the median of the part sizes

Plots the sample size and the moving range of the sample size

Sample Subgroup Size

Usually 3 to 6

Should be an odd number: 3, 5, 7, etc.

One

Attribute Charts Typical: Chart Type

P Chart

nP Chart

C Chart

U Chart

Primary Usage

Used for analyzing proportion or percent nonconforming or defective parts

Used for analyzing the number nonconforming or defective parts

Used for analyzing nonconformities or defects

Used for analyzing nonconformities per unit

What is Charted

Plots the proportion or percent of the nonconforming units

Plots the number of nonconforming items

Plots the count of all nonconformities found in the sample

Plots the average number of nonconformities in each sample

Sample Subgroup Size

Variable

Fixed

Variable

X & R Chart

How Control Charts Work UCLX

•

• •

•

• •

•

LCLX

•

Special Cause Criteria

1. Most measurements cluster around the center (average) line

2. A few measurements approach the edges (control limits) 3. No measurements outside the control limits 4. Same number of measurements on both sides of the center (mirror image) 5. Random (no patterns)

Statistical Process Control

Pitfalls • Ignoring out of control conditions • Comparing control limits to spec limits • Making process adjustments without understanding the source of the special cause variation • Putting SPC charts on everything

MSA Measurement Systems Analysis 55

MSA What is it? A collection of statistical methods used to assess how much I can trust the information from a gauge Why do we use it? Since all my information about a part/process comes from gauges, I need to know when the gauge information is dependable, and do something when it’s not 56

Bias: difference between the measurement and the “true” value

Stability: change in bias over time

Linearity: change in bias across expected range of measurements

Note that unacceptable linearity can happen in a variety of ways. Do not assume a constant bias.

Gage Repeatability and Reproducibility = GRR = R&R Variable, replicable measurements

Typical:

10 Parts 3 Appraisers 3 Trials

GRR / R&R

2  GRR =

2  Reproducibility 2  + Repeatability % Total Variation vs. % Tolerance Number of Distinct Categories (NDC) 61

Repeatability: gage-induced variation

Appraiser A

Repeatability

Reproducibility: operator-induced variation

Reproducibility

Appraiser

The Effect of Measurement Error “Observed”

“Actual”

Total Variation = Process Variation + Measurement Variation



Total

=  Process + 

2 Measurement

Think of a right triangle Measurement Variation

Process Variation Kenneth J Kortge 64

The Effect of Measurement Error Total Variation = Process Variation + Measurement Variation



2 Total

=

2 Process +



2 Measurement

Measurement Variation

What You Want to Know Kenneth J Kortge 65

Gage R&R Acceptance Criteria (Typical) % R&R Under 10% error – Acceptable 10% – 30% error – May be acceptable based upon importance of application, cost of measurement device, cost of repair, etc. Over 30% error – Not Acceptable. Every effort should be made to improve the measurement system

Number of Distinct Categories (NDC): Greater than or equal to 5 – Acceptable Less than 5 – Generally Not Acceptable

Measurement Systems Analysis Pitfalls • Using MSA to obtain a number, rather than to understand gage variation • Not documenting a conclusion and any actions needed, as part of the study • Not conducting MSA for all gages on the control plan (IATF 16949 requirement) • Not validating Software (IATF 16949 requirement) • Using wrong analysis method (non-replicable, attribute, etc.)

Automotive Core Tools Advanced Product Quality Planning (APQP)

Failure Mode and Effects Analysis (FMEA) Control Plan Production Part Approval Process ( P PA P )

Statistical Process Control (SPC) Measurement System Analysis (MSA) ASQ Automotive Division

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