managing business process flows: ch 9 six sigma quality 1 product quality and process capability ...

Managing Business Process Flows: Ch 9

Six Sigma Quality

1

Product Quality and Process Capability

Total Quality Management

The Quality Improvement Process

Quality Measurement and Analysis

Process Control and Capability

Quality by DesignCopyright © 2013 Pearson Education Inc. publishing as Prentice Hall

Quality Is

Recognized by a non-thinking process, and therefore cannot be defined - Zen and the Art of Motorcycle Maintenance, by R. M. Pirstig

That which makes anything such as it is - Dictionary Fitness for use - J. Juran and ASQ Conformance to requirements - P. Crosby Closeness to the target - deviations mean loss to the society

- G. Taguchi Providing full customer satisfaction at the most economical levels

- A. Feigenbaum Eight dimensional - Performance, Features, Conformance, Reliability,

Serviceability, Durability, Aesthetics, and Perception - D. Garvin

2Copyright © 2013 Pearson Education Inc. publishing as Prentice Hall

Quality and Capability

• Specifications • Design • Specifications • Features

• Control • Conformance • Performance

Process Capability

Product Quality

ProductDesign

Customer Needs

Ability to Satisfy Needs

ProcessDesign

SupplierSelection


Variation = Actual - Expected

Customer Needs - Product Design

Product Design - Process Capability

Process Capability - Process Performance

Process Performance - Product Performance

Product Performance - Customer Perception


Price – Quality Tradeoff

Dynamics of competition and rising customer expectations

Customer: Maximize Product Utility u (Q)subject to the budget constraint: P ≤ Band competing products available

Producer: Select a strategic position

Premium

Low ValueHigh Value

Budget

Price

Quality


Quality of Design

Design Quality

Value/Cost

Optimum


Quality of Conformance

Cost of Nonconformance(Internal + External)

Cost of Assurance(Appraisal + Prevention)

OptimumConformance Quality

Total Cost

$


Hank Kolb Case

Sources of the quality problem

– Supplier, equipment, worker,supervisor,...

Recommendations

– Short, medium, long term

Role of management– Systems

The quality culture– Values


The Total Quality Process

SupplierRelationshi

pPartnershipSelection

Communication

Cooperation

Material Procureme

ntQuality at

SourceLong

contracts Inspection Feedback

Process Planning

Defect Prevention

SimplifyMistake-proofRecruit, Train

Product Design

Build-in QualityJoint design

Robust designProducible

design

Customer Needs

Customer FocusContact

Expectations Competition

Process Control

Early Correction

Defect visibility Source

detection Local control

Product Delivery

Deliver QualityStore. Pack, Ship Install,

Instruct Interface,

Billing

Customer Experience

Follow ThroughProduct supportService

recovery Defect

analysis


The TQM Principles

Customer focus

Organization-wide involvement

Cross-functional communication

Local measurement and control

Mutual cooperation, commitment, trust

Continuous improvement

Long term Perspective


Malcolm Baldrige National Quality Award

Quality as a strategic concept Customer-driven quality Design quality - prevention Employee involvement, training Supplier quality Systems and processes - optimization Continuous improvement Management by fact and analysis Leadership, vision, values


ISO 9000

Series of standards agreed upon by the International Organization for Standardization (ISO)

Adopted in 1987

More than 100 countries

A prerequisite for global competition?

ISO 9000: “document what you do and then do as you documented.”

Design Procurement Production Final test Installation Servicing

ISO 9003

ISO 9002

ISO 900112Copyright © 2013 Pearson Education Inc. publishing as Prentice Hall

Quality Improvement Process

Measurement– Measure Variation

Analysis– Analyze Variation

Control– Control Variation

Improvement– Reduce Variation

Innovation– Redesign Product/Process

D

CA

P

D

CA

P

Control

Improve

Innovate

Improve


Importance of Metrics

“When you can measure what you are speaking about, and express it in numbers, you know something about it” - Lord Kelvin (1824-1907)

“Count what is countable, measure what is measurable, and what is not measurable, make measurable” - Galileo Galilei (1564-1642)

“Data! Data! Data! I can’t make bricks without clay” - Sherlock Holmes in The Adventure of Copper Beeches, by Sir Arthur Conan Doyle

“In God we trust, everyone else must bring data” - W. Edwards Deming


Type of Problem Number of Complaints

High Pressure

Low Pressure

Dents

Scratches

Labels

Check Sheet


Pareto Chart

0

5

10

15

20

25

Fre

qu

ency

High P Dent Low P

Type of Defect

The 80-20 Rule: Vital Few, Trivial Many


Cause - Effect Diagram

Equipment Material

Procedure Personnel

High PressureProblem

Nozzle

Vendor

Specifications

Lack of Training

Lack ofMaintenance

IncentivesDocumentation

Design

Feedback


Scatter Plot

Gas Injector Setting (psi)

Can Pressure (psi)


Histogram

0

2

4

6

8

10

12

14

16

Can Pressure (psi)

Fre

qu

ency

Specs

Mean = 82.5 psi, Standard Deviation = 4.2 psiFraction Defective = 26% (Theoretical = 30.1%)


Run Chart

70

75

80

85

90

95

Time

Can

Pre

ssur

e


Multi-Vari Chart

Variation Within / Between Days

70

75

80

85

90

95

Day

Pre

ssu

re (

psi

)

High

Average

Low


The Feedback Control Principle

Process

Disturbances Normal and Abnormal

Target Settings Performance

Decision Information


Time

Pro

ce

ss M

ea

su

re

Process Control Chart

Information: Monitor process variability over time Control Limits: Average + z Normal Variability Decision Rule: Ignore variability within limits as “normal”

Investigate variation outside as “abnormal” Errors: Type I - False alarm (unnecessary investigation)

Type II - Missed signal (to identify and correct)


X Bar Chart

Average X bar = 82.5 psi Standard Deviation of X bar = 1.6 psi Control Limits = Avg X bar + 3 Std of X bar

= 82.5 + (3)(1.6) = [77.7, 87.3] Process is “In Control” (i.e., the mean is stable)

76

78

80

82

84

86

1 3 5 7 9 11 13 15 17 19

Day

Avera

ge

UCL

LCL


Range (R) Chart

Average Range R = 10.1 psi Standard Deviation of Range = 3.5 psi Control Limits: 10.1 + (3)(3.5) = [0, 20.6] Process Is “In Control” (i.e., variation is stable)

05

101520

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

Day

Ran

ge

UCL

LCL


Number of Defects (c) Chart

Discrete Quality Measurement:D = Number of “defects” (errors) per unit of work

Examples: Number of typos/page, errors/thousand transactions,equipment breakdowns/shift, bags lost/thousand flown,power outages/year, customer complaints/month, defects/car.......

If n = No. of opportunities for defects to occur, and p = Probability of a defect/error occurrence in each

then D ~ Binomial (n, p) with mean np, variance np(1-p) Poisson (m) with m = mean = variance = np , if

n is large (≥ 20) and p is small (≤ 0.05)

With m = np = average number of defects per unit,Control limits = m + 3 √m


Performance Variation

Stable

Unstable

Trend

Cyclical

Shift27Copyright © 2013 Pearson Education Inc. publishing as Prentice Hall

Process Control and Improvement

LCL

UCL

Out of Control In Control Improved


Process Capability:

Ability to Meet Customer Requirements

Proportion of Output Within Specs: Given a Process in control with = 82.5 psi and = 4.2 psi P(Meet Specs) = 0.699

Shifting to 80 yields P(Meet Specs) = 0.766

Reducing to 2.5 yields P(Meet Specs) = 0.9544

LS US

LS US


Normal distribution => 99.73% of output falls in ( + 3)Cpk = Min[(US - ) / 3, ( - LS) / 3]

Ex. Can Pressure: Cpk = Min[0.1894, 0.5952] = 0.1984

With centered process: (US - = ( - LS)

Cp = (US - LS)/6] = Voice of the Customer

Voice of the Process

= 0.3968

Cp = 0.86 1 1.1 1.3 1.47 1.63 2.0

Defects = 10K 3K 1K 100 10 1ppm 2 ppb

Process Capability Ratio

LS US


Taguchi’s Quality Philosophy

Product / ProcessTarget Performance (T)

Actual Performance (P)

Design Parameters (D)

Noise Factors (N): Internal & External

LS T US P

LS Spec US

Loss = k(P - T)2

not 0 if within specsand 1 if outside

On Target is moreimportant than Within Specs


Robust Design

Identify Product/Process Design Parameters that– Have significant / little influence on performance– Minimize performance variation due to noise factors– Minimize the processing cost

Methodology: Statistical Design of Experiments Examples - Brownie mix, Ina Tile Co., TV

Product / ProcessTarget Performance (T)

Actual Performance (P)

Design Parameters (D)

Noise Factors (N): Internal & External


Design for Processing

Simplify – Fewer parts, steps– Modular design

Standardize – Less variety– Standard, proven parts, and procedures

Mistake-proof– Clear specs– Ease of assembly, disassembly, servicing


The Design Process

Goal – Develop high quality, low cost products, fast

Importance– 80% product cost, 70% quality, 65% success

Conventional – Technology-driven, Isolated, Sequential, Iterative

Difficulties – Revisions, cost overruns, delays, returns, recalls

Solution – Customer-driven, jointly planned, producible


Control, Capability and Design: Review

Every process displays variation in performance: normal or abnormal Do not tamper with a process that is “in control” with normal variation Correct an “out of control” process with abnormal variation Control charts monitor process to identify abnormal variation Control charts may cause false alarms (or missed signals) by mistaking normal

(abnormal) variation for abnormal (normal) variation Local control yields early detection and correction of abnormal variation Process “in control” indicates only its internal stability Process capability is its ability to meet external customer needs Improving process capability involves (a) changing the mean in the short run, and

(b) reducing normal variability in the long run, requiring investment Robust, simple, standard, mistake - proof design improves process capability Joint, early involvement in design by all improves product quality, speed, cost


Capability and Design: Review

Process capability measures its precision in meeting processing requirements Improving capability involves reducing variation and its impact on product

quality Simplicity, standardization, and mistake - proofing improve process capability Joint design and early involvement minimizes quality problems, delays, cost


All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying,

recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America.

Copyright © 2013 Pearson Education Inc. publishing as Prentice Hall

managing business process flows: ch 9 six sigma quality 1 product quality and process capability ...

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