six sigma for non normal processes: a case...

Copyright@ 2017 Global Lead Consultants

Six Sigma for Non NormalProcesses: A Case Study

Global Lead Consultants

Prof. Tariq A. AldowaisanFounder & GM, Global Lead ConsultantsASQ CMQ/OE, CSSBB, CQE, CQABCSP ASP, CSP, CET

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28 Sept. 2017


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“Quality has to be_________ not controlled.”

____ Phil Crosby


Bio• Bachelor, Master, & Ph.D. from Arizona State University, USA• Founder and General Manager, GLC• Professor of Industrial & Management Systems Engineering.• KFAS Prize Winner Scientific Production in EngineeringSciences in 2014• Holds Quality Certifications: ASQ CMQ/OE, CSSBB, CQE, CQA,CSQP• Holds Safety Certifications: BCSP ASP, CSP, & CET• Consults and trains in quality, organizational excellence, andsafety

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[email protected]

Copyright@ 2017 Global Lead Consultants4

Quality

Six Sigma

Six Sigma Performance

Case Example: Normal Six Sigma

Case Study: Non Normal Six Sigma

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Quality is ….

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Customer _______________________


Quality Starts and Ends with … Customer

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• Quality starts with identifying___________________

• Translating these customer needsinto technical features on theproducts and servicesThen• Producing the products andservices according to the specifiedfeatures, and• Quality ends with achieving_____________________.

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The Three Principles of Quality• Customer Driven• Process focus• Variation focus

A1A1 A2A2

A3A3

A4A4

A5A5

Output/PerformanceOrder Fulfilment

Process

38 Days Defective

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The Quality Trilogy & SS• Quality Planning … Set the _____________• Quality Control … Maintain _____________ to standard• Quality Improvement … Challenge _____________ & _____________

A1A1 A2A2

A3A3

A4A4

A5A5

Output/PerformanceOrder Fulfilment

Process

38 Days Defective

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3


• ______________ reduction• ______________ reduction

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A1A1 A2A2

A3A3

A4A4

A5A5

Cycle TimeOrder FulfilmentProcess

38 days Defective

Strategies of Performance Improvement


Lean … Issuing Commercial Licenses

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4


LSS … Canvas!

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Inputs(Resources)Inputs(Resources)ProcessEffectEffectImpactImpact OutputOutputEfficiencyEfficiency

ProductivityProductivity

QualityQualityCustomer

Vision &Strategic

Objectives Effectiveness

Effectiveness


LSS & KPIs

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Inputs(Resources)Inputs(Resources)ProcessEffectEffectImpactImpact OutputOutputEfficiencyEfficiency

ProductivityProductivity

QualityQualityCustomer

Vision &Strategic

Objectives Effectiveness

Effectiveness =

==

= 1

5


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“Six Sigma is a ___________program that when all issaid and done, improvesyour customers’ experience,lowers your costs, andbuilds better leaders.”

____ Jack Welch,Former CEO of GE


Elements of LSS Project

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Customer Delight

Company-WideTraining (Belts)Company-WideTraining (Belts)

StatisticsStatistics

ProjectManagement

ProjectManagement

TeamworkTeamwork

Lean & QualityTools (Waste &

Variation)

Lean & QualityTools (Waste &

Variation)

To some, what matters is the __________________; to others it is the_________________. In my opinion, it should be _______

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LSS & Business CustomerDelightQuality of

DesignQuality of

Conformance

__________________________________________

Right Product/Service Features Product/ ServiceFree of Deficiencies

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Variation and the Meaning of SSProcess Cycle Time

38 Days

Defective

Request fulfil

Good operation … 27 defects per 10,000 (3 Sigma)Excellent operation … 3.4 defects per 1,000,000 (6 Sigma lenient)

Ideal operation … 2 defects per 1,000,000,000 (6 Sigma strict)

A1A1 A2A2

A3A3

A4A4

A5A5

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7


Why LSS Works?1. ________________ results2. __________ management is involved3. A _______________ approach; DMAIC4. ________ project completion times 3 to 6 months5. _________ defined measures of success6. Infrastructure of ___________ individuals; belts7. Focus on _____________ and ___________8. Use of a sound ______________ approach17


Case Example: Six Sigma Normal• The standard of a copper cylinder diameter is_________________• The supervisor wanted to check preliminarily on thequality of production; so he examined the diametersof the last 10 produced items (last two decimals).

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13162522162216191720

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Case Example: Dot Diagram• The supervisor drew the Dot Diagram for the diametervalues as follows:

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14 16 18 20 22 24 26

2.262.202.1413162522162216191720


Measures of Centrality: Mean, Median, Mode

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The sample mean ( ̅) isa. the middle value in an ordered data. For even data set,the median is the average of the two middle values.b. the maximum value in a data set.c. the most widely used measure for central tendency. It isthe arithmetic average. It is the sum of all data valuesdivided by the number of data points. It is an estimate ofthe population mean .d. the most frequently occurring number in the data set. Adata set may have more than one mode.

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Case Example: Mean & Accuracy ̅ = ∑

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• The mean ( ̅) = _____________• Show the mean on the dot diagram• Accuracy = |Mean – Target|= |______ - ______| = ____________• Mode = ____________• Median = __________

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2.262.202.1413162522162216191720


Measures of Dispersion

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The sample standard deviation SD ( ) isa. the difference between the largest and smallestvalues in a data set.b. the most widely used measure for analyzingdispersion. It measures the average deviations fromthe mean. It estimates the population standarddeviation .c. the standard deviation squared.d. the standard deviation divided by the meanexpressed as a percentage.

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Case Example: SD & Precision

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= ∑( ̅)• The SD ( ) = _____________• Show the SD on the dot diagram.• Precision = SD = _____________• S2 = ______________• R = ___________• CV = _________

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2.262.202.1413162522162216191720


Case Example: Current Sigma Performance

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• The process quality is determined by the mean and SD.Process quality improves when:• the mean gets ___________ to the target• the standard deviation ____________

• In our example, the Sigma of our process is _____________

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2.262.202.1413162522162216191720

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SS Sigma Level Metrics

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• In SS, the process sigma level is calculated for ideal (i.e. noshift) and Motorola (i.e. 1.5 shift allowance) methods.• Motorola approximation:Sigma Level = 0.8406 + 29.37 − 2.221 ln( )• What is the sigma level of a process with a yield of 99.9930%?

Sigma Level ppm (ideal) ppm (Motorola)

1 Sigma 317,300 697,700

2 Sigma 45,500 208,700

3 Sigma 2,700 66,810

4 Sigma 63 6,210

5 Sigma 0.057 233

6 Sigma 0.002 3.4

= P(defect) = _________= Sigma Level= ____________


Process Accuracy & Precision

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12


Process Accuracy & Precision

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Process Improvement Strategiescurrent

desired

currentdesired

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13


Case Example: Sigma PerformanceImprovement

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• Assume a six sigma team studied the process of makingcopper rods over a 4-month period. They were able toimprove the extrusion process and the multiple formingdies.• This lead to reducing the sigma to half.

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2.262.202.14

0.037


Case Example: Sigma PerformanceImprovement

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• The production manager was pleased with the newperformance; however, he asked the team to improve further.So, the team – after further analysis – managed to fix therotating spindle so it doesn’t deviate during the drawingprocess.• This lead to moving the process mean closer to the nominalvalue.

14 16 18 20 22 24 26

2.262.202.14

0.0175

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What Sigma is Your Process?

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382614


Case Study: Research of SS Performance of NonNormal Processes

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How significant is the assumption of normality when the process isnot normal?Is the effort to achieve the six sigma goal of 3.4 ppm for a non-normal process the same as that of a normal?How does a non-normal process affect the 6 Sigma methodology?Research Team• Prof. Tariq A. Aldowaisan, Global Lead Consultants• Prof. Mustapha Nourelfath, Laval University, Canada• Dr. Jawad Hassan, Kuwait University

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Case Study: OFI

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38 Days

Requestfulfil

Good operation … 27 defects per 10,000 (3 Sigma)Excellent operation … 3.4 defects per 1,000,000 (4.5/6 Sigma)

Ideal operation … 2 defects per 1,000,000,000 (6 Sigma)


Case Study: RFQ Process

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• One-Sided (upper) Specification• Not-Normal

Defective

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Case Study: RFQ Process

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150100500

99.99

99

90

50

10

1

0.01

CT - T =38

Pe

rce

nt

10001001010.10.010.001

99.99

90

50

10

1

0.01

CT - T =38

Pe

rce

nt

1001010.1

99.99

90

50

10

1

0.01

CT - T =38

Pe

rce

nt

1001010.1

99.99

9990

50

10

1

0.01

CT - T =38

Pe

rce

nt

WeibullA D = 5.128P-V alue < 0.010

GammaA D = 2.058P-V alue < 0.005

Goodness of F it Test

NormalA D = 31.964P-V alue < 0.005

ExponentialA D = 114.791P-V alue < 0.003

Probability Plot for CT - T=38Normal - 95% C I Exponential - 95% C I

Weibull - 95% C I Gamma - 95% C I


Case Study: How Significant is the NormalityAssumption?

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1E-10

1E-08

0.000001

0.0001

0.01

1

100

10000

1000000

0 1 2 3 4 5 6 7 8 9 10

Fallo

ut R

ate

k

normal exponential

k (days) Normal (ppm) Exponential (ppm)

1 15 317,311 135,335

2 7.5 45,500 18,316

3 5 2,700 2,479

4 3.75 63.34 335.5

5 3 0.573 45.4

6 2.5 0.002 6.144

7 2.143 2.56E-6 0.832

8 1.875 1.33E-9 0.113

9 1.667 0 0.015

10 1.5 0 0.002

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Case Study: Flowcharting RFQ Process

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Case Study: The RFQ Milestones

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RFQ Process MilestonesNon-spareUp to 5K

Non-Spare5K – 30K

SpareUp to 5K

Spare5K – 30K

1 Time to issue RFQ 4 4 4 42 Time to bids’ closing date 14 14 14 143 Time to extended closing date 0 0 14 144 Time to evaluate bids 15 15 15 155 Time to prepare final recommendations 4 4 4 46 Time to Award 1 8 1 8

Cycle Time Deadline (Days) 38 45 52 59

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Case Study: Process Analysis

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Case Study: Root Cause Analysis

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1

1

1

1

1

1

3

5

7

15

22

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DELAY DUE TO LOW VALUE (LESS THAN KD.500/-)

DELAY DUE TO MISSING DOCUMENTS

DELAY DUE TO NEED FOR OFFER REVIEW BY MULTIPLE DIVISIONS

DELAY DUE TO NO OFFER RECEIVED (HENCE EXTENDING CLOSING DATE)

DELAY IN OPENING BIDS (SENIOR/ BUYER)

DELAY RFQ PROCESSING (BY BUYERS)

DELAY DUE TO MANY OFFERS/DOCUMENTS FOR REVIEW AND FINALIZATION

DELAY TO PRICE NEGOTIATIONS

DELAY DUE TO CATALOG ENGINEER /USER IN GIVING FINAL COMMENTS

DELAY DUE TO REQUESTING TECHNICAL CLARIFICATIONS FROM VENDORS

USER/CAT.ENGR DELAY PROVIDING CLARIFICATIONS

DELAY BY VENDORS PROVIDING CLARIFICATIONS

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Case Study:ImprovementMethodology

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Case Study: Standard & Deadline

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Determine CT deadline based on CT standard and benchmarks, if availableDetermine CT deadline based on CT standard and benchmarks, if availableDetermine CT standard using scientific methodDetermine CT standard using scientific methodDetermine performance zones based on CT standard and deadlineDetermine performance zones based on CT standard and deadlineRevise BSC on RFQ Completed on time (%), where SMG is at 99.73% (i.e. 3)Revise BSC on RFQ Completed on time (%), where SMG is at 99.73% (i.e. 3)

DeadlineStandard

Zone A Zone B Zone C

2700 ppm680,000 ppm

270,000ppm

47,300ppm

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Case Study: Research of SS Performance of NonNormal Processes

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How significant is the assumption of normality when the process isnot normal?Is the effort to achieve the six sigma goal of 3.4 ppm for a non-normal process the same as that of a normal?How does a non-normal process affect the 6 Sigma methodology?Title Journal Status

1. Six Sigma Performance for Non-NormalProcesses

European Journal of OperationsResearch (EJOR)

Published2015

2. Evaluating Six Sigma failure rate forinverse Gaussian cycle times

International Journal of ProductionResearch (IJPR)

Published2016

3. Six Sigma for Gamma-Distributed ProcessCycle time

International Journal of Quality &Reliability Management (IJQRM)

Accepted2017

six sigma for non normal processes: a case...

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