8 Quality Management Dummies

7/23/2019 8 Quality Management Dummies

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8 - PROJECT QUALITY MANAGEMENT

A. BASIC QUALITY CONCEPTS

Quality

Management• Integrated with Collect Requirements and Planning Stakeholder

Management

Quality • Must be planned, designed, and built in

Customer

Satisfaction• Focus of Quality Management

• Conformance to requirements and tness for use.

•

roduct, rocess, and ro!ect meet the "equirements and #nd$result isuse and usefulroduct Satisfaction • Focus is on the Customer

ro!ect Satisfaction • Focus is on the Sta%eholder and not !ust customer

Continuous

Impro&ement• art of Quality Management 'for Product and Project Quality (

Quality

Impro&ement• lan$)o$Chec%$*ct Style by +alter Shewhart and . #dwards )emings

'-/0s(

• PLAN 1 establish the new ob!ecti&es and processes to deli&er e2pected

results

• DO 1 implement the processes

• CHECK 1 measure the new processes and compare the results against

e2pected results• ACT$ *naly3e the di4erences to determine the cause

Quality 5heorists • oseph uran 1 60780 principle. Quality as tness for use.

• +.#dwards )eming 1 -9 points to 5QM and lan$)o$chec% *ct for basis of

Quality Impro&ement

• hilip Crosby 1 Cost of oor Quality and :ero )efects and re&ention o&er

Inspection. Quality is conformance to requirements

B. BASIC STATISTICS

robability

)istribution• ;i%elihood of di4erent outcomes from a chance e&ent

<ormal

)istribution

• Bell-shape !s"#!$%"!&'(Ga%ss!a' !s"#!$%"!&'

• Mean, median, mode are the same &alue

Cumulati&e

)istribution• Show the probability that a gi&en &alue and less 'or more( will be

achie&ed

Mean • Expected value

• *&erage of all data points

• May be computed as simple a&erage or weighted a&erage

• Shows the height o the curve

Median • oint in the distribution where /0= of the results are abo&e the &alue and

/0= of the results are below the &alue

Mode • Most frequent data point

5riangular

)istribution

• Calculated by > discrete &ariables 'optimistic, pessimistic, most li%ely(

• <ot weighted in calculating the mean• )&#*%la

Op"!*!s"!+ , M&s" L!el , Pess!*!s"!+

/

#"5 )istribution • )&#*%la

Op"!*!s"!+ , 0 M&s" L!el , Pess!*!s"!+

1Standard )e&iation • Measure of the range of outcomes, the a&erage di4erence from the

mean, calculated as the square root of the &ariance 'symbol is 2(

• )&#*%la 3&# N&#*al D!s"#!$%"!&'

4Pess!*!s"!+ 5 Op"!*!s"!+6



1

• !etermines the width o the curve

M#5"IC • Measurement or denition describing what something is and how it will

be measured

C. )OR THE E7AM

• )istinction between the QUALITY and GRADE

QUALITY • !egree to which the pro!ect fullls requirements

GRADE • Category or rank used to distinguish items ha&e the samefunctional use but do not share the same requirements for quality

• )istinction between the ACCURACY and PRECISION

ACCURACY • *ssessment of correctness

PRECISION • *ssessment of exactness

• )istinction between the TQM and CQI

TOTAL QUALITY

MANAGEMENT 4TQM6• ractice focuses on organi"ations always looking or ways to

improve the quality o their products and processesCONTINOUS QUALITY

IMPROEMENT 4CQI6

• Focuses on continuous incremental improvements

•

?ai3en, apanese for impro&ement

• @ased on <A"M*; )istribution. Bou are loo%ing for mean and the standard de&iation.

• *ll &alues lie within > standard de&iations of the mean

<A"M*; )IS5"I@5IA< Measurements are assessed by the number of the standard de&iations

from the mean.

D6.>= of the data points fall within - standard de&iation

/./= of the data points fall within 8 standard de&iations

.E= of the data points fall within > standard de&iations

# $atter distri%ution has relatively greater standard deviationCUMULATIE

DISTRIBUTION

0.-/= of the data points fall between 0 and > from the mean

8.8/= of the data points fall between 0 and $8 from the mean

-D= of the data points fall between 0 and $- from the mean

69= of the data points fall between 0 and G- from the mean

E.E/= of the data points fall between 0 and G8 from the mean

.6/= of the data points fall between 0 and G> from the mean

D. S!"%a"!&'

* team member estimates that 5as% * will most li%ely be nished in >0 days.

@est case scenario is that it could be nished in 89 days

+orst case scenario is >D days.

Bou would li%e estimates for e2pected completion.

Q%es"!&'9 :ha" !s "he p#&$a$!l!" "ha" &% ;!ll <'!sh "he "as !' =8-/= as>S&l%"!&'9

?. Calculate the mean 'e2pected &alue( using #"5 distribution equation

Op"!*!s"!+ , 0 M&s" L!el , Pess!*!s"!+

1

@ =0 , 0 4/6 , /1

1

@ /

=. Calculate the standard de&iation using the short formula

4Pess!*!s"!+ 5 Op"!*!s"!+6

1



@ /1 5 =0

1

@ =

/. A a' s%$"#a+" "he s"a'a# e!a"!&' al%e "& a' 3#&* "he *ea'

,(-?2 !s =8 5 /= as ;h!+h #ep#ese'"s 18

Chance that the acti&ity will be nished within 86$>8 days

C%*%la"!e D!s"#!$%"!&'

0.-/= of the data points fall between 0 and > from the mean

8.8/= of the data points fall between 0 and $8 from the mean

-D= of the data points fall between 0 and $- from the mean

69= of the data points fall between 0 and G- from the mean

E.E/= of the data points fall between 0 and G8 from the mean

.6/= of the data points fall between 0 and G> from the mean

+hat is the probability that you will nish the tas% in 86$>8 daysH Calculate the probability of

nishing in >8 days or less.

It is as%ing for cumulati&e probability of all the &alues of >8 days or less.

S&l%"!&'

• In Step - of the preceding list, the mean 'point in normal distribution that /0= of the results are

abo&e or below was >0 days.

• Standard )e&iation was 8

• >0 days 'the mean( G - '8 days( >8 days

• ;oo%ing at the preceding information, you can see that 69= of the results fall between 0 and

G- from the mean

• 5herefore you can reliably estimate that 69= chance that the tas% will be nished in >8 days or

less

E. TIP

• @ecause D6= of all results are G7$- from the mean, if you are determining the percent that is

!ust G-, you di&ide D6= by 8 to get >9=. 5o get the cumulati&e distribution, you start with the

mean /0= and add >9= to show the cumulati&e &alue for G-J

, 418 ( =6 @ 80

• Subtract >9= to get the cumulati&e &alue for $-J

- 418 ( =6 @ ?1

•

Follow the same method for 8 using /./= di&ided by 8, and for > using .E= di&ided by 8.

F. PROCESSES

PROCESS DE)INITION INPUT OUTPUT TOOLS

TECHNIQUES

6.- ;*<

Q*;I5B

M*<*K#M#<

5

Identifying the

quality

standards7requirem

ents for both the

product and the

Scope Statement

'+@S and +@S

)ictionary(

$ 5here is info on

product quality

-. Quality

Management

lan

8. rocess

Impro&ement

-. Cost$benet

analysis

8. Cost of Quality

>. Se&en @asic

Quality 5ools



'lanning( pro!ect throughout

the pro!ect$

planning phase and

documenting how

the pro!ect will

demonstrate

compliance.

Schedule baseline

Cost baseline

$ )etermine quality

of the pro!ect

performance

"is% "egister

$ 5o identify e&ents

that cannegati&ely impact

pro!ect7product

quality

Sta%eholder "egister

$ )ocuments

sta%eholders with

interest or impact

on quality

management

##F 'standards andregulations(

A* 'company policies

dening process that

must be followed to

ensure pro!ect and

product quality(

lan

>. Quality Metrics

9. Quality

Chec%lists

/. ro!ect

)ocument

pdates

9. @enchmar%ing

/. )esign of

#2periments

D. Statistical

Sampling

E. *dditional

Quality lanning

5ools

6. Meetings

6.8 #"FA"M

Q*;I5B

*SS"*<C#

4EFe+%"!'6

-. Quality

Management lan

8. rocess

Impro&ement lan

>. Quality metrics9. Quality Control

Measurements

/. ro!ect )ocuments

-. Change "equests

8. M lan pdates

>. ro!ect

)ocument

pdates9. A* updates

-. Quality

Management

and Control

tools

8. Quality *udits>. rocess

*nalysis

6.> CA<5"A;

Q*;I5B

4M&'!"&#!'

a'

C&'"#&ll!'6

-. ro!ect

Management lan

8. Quality Metrics

>. Quality Chec%lists

9. +or% erformance

)ata

/. *ppro&ed Change

"equests

)eli&erables

ro!ect )ocumentsA* *ssets

-. Quality Control

Measurements

8. Lalidated

Changes

>. Lalidated

)eli&erables

9. +or%

erformance

Information

/. Change "equestsD. M lan pdates

E. ro!ect

)ocument

pdates

6. A* updates

-. Se&en basic

quality tools

8. Statistical

sampling

>. Inspection

9. *ppro&ed

Change

"equests

re&iew

G. T&&ls a' Te+h'!%es

Cost$@enet Financial *nalysis 5ool to determine benets against cost



*nalysis

Cost of

Quality

Method of determining costs incurred to ensure quality

a. Cost of Conformance 1 cost of not allowing defects to occur

're&ention and appraisal costs 1 costs for quality planning, quality control, and quality

assurance to ensure compliance to requirements(

P#ee'"!&' C&s"s 5 '&" all&;!' e3e+"s "& &++%#

e.g. 5raining, robust processes and documentation, appropriate tools and equipment

App#a!sal +&s"s 5 *eas%#!' #es%l"s

#.g. 5esting, inspection, test equipment calibration, independent &alidation, quality

assurance, quality control(

b. Cost of <onconformance 1 cost of failure

'"ewor% costs, Costs of +arranty +or% and waste ,loss of reputation(

I'"e#'al Scrap material, "ewor%, "oot cause analysis

EF"e#'al +arranty, ;awsuits, ;oss of business and goodwill@enchmar%in

g

@est outcomes from other pro!ects

)esign of

#2periments

5o optimi3e a product or process. +or%ing with multiple &ariables to nd best possible

combination

Statistical

Sampling

5o determine whether a group of deli&erables meet quality requirements.

a. A""#!$%"e Sa*pl!' 1 whether result conforms.

b. a#!a$le Sa*pl!' 1 degree to which result complies as rated on a continuous

scale

Se&en @asic

Quality 5ools

'EQC tools(

-. Cause and e4ect )iagram or )!sh$&'e D!a#a* or Ish!a;a D!a#a* 1 identify

root cause 'problem statement is e4ect and factors are causes(

8. Flowcharts 1 see relationship b7w proess steps

>. Chec%sheets tally sheetsN 1 ensure series of steps are followed consistently, tally

the occurrence of defect

9. areto diagrams 1 &ertical bar chart with e&ents in descending order to ran%

problems/. Oistograms 1 arranged to show the shape of distribution

D. Control Charts 1 whether process is table and predictable. lanned &alue of a

process is the centerline. pper and lower control limits are G7$ >

pper and lower specication limits are limits specied in the quality requirements.

If measurement is getting to the control limit, ta%e action to get it bac% to midline

a. Control chart 1 graphic display of process data o&er time and against

established control limits and that has a centerline assisting in detecting trend

of plotted &alues toward either control limit

b. Control limits 1 area composed of > standard de&iations

c. Specication limits 1 area on either side of the centerline, mean, of data plotted

on control chart that meets customer requirements.E. Scatter )iagrams 1 P,B matri2 that plots the relationship between two &ariables to

determine whether relationship e2ists.*dditional

Quality

lanning

5ools

-. @rainstorming

8. Force eld analysis

>. <ominal Kroup 5echnique

H. NOTES

Q%al!" $ Meeting the "equirements 'not deli&ering more quality(



N& G&l Pla"!' 'it uses time and resources at additional cost to add features and functions

that are unnecessary(

#&aluate costs of conformance with costs of nonconformance by C&s"-Be'e<" A'als!s

)uring planning process, you identify the items to be sampled, number sampled, and criteria for

sampling.

Se&en @asic Quality 5ools can also be used in Control Quality rocess

Management is responsible for in&estment in quality and pro&iding resources for quality

management

I. OUTPUTS9

Q%al!"

*a'ae*e'" pla'

$ describe how you plan to conduct &arious quality processes on your pro!ect

$ Contains quality management roles, responsibilities, quality assurance

approach, techniques and measurements for quality control, plans for quality

impro&ement acti&ities

P#&+ess

I*p#&e*e'" Pla'

$ instructions to impro&e the processes 'process description, process metrics,

targets for impro&ement, impro&ement approach, owchart of current

processes 1 as is process(

MI$ism

Documents

8 Quality Management Dummies