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KARPAGAM INSTITUTE OF TECHNOLOGY

B.E. / B.TECH. CONTINUOUS ASSESSMENT INTERNAL TEST-II

REGULATIONS – 2008

  VII SEMESTER : AERONAUTICAL ENGINEERING

08018006 - TOTAL !UALITY MANAGEMENT

"ATE:1#/0$/2012 TIME : 10.00 AM %& 11.#0 AM

 

MA'.MARKS : (0

PART – A

A)*+, A !,*%&)*  ( 2 3 10 MARKS4

1. N5, %7, *,,) %&&* &9 !5%.

Pareto Diagram, Process Flow Diagram, Cause And Effect Diagram, Check Sheets, Histogram,

Control Charts, Scatter Diagram

2. ;75% * %7, *, &9 <&)%& <75%=

The control chart is used to keep a continuing record of a particular qualit characteristic!

"t is a picture of process o#er time!

#. H&+ + & >,%,), %7, &?% <&*%=

$a% &ake comparison with other organi'ation

$(% )ptimi'e the indi#idual categories

$c% Analse the relationship among the cost categories!

4. ",9), T&%5 P&><%, M5)%,)5)<,. 

Total Producti#e &aintenance $TP&% is defined as keeping the running plant andequipment at its highest producti#e le#el with the co*operation of all areas of the

organi'ation

(. ;75% 5, %7, ),+ *,,) 5)5@,,)% %&&*=

$+% h, h$-% Forced Field Analsis

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$.% /ominal 0roup Technique

$1% Affinit Diagram

$2% "nter*3elationship Digraph$4% Tree Diagram

$5% &atri6 Diagram

$7% Prioriti'ation &atrices$8% Process Decision Program Chart

PART B

  A)*+, ANY FIVE !,*%&)*  (  830 5*4

6. E?5) %7, <&)<,?% &9 S S@5=

S S@5 is a (usiness management strateg, originall de#eloped ( &otorola in +874!

Si6 Sigma (ecame well known after 9ack elch made it a central focus of his (usiness strategat 0eneral Electric in +882, and toda it is widel used in man sectors of industr! Si6 Sigma

seeks to impro#e the qualit of process outputs ( identifing and remo#ing the causes of defects

$errors% and minimi'ing #aria(ilit in manufacturing and (usiness processes!

:1;

 "t uses a setof qualit management methods, including statistical methods, and creates a special

infrastructure of people within the organi'ation $<=lack =elts<, <0reen =elts<, etc!% who are

e6perts in these methods!:1; Each Si6 Sigma pro>ect carried out within an organi'ation follows a

defined sequence of steps and has quantified financial targets $cost reduction and?or profitincrease%!

The term Six Sigma originated from terminolog associated with manufacturing,

specificall terms associated with statistical modeling of manufacturing processes! The maturit

of a manufacturing process can (e descri(ed ( a sigma rating indicating its ield, or the percentage of defect*free products it creates! A si6 sigma process is one in which 88!88844@ of

the products manufactured are statisticall e6pected to (e free of defects $.!1 defects per

million%! &otorola set a goal of <si6 sigma< for all of its manufacturing operations, and this goal (ecame a (word for the management and engineering practices used to achie#e it!

M,%7&>*

Si6 Sigma pro>ects follow two pro>ect methodologies inspired ( Demings Plan*Do*Check*Act

Ccle! These methodologies, composed of fi#e phases each, (ear the acronms D&A"C and

D&ADB!:+2;

D&A"C is used for pro>ects aimed at impro#ing an e6isting (usiness process!:+2; D&A"C

is pronounced as <duh*ma*ick<!

D&ADB is used for pro>ects aimed at creating new product or process designs!:+2; D&ADB is pronounced as <duh*mad*#ee<!

"MAIC

The D&A"C pro>ect methodolog has fi#e phases

"efine the pro(lem, the #oice of the customer, and the pro>ect goals, specificall!

Measure ke aspects of the current process and collect rele#ant data!

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Anal'e the data to in#estigate and #erif cause*and*effect relationships! Determine what

the relationships are, and attempt to ensure that all factors ha#e (een considered! Seek out

root cause of the defect under in#estigation!

Impro#e or optimi'e the current process (ased upon data analsis using techniques such

as design of e6periments, poka oke or mistake proofing, and standard work to create a new,future state process! Set up pilot runs to esta(lish process capa(ilit!

Control the future state process to ensure that an de#iations from target are corrected

 (efore the result in defects! "mplementcontrol sstems such as statistical process control,

 production (oards, #isual workplaces, and continuousl monitor the process!

Some organi'ations add a R ecogni'e step at the (eginning, which is to recogni'e the right

 pro(lem to work on, thus ielding an 3D&A"C methodolog!:+5;

"MA"V & "FSS

The D&ADB pro>ect methodolog, also known as DFSS $<"esign For Si6 Sigma<%,:+2; features

fi#e phases

"efine design goals that are consistent with customer demands and the enterprise

strateg!

Measure and identif CTs $characteristics that are Critical To !ualit%, product

capa(ilities, production process capa(ilit, and risks!

Anal'e to de#elop and design alternati#es, create a high*le#el design and e#aluate

design capa(ilit to select the (est design!

"esign details, optimi'e the design, and plan for design #erification! This phase ma

require simulations!

Verif the design, set up pilot runs, implement the production process and hand it o#er to

the process owner$s%!

. E?5) 7&+ %& > 7&*, &9 D5% ) >,?&)@ D5% 9)<%&).

ualit Function Deploment is a planning tool used to fulfill customer e6pectations!

ualit Function Deploment focuses on customer e6pectations or requirements, oftenreferred to as #oice of the customer!

!F" TEAM :

There are two tpes of teams namel, +! Team for designing a new product and -! Team forimpro#ing an e6isting product

HOUSE OF !UALITY :

Interrelationship

Between

Technical

Descriptors

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THE STEPS "/ ="D"/0 A H)SE )F A"TG A3E

+! ist Customer 3equirements $HATs%

-! ist Technical Descriptors $H)s%.! De#elop a 3elationship &atri6 =etween HATs and H)s

1! De#elop an "nter*relationship &atri6 (etween H)s

2! Competiti#e Assessmentsa! Customer Competiti#e Assessments

 (! Technical Competiti#e Assessments

Technical Descriptors

(Voice of the organization)

Relationship between

Requirements and

Descriptors

Prioritized

Technical Descriptors

     u  s   t  o  m  e  r   R  e  q  u   i  r  e  m  e  n   t  s

   (   V  o   i  c  e  o   f   t   h  e  c  u  s   t  o  m  e  r   )

   P  r   i  o  r   i   t   i  z  e   d

     u  s   t  o  m  e  r   R  e  q  u   i  r  e  m  e  n   t  s

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4! De#elop Prioriti'ed Customer 3equirements

5! De#elop Prioriti'ed Technical Descriptors

8. B,9 ,?5) %7, <&)<,?% &9 T&%5 P&><%, M5)%,)5)<,.

Total Producti#e &aintenance $TP&% is an e6tension of the Total ualit &anagement

$T&% philosoph to the maintenance function! TP& has the following steps +!

&anagement should learn the new philosoph of TP&! -! &anagement should promote the

new philosoph of TP&! .! Training should (e funded and de#eloped for e#erone in the

organi'ation! 1! Areas of needed impro#ement should (e identified! oss measurements to

identif impro#ement needs are

Down time losses

3educed speed losses

Poor qualit losses2! Performance goals should (e formulated! 4! An implementation plan should (e de#eloped!

5! Autonomous worth groups should (e esta(lished!

$. E?5) %7, ,),9%* &9 FMEA= F&EA is an analtical technique that com(ines the technolog and e6perience of people

in identifing foreseea(le failure modes of a product or process and planning for its

elimination 

Ha#ing a sstematic re#iew of components failure modes to ensure that an failure

 produces minimal damage! Determining the effects of an failure on other items!

Pro#iding input data for e6change studies!

Determining how the high*failure rate components can (e adapted to high*relia(ilit

components!

Eliminating ? minimi'ing the ad#erse effects that failures could generate!

Helping unco#er the mis>udgements, errors etc!

 3educe de#elopment time and cost of manufacturing!

10. B,9 ,?5) T5@<7* !5% L&** F)<%&)Taguchis ualit oss Function concept com(ines cost, target and #ariation in one metric with

specifications (eing of secondar importance!

Taguchi has defined qualit as the loss imparted to societ from the time a product is shipped!

Societal losses include failure to meet customer requirements, failure to meet ideal performance and

harmful side effects!

CUSTOMERS PERCEIVE !UALITY AS MEETING THE TARGET RATHER

THAN UST MEETING THE SPECIFICATIONS.

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There are three common qualit loss functions

+! /ominal * the * (est!

-! Smaller * the * (etter!

.! arger * the * (etter!

NOMINAL – THE – BEST :

Although Taguchi de#eloped so man loss functions, man situations are appro6imated ( the quadratic

function which is called the N&)5 – %7, – ,*% tpe!

The quadratic function is shown in figure! "n this situation, the loss occurs as soon as the performance

characteristic, , departs from the target I!

   !  o  s  s   (   R  s   )

USL

A

τ + ∆

LSL

Performance Characteristic

Quadratic Loss Function

L

0τ - ∆

Y

τ

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At I, the loss is 3s! J!

At S $or% S, the loss is 3s! A!

The quadratic loss function is descri(ed ( the equation K k $ * I% -!

here,

K cost incurred as qualit de#iates from the target!

K Performance characteristic

I K target

k K ualit loss coefficient!

The loss coefficient is determined ( setting L K $ M 

 I%, the de#iation from the target! hen L is the

S $or% S, the loss to the customer of repairing $or% discarding the product is 3s! A!

Thus, N K A ? $ M   I%- K A ? L- !

SMALLER – THE – BETTER :

The following figure shows the smaller M the M (etter concepts!

The target #alue for *5, – %7, – ,%%,  is J! There are no negati#e #alues for the performance

characteristic!

The radiation leakage from amicrowa#e appliance, the

response time for a computer,

 pollution from an automo(ile, out

of round for a hole etc! are the

 performance characteristics for

this concept!

LARGER – THE – BETTER :

The following figure shows the

concept of the arger M the M (etter!

   L  o  s  s   (   R  s   )

A

Performance Characteristic

Smaller-the-better

L

0

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"n the arger M the M (etter concept, the target #alue is O $infinit%, which gi#es a ,& &**! There are no

negati#e #alues and the worst case is at K J! Actuall, larger M the M (etter is the reciprocal of smaller M

the M (etter! The performance characteristics in arger M the M (etter are (ond strength of adhesi#es,

welding strength etc!

11. E?5) %7, %, P&<,** C5?5%.

A process is a unique com(ination of tools, materials, methods, and people engaged in

 producing a measura(le output for e6ample a manufacturing line for machine parts! All

 processes ha#e inherent statistical #aria(ilit which can (e e#aluated ( statistical methods!

The Process Capa(ilit is a measura(le propert of a process to the specification,

e6pressed as a process capa(ilit inde6 $e!g!, C pk or C pm% or as a process performance inde6 $e!g!,

y

 L o s s ( R s )

A

Performance Characteristic

Larger-the-better

L

0y

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P pk  or P pm%! The output of this measurement is usuall illustrated ( a histogram and calculations

that predict how man parts will (e produced out of specification $))S%!

Process capa(ilit is also defined as the capa(ilit of a process to meet its purpose as

managed ( an organi'ations management and process definition structures "S) +22J1!Two

 parts of process capa(ilit are +% &easure the #aria(ilit of the output of a process, and -%

Compare that #aria(ilit with a proposed specification or product tolerance!

CAPA=""TG STDG The output of a process is e6pected to meet customer

requirements, specifications, or engineering tolerances! Engineers can conduct a process

capa(ilit stud to determine the e6tent to which the process can meet these e6pectations!

The a(ilit of a process to meet specifications can (e e6pressed as a single num(er using

a  process capa(ilit inde6 or it can (e assessed using control charts! Either case requires running

the process to o(tain enough measura(le output so that engineering is confident that the process

is sta(le and so that the process mean and #aria(ilit can (e relia(l estimated! Statistical process 

controldefines techniques to properl differentiate (etween sta(le processes, processes that are

drifting $e6periencing a long*term change in the mean of the output%, and processes that aregrowing more #aria(le! Process capa(ilit indices are onl meaningful for processes that are

sta(le $in a state of statistical control%!

12. E5&5%, B,)<7 M5)@ P&<,**.

The following si6 steps contain the core techniques of =enchmarking

1. ",<>, +75% %& ,)<75 

=enchmarking can (e applied to an (usiness or production process

The strateg is usuall e6pressed in terms of mission and #ision statements

=est to (egin with the mission and critical factors

Choosing the scope of the =enchmarking stud Pareto analsis M what process to in#estigate

Cause and Effect diagram M for tracing outputs (ack 

2. U)>,*%5)> <,)% ?,9&5)<,

nderstand and document the current process

Those working in the process are the most capa(le of identifing and correcting

 pro(lems

hile documenting, it is important to quantif

Care should (e taken during accounting information

#. P5)

A (enchmarking team should (e chosen

)rgani'ations to ser#e as the (enchmark need to (e identified

Time frame should (e agreed upon for each of the (enchmarking tasks

There are three tpes of (enchmarking

a! "nternal (! Competiti#e

c! Process

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. S%> O%7,*

=enchmarking studies look for two tpes of information

How (est the processes are practiced

&easura(le results of these practices

Three techniques for conducting the research are

uestionnaires

Site #isits

Focus groups

(. L,5) 9& %7, >5%5

Answering a series of questions like

"s there a gap (etween the organi'ations performance and the performance of the (est*in*class organi'ationsQ

hat is the gapQ How much is itQ

h is there a gapQ hat does the (est*in*class do differentl that is (etterQ "f (est*in*class practices were adopted, what would (e the resulting impro#ementQ

=enchmarking studies can re#eal three different outcomes

 /egati#e gap

Parit

Positi#e gap

6. U*)@ %7, 9)>)@*

The o(>ecti#e is to close the gap! For this

Findings must (e communicated to the people within the organi'ation

Action plans must (e de#eloped to implement new processes0roups that must agree on the change

Process owners

pper management

Steps for the de#elopment and e6ecution of action plans are

+! Specif tasks-! Sequence tasks

.! Determine resources needs1! Esta(lish task schedule2! Assign responsi(ilit for each task 

4! Descri(e e6pected results

5! Specif methods for monitoring results

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