calidad del software - ocw upm

Software Quality

Unit 2. Advanced techniques

Calidad del Software

Index

1. Statistical techniques: Statistical process

control, variable control charts and control

chart for attributes.

2. Advanced techniques: Quality function

deployment (QFD), Failure mode and effect

analysis (FMEA), Poka-Yoke.


GOALS:

Process stability observation trough

statistical techniques.

Continuous process improvement.

To study the way in which process

variables can affect essential

characteristic of the product or service.

Statistical process control (SPC)


SPC is a tool which permits to predict, reduce and maintain variations within reasonable limits.

It is possible to find out:

•Controllable variables (assignable causes): changes in the raw material, breakdown in the machinery...

•Uncontrollable variables (non assignable causes): random variables …



A process is said to be under statistical

control when it is only affected by random

variables due to non assignable causes.

If it is also affected by assignable causes, it

is said that the process is out of statistical

control.

In SPC variations are measured, it is study

their causes and they are corrected.



It is a plotting graph in which a central line and tolerance limits (upper and lower) appears. This lines permit to study the variation of a determine variable (plotted values) with respect to the central line.

To do that, samples are periodically taken during the manufacturing process. The average and variability of the process are studied, and the process are kept under statistical control.

Control Charts


Control Charts

88

90

92

94

96

98

100

102

104

106

108

1 2 3 4 5 6 7 8 9 10

Siz

e

Sample number

Control Chart

UTL

LTL

Samplenumber

1 2 3 4 5 6 7 8 9 10

Size 94 101 98 99 94 106 104 99 101 104

Tolerance 5100


Two types:

• By variable: the variation of a

measurable characteristic is

controlled.

• By attributes: it is controlled if a

determined condition is satisfied.

Control Charts


Normal Distribution

Variable Control Charts

66,26%

95,44%

99,73%

Gauss bell


To know if a process following a Normal distribution is under statistical control, it is needed to calculate Upper and Lower Control limits:

With these limits, it is assured that the 99.73% of the measured values are within limits.


x

3xLCI

3xLCS



80

85

90

95

100

105

110

115

120

125

130

1 2 3 4 5 6 7 8 9 10

Siz

e

Sample number

UTL

LTL

UCL

LCL

x


They are used when measurements are not

possible, for example, scratches, damages, etc.

These controls are made at the end of the

process, when defects are presented. They are

necessary to assure product quality.

One of the most used is the p chart. The p chart

is used to report the proportion of

nonconforming unit in a sample or subgroup.

Control Charts for Attributes


From data the proportion of nonconforming

units are calculated for each one of the

samples (p%)

, the average of the p%, and control

limits are then calculated.


n

)p%(p%.p%UCLp

1003

n

)p%( p%.p%LCLp

1003

p%



Sample number 1 2 3 4 5 6 7 8 9 10

Number inspected 40 40 40 40 40 40 40 40 40 40

Number nonconforming 2 2 1 5 2 4 1 2 1 3

Proportion %p 5,0 5,0 2,5 12,5 5,0 10,0 2,5 5,0 2,5 7,5

p% = 5,75UCL= 16,79LCL= - 5,29

0,0

2,0

4,0

6,0

8,0

10,0

12,0

14,0

16,0

18,0

20,0

1 2 3 4 5 6 7 8 9 10

p%

p Chart of nonconforming unit

p%

UCL


It is said that a process or machine is

capable when they meet specifications.

Process capability is not only used to assure

that process are under statistical control,

but also to minimize the number of

nonconforming units.

Process Capability


A process with UCL > UTL (Upper Tolerance

Limit) can produce nonconforming products.

80

85

90

95

100

105

110

115

120

125

130

1 2 3 4 5 6 7 8 9 10

Leng

th

Sample number

USL

LSL

UCL

LC

x

Process Capability


When a process follows a normal distribution, the process is in

statistical control, process capability is equal to . Thus, if

we are capable of designing processes so that UTL – LTL > ,

it is possible to assure that practically all the products are in

tolerance zone.

6

Process Capability

LTI LTS

LTS-LTI

99,73%

6


Capability index is the relation between tolerance

and process capability ( ).

If process produces nonconforming units.

If process is capable, and values are in

tolerance zone.

Capability Index

6

6σ

LTLUTLCp

1Cp

1,33Cp


Capability Index

A process with can produce units out

of limits, when the process is not centered.

They are defined Upper and Lower capability

index as follow:

1,33Cp

3σ

xUTLCpU

3σ

LTL-xCpL


A process is said to be centered iff:

(CpL = Cp = CpU)

If > , the process is off-center towards

lower tolerance limit.

If > , the process is off-center towards

upper tolerance limit.

Capability Index

pC pUC

pC pLC


It is an acceptation by inspection

technique.

A shipment or lot is accepted if a small

sample of the product meets

specifications.

Sampling plans


PROBLEMS:

•How to determine the size of the

sample?

•Which criteria use to accept or reject

the lot?

Sampling plans


SOLUTIONS:

•Characteristic function of defect per

lot.

•Specific software for determining

•UNE 66020 tables.

Sampling plans


It is a very useful tool to:

• Know customer wishes.

• Define product or service characteristics and requirements.

• Reduce development time.

• Reduce complaints.

• Remove non valuable processes.

Quality Function Deployment (QFD)


House of quality is the primary tool used

in QFD. It is a matrix in which Customer

Requirements (CR) are correlated with

prioritized Technical Descriptors(TD).



Steps to build up the matrix:

1. List Customer Requirements (WHATs).

2. Group customer data.

3. Assign priorities to CR’s.

4. List Technical Descriptors (HOWs).

5. Group technical descriptors (affinity

diagram).



6. Develop a relationship matrix between

WHATs & HOWs.

7. Develop an interrelationship matrix

between HOWs.

8. Competitive assessment (compare with

current products in the market).



9. Develop objective measures per Technical

Descriptor (TD).

10.Establish objectives per TD.

11.Select TD of urgent attention.




Image from the book CALIDAD. Pablo Alcalde San Miguel. Ed. THOMSON Paraninfo


FMEA is a preventive and multidisciplinary teamwork technique that it is performed in a planned and systematically way in order to detect failures in a design, product or service.

Failure Mode and Effect Analysis

(FMEA)


TYPES of FMEA:

•Design FMEA: It is focused into product and component design. Will reduce development time and cost of manufacturing process.

•Process FMEA: It is utilized to identify potential process failure modes by ranking failures and helping to establish priorities according to relative impact on the internal or external customer.


(FMEA)


OBJECTIVES:

• Recognize and evaluate the potential failure of a product or process and its effects.

• Identify actions that could eliminate or reduce the chance of the potential failure occurring.

• Analyze and evaluate the efficacy of the adopted actions and provided resources.


(FMEA)


Steps to follow:

1. Set up the working team.

2. Define process / product functions.

3. Predict potential failure modes.

4. Identify potential failures effects.

5. Analyze possible failure causes.


(FMEA)


Steps to follow:

6. Identify current control systems.

7. Determine assessment index per failure

mode.

8. Plan improvement actions.

9. FMEA revision and traceability.


(FMEA)


(FMEA)

• Example:

Perform a product FMEA for a hair dryer

fan.

• Step 2, define product functions.



Component Function

fan To impel the air

To refresh the engine


(FMEA)

• Step3, predict potential failure modes.


Component Function Failure mode


To refresh the

engine

Blade breakdown



(FMEA)

• Step 4, identify potential failure

effects.


Component Function Failure mode Failure effect


To refresh the

engine

Blade breakdown • Temperature

raising

• Hair dryer stops

• User’s burns



(FMEA)

• Step 5, Analyze possible failure causes (cause-and-effect diagram).


Component Function Failure mode Failure effect Failure cause

fan To impel the

air

To refresh the

engine

Blade

breakdown

• Temperature

raising

• Hair dryer

stops

• User’s burns

• Defect in

material

composition

• Defective

assembly



(FMEA)

• Step 6, Identify current control

systems.


Component Function Failure mode Failure effect Failure cause Controls

fan •To impel

the air

•To refresh

the engine

Blade

breakdown

• Temperature

raising

• Hair dryer

stops

• User’s burns

• Defect in

material

composition

• Defective

assembly

•Supplier

certificate

•Automatic

auto control



(FMEA)

• Step 7, determine assessment index

per failure mode.


Severity Occurrence Detection

Criteria S Criteria O Criteria D

Very slow, failure is not

perceptible by customer

1 Exceptionaly 1 Remote probability failure

comes to customer

1

Low, minor disruption to

customer

2-3 Hardly ever 2-3 Low probability failure

comes to customer.

2-3

Moderate, it produces

dissatisfaction in customer

4-6 often 4-6 Moderate … 4-6

High, it produces high

dissatisfaction in customer.

7-8 Frequently 7-8 High probability … 7-8

Very high, it produces

standards non conformity

or safety problems.

9-10 Almost ever 9-10 Very high probability … 9-10


(FMEA)

• Step 7, determine assessment index

per failure mode.


Component Function Failure mode Failure effect Failure cause Current conditions

Controls O S D RPN

fan • To impel the

air

• To refresh the

engine

Blade

breakdown

• Temperature

raising

• Hair dryer

stops

• User’s burns

• Defect in

material

composition

• Defective

assembly

• Supplier

certificate

• Automatic

auto control

2 10 5 100


Risk Priority Number


(FMEA)

• Step 8, to plan improvement actions

• An individual or group is designed as

responsible.

• A new assessment of failure modes with

the actions taken are made.

• Concrete actions:

Changes in product, service or process design

Inspection or control increment



(FMEA)

• Step 9, FMEA revision and traceability.

• After corrective actions has been

implemented, resulting severity,

occurrence and detection ranks should be

re-calculated.

• Periodic reviews are planned to update

the FMEA.



It is a quality technique proposed by a Japanese engineer Shigeo Shingo in the sixties. The term means “mistake-proofing”.

Poka-Yoke refers to a special inspection mechanism which is used primarily to detect and prevent causes of defects in a system.

Poka-Yoke is a method of preventing errors by putting limits on how an operation can be performed in order to force the correct completion of the operation.

Poka-Yoke


CERO DEFECTS

•A defect is the result or effect of a

simple error.

•With 100% inspections in errors source,

defects are removed.

•100% inspections have a cost and it

must be bounded by the expected profit.

Poka-Yoke


Shingeo Shingo’s CERO DEFECTS :

•Inspection in error source.

•100% inspections using simple and

cheap Poka-Yoke systems.

•Immediate action, operations are

stopped when an error occurs. Moreover,

they do not continue until cause is

remove.

Poka-Yoke


The ideal is to include Poka-Yokes from design stage. If we don’t do that, we are not following the basic quality principle “to do it right the first time”.

Usually, Poka-Yokes are used in combination with other techniques. FMEA is one of them. Through FMEA it is possible to deduce where must be included Poka-Yokes into the process.

Poka-Yoke


Poka-Yoke

Productor Service Design

Process Design

SYSTEM

Poka-Yoke

Product or Service FMEA

Poka-Yoke

Process FMEA

CUSTOMER


Zero Defects Evolution

Nonconforming products

Customer

1st Stage

Error

Defect

Process

Customer

Conformingproducts

2nd StageEtapa

Error

Defect

Inspections

Process

Conformingproducts

Customer

Error

Defect

Inspections

Process

Impro

vem

ent

3rd Stage

Error

Defect

Inspections

Process

4th Stage

Impro

vem

ent

Error

POKA-YOKEZero Defects

Process

5th Stage

Impro

vem

ent

Conformingproducts

Customer

Conformingproducts

Customer

calidad del software - ocw upm

Documents