Software Quality. Unit 2. Advanced techniques

Software Quality

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.

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

88 90 92 94 96 98 100 102 104 106 108 1 2 3 4 5 6 7 8 9 10 S iz e Sample number Control Chart UTL LTL Sample number 1 2 3 4 5 6 7 8 9 10 Size 94 101 98 99 94 106 104 99 101 104 Tolerance 100 5

Two types:

•

By variable: the variation of a

measurable characteristic is

controlled.

•

By attributes: it is controlled if a

determined condition is satisfied.

Normal Distribution

Variable Control Charts

66,26% 95,44% 99,73%

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.

Variable Control Charts

x

3

x

LCI

3

x

LCS

Variable Control Charts

80 85 90 95 100 105 110 115 120 125 130 1 2 3 4 5 6 7 8 9 10 S iz 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.

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.

Control Charts for Attributes

n ) p% ( p% . p% UCL_p 3 100 n ) p% ( p% . p% LCL_p 3 100 p%

Control Charts for Attributes

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% _{= 5,75} UCL= 16,79 LCL= - 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%

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.

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 L e n g 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 LTL UTL C_p 1 C_p 1,33 C_p

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: 1,33 C_p

3σ

x

UTL

C

_pU

3σ

LTL

-x

C

_pL

A process is said to be centered iff:

(C_pL = C_p = C_pU)

If > , the process is off-center towards lower tolerance limit.

If > , the process is off-center towards upper tolerance limit.

Capability Index

p

C C_pU

p

It is an acceptation by inspection technique.

A shipment or lot is accepted if a small sample of the product meets

specifications.

PROBLEMS:

•How to determine the size of the

sample?

•Which criteria use to accept or reject

the lot?

SOLUTIONS:

•Characteristic function of defect per

lot.

•Specific software for determining

•UNE 66020 tables.

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.

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.

Quality Function Deployment (QFD)

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.

Failure Mode and Effect Analysis

(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.

Failure Mode and Effect Analysis

(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.

Failure Mode and Effect Analysis

(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.

Failure Mode and Effect Analysis

(FMEA)

Failure Mode and Effect Analysis

(FMEA)

• Example:

Perform a product FMEA for a hair dryer fan.

• Step 2, define product functions.

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

Component Function

fan To impel the air

Failure Mode and Effect Analysis

(FMEA)

• Step3, predict potential failure modes.

Component Function Failure mode

fan To impel the air

To refresh the engine

Blade breakdown

Failure Mode and Effect Analysis

(FMEA)

• Step 4, identify potential failure

effects.

Component Function Failure mode Failure effect

fan To impel the air

To refresh the engine

Blade breakdown • Temperature raising

• Hair dryer stops • User’s burns

Failure Mode and Effect Analysis

(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

Failure Mode and Effect Analysis

(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

Failure Mode and Effect Analysis

(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.

Failure Mode and Effect Analysis

(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

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

Failure Mode and Effect Analysis

(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

Failure Mode and Effect Analysis

(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.

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.

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.

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

Product

or 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 Conforming products 2nd _Stage Etapa Error Defect Inspections Process Conforming products Customer Error Defect Inspections Process Impr ov ement 3rd _Stage Error Defect Inspections Process 4th _Stage Impr ov emen t Error POKA-YOKE Zero Defects Process 5th _Stage Impr ov emen t Conforming products Customer Conforming products Customer