Pom quality assurance

Quality Assurance

Preeti Nigam

Quality Assurance

Quality Assurance that relies primarily on inspection after production is referred to as acceptance sampling.

Quality assurance efforts that occur during production are referred to as statistical process control.

Approaches to Quality Assurance

The least progressive

The most progressive

Inspection before/after production

Corrective action during production

Quality built into the process

Acceptance Sampling

Process Control

Continuous Improvement

Inspection

Monitoring in the production process can occur at three points: before production, during production and after production.

Inputs Transformation Outputs

Acceptance Sampling

Process Control Acceptance Sampling

How Much to Inspect and How Often Low cost high volume items like paper clips, wooden

pencils etc. often require little inspection because1. The cost associated with passing defectives is quite low2. The processes that produce these items are usually highly

reliable Conversely, high cost low volume items that have

large costs associated with passing defectives often require more intensive inspections. E.g.. Space vehicle.In high volume systems automated inspection is one option that can be employed.

Amount of Inspection

Total Cost

Cost of Inspection

Cost of passing defectives

Optimal Amount of inspection

Cost

0

Where to inspect in the process

1. Raw materials and purchased parts

2. Finished products

3. Before a costly operation

4. Before an irreversible process

5. Before a covering process

Examples of inspection points

Type of business Inspection points

Characteristics

Fast Food Cashier Accuracy

Parking Lot Safe, well-lighted

Hotel/Motel Main Desk Appearance, Waiting time, accuracy of bills

Maid service Completeness, productivity

Supermarket Deliveries Quality, Quantity

Shelf displays Appearance

Quality Management

Quality is the ability of a product or service to consistently meet or exceed customer expectations.

The Quality Gurus Walter Shewhart

“Father of statistical quality control” W. Edwards Deming Joseph M. Juran Armand Feignbaum Philip B. Crosby Kaoru Ishikawa Genichi Taguchi

Key Contributors to Quality Management

Contributor

Deming Juran Feignbaum Crosby Ishikawa Taguchi Ohno and Shingo

Known for

14 points; special & common causes of variation Quality is fitness for use; quality trilogy Quality is a total field Quality is free; zero defects Cause-and effect diagrams; quality circles Taguchi loss function Continuous improvenment

Quality

Total Quality Management Definition-Managing the entire organization

so that it excels on all dimensions of products and services that are important to the customer.

Total = Quality involves everyone and all activities in the company

Quality = Conformance to requirements

Management = Quality can and must be managed

Ten Steps to TQM

1. Pursue new strategic thinking2. Know your customers3. Set true customer requirements4. Concentrate on prevention not correction5. Reduce chronic waste6. Pursue a continuous improvement strategy7. Use structured methodology for process improvement8. Reduce variation9. Use balanced approach10. Apply to all functions

Elements of TQM1. Continual improvement2. Competitive benchmarking3. Employee empowerment4. Team approach5. Decisions based on facts6. Knowledge of tools7. Supplier quality8. Champion9. Quality at the source10. Suppliers

Principles of TQM

1. Quality can and must be managed2. Everyone has a customer and is a supplier3. Process not people are the problem4. Every employee is responsible for quality5. Problems must be prevented, not just fixed6. Quality must be measured7. Quality improvements must be continuous8. The quality standard is defect free9. Goals are based on requirements, not negotiated10. Life cycle costs, not front end costs11. Management must be involved and lead12. Plan and organize for quality improvement

Lack of: Company-wide definition of quality Strategic plan for change Customer focus Real employee empowerment Strong motivation Time to devote to quality initiatives Leadership

Obstacles to Implementing TQM

Poor inter-organizational communication

View of quality as a “quick fix” Emphasis on short-term financial

results Internal political and “turf” wars

Obstacles to Implementing TQM

Quality Specifications

Design Quality- refers to the inherent value of the product in the market place and is thus a strategic decision for the firm.

E.g. performance, features, reliability, durability, response, aesthetics

Quality Specifications

Conformance Quality- refers to the degree to which the product or service design specifications are met. The activities involved in achieving the conformance are of a day to day nature.

Product with high design quality can have a low conformance quality or vice-versa.

The Consequences of Poor Quality

Loss of business Liability Productivity Costs

Substandard work Defective products Substandard service Poor designs Shoddy workmanship Substandard parts and materials

Ethics and Quality

Having knowledge of this and failing to correctand report it in a timely manner is unethical.

Quality Specifications Quality at the Source

The philosophy of making each worker responsible for the quality of his or her work.

i.e. the person who does the work takes responsibility for making sure that his or her output meets specifications.

Costs of Quality

1. Appraisal Costs- Cost to ensure that product is acceptable e.g. inspection, testing

2. Prevention Costs- The sum of all costs to prevent defects e.g. train, redesign, purchase new, make modifications

3. Internal Failure Costs- Costs for defects incurred within the system e.g. scrap, rework, repair

4. External Failure Costs- Costs for defects that pass through the system e.g. warranty replacements, loss of goodwill, product repair

Continuous Improvement

Philosophy that seeks to make never-ending improvements to the process of converting inputs into outputs.

Kaizen: Japanese word for continuous improvement.

Zero Defects First introduced by US Defence services in the manufacture of

aircrafts and aerospace vehicles in 1962- “ZD Program”

Principles-1. Creator is the Master- worker is more knowledgeable and suitable to identify &

rectify errors

2. Inspection by Internal agency is better than external person- Inspection by outside agency may lead to presumption that workers have less knowledge & could affect their morale

3. Prevention is better than cure- Errors are caused by lack of knowledge and lack of attention. Improved by making workers directly involved in the manufacture and providing better training, better supervision and assistance. Workers are to be convinced that they are capable of producing products with zero error

Success of ZD depends on –1. ZD Committee2. Top Management involvement and commitment3. Selling the idea4. Motivation

Identify a critical process that needs improving

Identify an organization that excels in this process

Contact that organization Analyze the data Improve the critical process

Benchmarking Process

Poka-YokesSimple practices that prevent errors or provide feedbackin time for worker to correct errors. e.g. defects, omitted processing, missing parts, wrong parts

It includes tooling that-1. Prevents worker from making an error that leads

to a defect before starting a process2. Gives rapid feedback of abnormalities in the

process to the worker in time to correct them.

Quality Awards1. Malcolm Balridge National Quality Award

2. The Deming Prize

3. The European Quality Award

4. ISO 9001

5. Black Belt

6. Master Black Belt

7. Greenbelt

Malcolm Balridge National Quality Award

1.0 Leadership (125 points)

2.0 Strategic Planning (85 points)

3.0 Customer and Market Focus (85 points)

4.0 Information and Analysis (85 points)

5.0 Human Resource Focus (85 points)

6.0 Process Management (85 points)

7.0 Business Results (450 points)

Benefits of Balridge Competition

Financial success Winners share their knowledge The process motivates employees The process provides a well-designed

quality system The process requires obtaining data The process provides feedback

European Quality Award

Prizes intended to identify role models Leadership Customer focus Corporate social responsibility People development and involvement Results orientation

The Deming Prize

Honoring W. Edwards Deming

Japan’s highly coveted award

Main focus on statistical quality control

Quality Certification ISO 9000

Set of international standards on quality management and quality assurance, critical to international business

ISO 14000 A set of international standards for assessing

a company’s environmental performance

ISO 9000 Quality Management Principles

Customer focus Leadership People involvement Process approach A systems approach to management Continual improvement Factual approach to decision making Mutually beneficial supplier relationships

ISO 14000 - A set of international standards for assessing a company’s environmental performance

Standards in three major areas Management systems Operations Environmental systems

ISO 14000

Management systems Systems development and integration of

environmental responsibilities into business planning

Operations Consumption of natural resources and energy

Environmental systems Measuring, assessing and managing emissions,

effluents, and other waste

ISO 14000

Assignment Quality Awards were discussed in the class

and assignment given

Statistical Quality Control SQC- Techniques designed to evaluate quality

from a conformance view. That is how well we are doing at meeting the specifications that have been set during the design of the parts or services that we are providing.

SPC- Techniques for testing a random sample of output from a process to determine whether a process is producing items within a prescribed range.

Normal Distribution

Mean

95.44%

99.74%

Standard deviation

Basic Quality Tools Flowcharts

Check sheets

Histograms

Pareto Charts

Scatter diagrams

Control charts

Cause-and-effect diagrams

Run charts

Check SheetBilling Errors

Wrong Account

Wrong Amount

A/R Errors

Wrong Account

Wrong Amount

Monday

Pareto Analysis

80% of the problems may be

attributed to 20% of the

causes.

80% of the problems may be

attributed to 20% of the

causes.

Smearedprint

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f d

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ts

Offcenter

Missinglabel

Loose Other

Cause-and-Effect Diagram

Effect

MaterialsMethods

EquipmentPeople

Environment

Cause

Cause

Cause

Cause

Cause

CauseCause

Cause

CauseCause

Cause

Cause

Control Chart Control Chart

Purpose: to monitor process output to see if it is random

A time ordered plot representative sample statistics obtained from an on going process (e.g. sample means)

Upper and lower control limits define the range of acceptable variation

Control LimitsSamplingdistribution

Processdistribution

Mean

Lowercontrol

limit

Uppercontrol

limit

Control Chart

970

980

990

1000

1010

1020

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

UCL

LCL

Control Chart

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

UCL

LCL

Sample number

Mean

Out ofcontrol

Normal variationdue to chance

Abnormal variationdue to assignable sources

Abnormal variationdue to assignable sources

Quality Control Techniques

Quality Control Techniques

Control Charts Acceptance Sampling

For Variables

For Attributes

Plan with α

Single Sampling

For Variables For Attributes

X Chart

R Chart

P Chart

C Chart Plan with α & βDouble Sampling

Multiple Sampling

Control Chart Issues 1. Size of sample 4-5

2. No. of samples 25

3. Frequency 5 units every half hour

4. Control Limits 3 std dev above and below mean

Control Charts for Variables

Mean control charts Used to monitor the central tendency of a

process.

X bar charts

Range control charts Used to monitor the process dispersion

R charts

Variables generate data that are Variables generate data that are measuredmeasured..

Control Chart for Variables

X Chart is simply a plot of the means of the samples that were taken from a process. X is the average of the means.

UCLx = X + 3σx = X + AR

LCLx = X - 3σx = X - AR

X = Mean of sample

X = Mean of sample means

σx = sample std. error = σ/√n

Control Chart for Variables R Chart is a plot of the range within each sample.

R is the average of range of each sample.

UCLR = R + 3σR = BR

LCLR = R - 3σR = CR

R = RangeσR = std. dev of R

Mean and Range Charts

UCL

LCL

UCL

LCL

R-chart

x-Chart Detects shift

Does notdetect shift

(process mean is shifting upward)

SamplingDistribution

x-Chart

UCL

Does notreveal increase

Mean and Range Charts

UCL

LCL

LCL

R-chart Reveals increase

(process variability is increasing)SamplingDistribution

NumericalQ- The following data was obtained over a 5 day

period to indicate X and R control chart for a quality characteristic of a certain manufacturing product that had required substantial amount of rework. All the figures apply to the product made on a single machine by a single operator. Sample size is 5. Two samples are taken per day. Comment on the process using X and R charts.

DaysSample # 1 2 3 4 5

1 10 12 13 8 9

2 7 10 8 11 9

3 11 12 9 12 10

4 10 9 8 13 11

5 8 11 11 7 7

6 11 8 8 11 10

7 10 12 13 13 9

8 10 12 12 10 12

9 12 13 11 12 10

10 10 13 7 9 12

DaysSample #

1 2 3 4 5 X R

1 10 12 13 8 9 10.4 5

2 7 10 8 11 9 9.0 4

3 11 12 9 12 10 10.8 3

4 10 9 8 13 11 10.2 5

5 8 11 11 7 7 8.8 4

6 11 8 8 11 10 9.6 3

7 10 12 13 13 9 11.4 4

8 10 12 12 10 12 11.2 2

9 12 13 11 12 10 11.6 3

10 10 13 7 9 12 10.2 6

Solution

∑X = 103.2

X = ∑X/k = 103.2/10 = 10.32

For sample size n = 5, A= 0.58, B = 2.11, C = 0UCLx = X + AR

= 10.32 + (0.58*3.9)= 10.32 + 2.262 = 12.582

LCLx = X – AR= 10.32 – 2.262= 8.058

∑R = 39

R = ∑R/k = 39/10 = 3.9

UCLR = BR= 2.11 * 3.9= 8.229

LCLR = CR= 0*3.9= 0

P Chart P Chart is the percent defective chart based on

Normal distributionIts purpose – 1. discover the average % of non-conforming parts2. bring to mgmt attention any change in the average quality

level

UCLρ = ρ + 3√ ρ (1- ρ )/n = ρ + 3σρ

LCLρ = ρ - 3√ ρ (1- ρ )/n = ρ - 3σρ ρ = process % defective ρ = process mean % n = sample size

Use of p-Charts

When observations can be placed into two categories. Good or bad Pass or fail Operate or don’t operate

When the data consists of multiple samples of several observations each

Assignment NumericalQ- Completed forms from a particular department of an

Insurance Company were sampled daily to check the performance quality of that department. 1 sample of 100 units was collected each day for 15 days.

a) Develop p chart using 95% confidence level (1.96 σp)b) Plot the 15 samples collectedc) What comments can you make about the process

Numerical contd.Sample No. of

Forms with Errors

Sample No. of Forms with Errors

1 4 8 3

2 3 9 4

3 5 10 2

4 0 11 7

5 2 12 2

6 8 13 1

7 1 14 3

15 1

C Chart C Chart is the no. of defectives/ sample

area based on Poisson distribution

UCLc = C + 3√C

LCLc = C - 3√C

C = mean number of non-conformities

Use of c-Charts

Use only when the number of occurrences per unit of measure can be counted; non-occurrences cannot be counted. Scratches, chips, dents, or errors per item Cracks or faults per unit of distance Breaks or Tears per unit of area Bacteria or pollutants per unit of volume Calls, complaints, failures per unit of time

NumericalQ- β electronic company manufactures resistors

on mass production basis. At some intermediate point of production line, 10 samples of size 100 each have been taken. Resistors within each sample were classified into good or bad. The related data are given in the following table. Construct p chart with 3 sigma limit and comment on the process.

TableSample # 1 2 3 4 5 6 7 8 9 10

# defective resistors

12 15 20 14 9 20 15 10 9 8

Acceptance Sampling Acceptance Sampling deals with accept/reject

situation of the incoming raw materials

Acceptable Quality Level (AQL)Lots are defined as high quality if they contain no more than a specified level of defectives

Lot Tolerance Percent Defective (LTPD)Lots are defined as Low Quality if the % of defectives is greater than a specified amount

Type I and Type II Error Type I Error or Producer’s Risk

The probability associated with rejecting a high quality lot and is denoted by α

Type II Error or Consumer’s Risk

The probability associated with accepting a low quality lot and is denoted by β

Sampling Plan1. Single Sampling Plan

Sample size n and acceptance number cE.g. n= 50 and c= 3If no. of defectives <= 3 accept the lot or else reject

2. Double Sampling PlanAt the max two samples will be drawn before accepting/rejecting lot. If 1st lot is not accepted then 1 more sample is drawn and based on combined quality level of the samples, final decision is made

NumericalQ1- Design Single Sampling Plan with the

following parameters

Producer’s risk α = 0.5, β = 0.10, AQL = 0.04, LTPD = 0.10

Q2- Assume lot size of 1500 units and AQL of 4%. Design a Double Sampling Plan.

Numerical Exercises Numerical exercises on

1. X Chart2. R Chart3. P Chart4. C Chart 5. Single Sampling6. Double Samplingwere solved on all the Board.

Assignment given