pom quality assurance
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Quality Assurance
Preeti Nigam
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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.
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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
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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
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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.
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Amount of Inspection
Total Cost
Cost of Inspection
Cost of passing defectives
Optimal Amount of inspection
Cost
0
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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
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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
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Quality Management
Quality is the ability of a product or service to consistently meet or exceed customer expectations.
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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The Consequences of Poor Quality
Loss of business Liability Productivity Costs
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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.
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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.
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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
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Continuous Improvement
Philosophy that seeks to make never-ending improvements to the process of converting inputs into outputs.
Kaizen: Japanese word for continuous improvement.
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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
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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
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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.
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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
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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)
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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
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European Quality Award
Prizes intended to identify role models Leadership Customer focus Corporate social responsibility People development and involvement Results orientation
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The Deming Prize
Honoring W. Edwards Deming
Japan’s highly coveted award
Main focus on statistical quality control
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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
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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
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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
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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
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Assignment Quality Awards were discussed in the class
and assignment given
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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.
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Normal Distribution
Mean
95.44%
99.74%
Standard deviation
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Basic Quality Tools Flowcharts
Check sheets
Histograms
Pareto Charts
Scatter diagrams
Control charts
Cause-and-effect diagrams
Run charts
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Check SheetBilling Errors
Wrong Account
Wrong Amount
A/R Errors
Wrong Account
Wrong Amount
Monday
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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
Nu
mb
er o
f d
efec
ts
Offcenter
Missinglabel
Loose Other
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Cause-and-Effect Diagram
Effect
MaterialsMethods
EquipmentPeople
Environment
Cause
Cause
Cause
Cause
Cause
CauseCause
Cause
CauseCause
Cause
Cause
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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
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Control LimitsSamplingdistribution
Processdistribution
Mean
Lowercontrol
limit
Uppercontrol
limit
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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
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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
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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
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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
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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..
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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
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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
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Mean and Range Charts
UCL
LCL
UCL
LCL
R-chart
x-Chart Detects shift
Does notdetect shift
(process mean is shifting upward)
SamplingDistribution
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x-Chart
UCL
Does notreveal increase
Mean and Range Charts
UCL
LCL
LCL
R-chart Reveals increase
(process variability is increasing)SamplingDistribution
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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.
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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TableSample # 1 2 3 4 5 6 7 8 9 10
# defective resistors
12 15 20 14 9 20 15 10 9 8
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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
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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
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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
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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.
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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