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Pom quality assurance
 

Pom quality assurance

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    Pom quality assurance Pom quality assurance Presentation Transcript

    • 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 because
        • The cost associated with passing defectives is quite low
        • 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
      • Raw materials and purchased parts
      • Finished products
      • Before a costly operation
      • Before an irreversible process
      • Before a covering process
    • Examples of inspection points Appearance Shelf displays Quality, Quantity Deliveries Supermarket Completeness, productivity Maid service Appearance, Waiting time, accuracy of bills Main Desk Hotel/Motel Safe, well-lighted Parking Lot Accuracy Cashier Fast Food Characteristics Inspection points Type of business
    • 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
    • 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
      • Pursue new strategic thinking
      • Know your customers
      • Set true customer requirements
      • Concentrate on prevention not correction
      • Reduce chronic waste
      • Pursue a continuous improvement strategy
      • Use structured methodology for process improvement
      • Reduce variation
      • Use balanced approach
      • Apply to all functions
    • Elements of TQM
      • Continual improvement
      • Competitive benchmarking
      • Employee empowerment
      • Team approach
      • Decisions based on facts
      • Knowledge of tools
      • Supplier quality
      • Champion
      • Quality at the source
      • Suppliers
    • Principles of TQM
      • Quality can and must be managed
      • Everyone has a customer and is a supplier
      • Process not people are the problem
      • Every employee is responsible for quality
      • Problems must be prevented, not just fixed
      • Quality must be measured
      • Quality improvements must be continuous
      • The quality standard is defect free
      • Goals are based on requirements, not negotiated
      • Life cycle costs, not front end costs
      • Management must be involved and lead
      • 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 correct and 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
      • Appraisal Costs- Cost to ensure that product is acceptable e.g. inspection, testing
      • Prevention Costs- The sum of all costs to prevent defects e.g. train, redesign, purchase new, make modifications
      • Internal Failure Costs- Costs for defects incurred within the system e.g. scrap, rework, repair
      • 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-
        • Creator is the Master- worker is more knowledgeable and suitable to identify & rectify errors
        • 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
        • 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 –
        • ZD Committee
        • Top Management involvement and commitment
        • Selling the idea
        • 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-Yokes
        • Simple practices that prevent errors or provide feedback
        • in time for worker to correct errors.
        • e.g. defects, omitted processing, missing parts, wrong parts
      • It includes tooling that-
      • Prevents worker from making an error that leads to a defect before starting a process
      • Gives rapid feedback of abnormalities in the process to the worker in time to correct them.
    • Quality Awards
      • Malcolm Balridge National Quality Award
      • The Deming Prize
      • The European Quality Award
      • ISO 9001
      • Black Belt
      • Master Black Belt
      • 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 Sheet
      • Billing 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. Smeared print Number of defects Off center Missing label Loose Other
    • Cause-and-Effect Diagram Effect Materials Methods Equipment People Environment Cause Cause Cause Cause Cause Cause Cause Cause Cause Cause 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 Limits Sampling distribution Process distribution Mean Lower control limit Upper control 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 of control Normal variation due to chance Abnormal variation due to assignable sources Abnormal variation due to assignable sources
    • Quality Control Techniques For Variables For Attributes X Chart R Chart P Chart C Chart Plan with α & β Double Sampling Multiple Sampling Quality Control Techniques Control Charts Acceptance Sampling For Variables For Attributes Plan with α Single Sampling
    • Control Chart Issues
      • Size of sample 4-5
      • No. of samples 25
      • Frequency 5 units every half hour
      • 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 measured .
    • 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 + 3 σ x = X + AR
      • LCLx = X - 3 σ x = X - AR
      • X = Mean of sample
      • X = Mean of sample means
      • σ x = 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.
      • UCL R = R + 3 σ R = BR
      • LCL R = R - 3 σ R = CR
      • R = Range
      • σ R = std. dev of R
    • Mean and Range Charts UCL LCL UCL LCL R-chart Detects shift Does not detect shift (process mean is shifting upward) Sampling Distribution x-Chart
    • Mean and Range Charts UCL Does not reveal increase UCL LCL LCL R-chart Reveals increase (process variability is increasing) Sampling Distribution x-Chart
    • Numerical
      • Q- 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.
    • Days 12 9 7 13 10 10 10 12 11 13 12 9 12 10 12 12 10 8 9 13 13 12 10 7 10 11 8 8 11 6 7 7 11 11 8 5 11 13 8 9 10 4 10 12 9 12 11 3 9 11 8 10 7 2 9 8 13 12 10 1 5 4 3 2 1 Sample #
    • Days 10 9 8 7 6 5 4 3 2 1 Sample # 10 12 10 10 11 8 10 11 7 10 1 13 13 12 12 8 11 9 12 10 12 2 7 11 12 13 8 11 8 9 8 13 3 9 12 10 13 11 7 13 12 11 8 4 12 10 12 9 10 7 11 10 9 9 5 6 10.2 3 11.6 2 11.2 4 11.4 3 9.6 4 8.8 5 10.2 3 10.8 4 9.0 5 10.4 R X
    • Solution
      • ∑ X = 103.2
      • X = ∑X/k = 103.2/10
      • = 10.32
      • For sample size n = 5,
      • A= 0.58, B = 2.11, C = 0
      • UCLx = 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
      • UCL R = BR
      • = 2.11 * 3.9
      • = 8.229
      • LCL R = CR
      • = 0*3.9
      • = 0
    • P Chart
      • P Chart is the percent defective chart based on Normal distribution
      • Its purpose –
          • discover the average % of non-conforming parts
          • bring to mgmt attention any change in the average quality level
      • UCL ρ = ρ + 3 √ ρ (1- ρ )/n = ρ + 3 σ ρ
      • LCL ρ = ρ - 3 √ ρ (1- ρ )/n = ρ - 3 σ ρ
      • 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 Numerical
      • Q- 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.
      • Develop p chart using 95% confidence level (1.96 σ p)
      • Plot the 15 samples collected
      • What comments can you make about the process
    • Numerical contd. 3 14 1 7 1 15 1 13 8 6 2 12 2 5 7 11 0 4 2 10 5 3 4 9 3 2 3 8 4 1 No. of Forms with Errors Sample No. of Forms with Errors Sample
    • C Chart
      • C Chart is the no. of defectives/ sample area based on Poisson distribution
      • UCL c = C + 3 √C
      • LCL c = 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
    • Numerical
      • Q- 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.
    • Table 8 9 10 15 20 9 14 20 15 12 # defective resistors 10 9 8 7 6 5 4 3 2 1 Sample #
    • 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 Plan
      • Single Sampling Plan
      • Sample size n and acceptance number c
      • E.g. n= 50 and c= 3
      • If no. of defectives <= 3 accept the lot or else reject
      • Double Sampling Plan
      • At the max two samples will be drawn before accepting/rejecting lot. If 1 st lot is not accepted then 1 more sample is drawn and based on combined quality level of the samples, final decision is made
    • Numerical
      • Q1- 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
        • X Chart
        • R Chart
        • P Chart
        • C Chart
        • Single Sampling
        • Double Sampling
        • were solved on all the Board.
      • Assignment given