1b7 quality control
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This document discusses total quality management and continuous quality improvement. It covers quality planning, quality control, and quality improvement. Quality planning involves understanding customer needs. Quality control includes inspection, process control, and correction. Quality improvement aims to establish infrastructure. Common quality control tools are discussed like check sheets, Pareto charts, why-why diagrams, flowcharts, and control charts. Problem solving uses the plan-do-study-act cycle. Quality circles link these approaches.
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1b7 quality control
- 2. QUALITYPLANNING Whoiscustomer? Whatdotheyneed? QUALITYCONTROL Evaluate,compare,act QUALITY IMPROVEMENT Establishinfrastructure Who is customer? What Level of Quality do they need? Are they purchasing to Some Quality Specification? Any Safety Considerations? Future Litigation? Ethical Issues?
- 3. QUALITYPLANNING Whoiscustomer? Whatdotheyneed? QUALITYCONTROL Evaluate,compare,act QUALITY IMPROVEMENT Establishinfrastructure QUALITY CONTROL Inspection • Destructive • Non-destructive • Sampling Process Control • Monitoring Process (relates to inspection) • Feedback Control • Statistical Process Control (knowing when the process is out of control) Correction • Knowing what to correct when process is out of control
- 4. Cost of Quality Before & After Improvement 0 10 20 30 40 50 60 70 80 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 Time Series 1
- 5. Tools for Quality Control Check Sheets Pareto Charts Why-Why Diagrams Cause & Effect Diagrams Flowcharts Histograms Scatter Diagram Control Charts
- 7. CHECK SHEETS Used to keep a record of the number and type of discontinuities over a specified period of time or within a certain batch of product. PARETO CHART A graphical representation ranking discontinuities from the most to least significant. Used to help brainstorm what discontinuities, if worked upon first, would be the most likely to produce the greatest improvement in quality. Class Example Our manufacturing procedure is composed of several steps. Several of these procedures have lead to discontinuities noticed upon inspection. The steps causing defectives are as follows: ∀• Caulking 198 defectives ∀• Fitting 25 defectives ∀• Connections 103 defectives ∀• Torque 18 defectives ∀• Gapping 72 defective A Pareto Diagram will be developed.
- 10. WHY-WHY DIAGRAMS A systematic representation of causes of why some occurrence happens. Used to guide brainstorming sessions.
- 12. FLOW CHARTS Flow charts are graphical representations of the steps involved in a process. Constructing a flow chart helps give a better understanding of the systems involved. Process DecisionData Process Process Terminator Yes No Control transfer
- 13. CAUSE AND EFFECT DIAGRAMS (Fishbone Diagram) Used in brainstorming session to help identify the causes of quality losses. This diagram is particularly useful after the flow chart and the Pareto diagrams have been developed. QUALITY (Effect)Cause Step 1:Decide on the quality characteristic {e.g. Reduction of wobble during machine rotation} Step 2:Set up the fish bone backbone Step 3:Identify main factors causing effect {e.g. Workers, Materials, Inspection, Tools} Step 4: Add Cause to each branch
- 15. Benefits of Cause and Effect Diagram • Making diagram is educational in itself • Outline relationship • Note what samples need to be taken • Guide for discussion • Causes are actively sought and results written on diagram • Appropriate data collected - no time wasted • Shows level of technology
- 17. CONTROL CHARTS • Used to test if the process is in control • Used to see if significant changes have occurred in the process over time “Indiscreet” or “Continuous Data Chart” or “X-R Chart” Measurement at time intervals Measurements compared - control over time. Examples: Length (mm) Volume (cc) Weight (gm) Power (kwh) Time (sec) Pressure (psi) Voltage (v) “Discrete Data Charts” or “pn-p charts” Inspection on lot or batch Note # good/defective # of parts inspected in the lot = n Fraction of defective in lot = p Number of defectives = pn
- 18. - R CHART CONSTRUCTIONX In the manufacturing process for this example parts are being machined with a nominal diameter of 13 mm. Samples are taken at the following times of day: 6:00, 10:00, 14:00, 18:00 and 22:00, for 25 consecutive days. The diameter measurements from these samples are presented on the table in the next slide. Class Example
- 20. Step 1: Collect Data Step 2: Sort data into subgroups (i.e. lots, order #, days, etc.) n = size of the subgroup {in this example 5 times per day) k = number of subgroups {in this example 25 days} Step 3: Find the mean for each subgroup ( X ) X = X X X X n n1 2 3+ + +..... Step 4: Find Range for each subgroup ( R ) R = X largest value - X smallest value
- 21. Step 5: Find Overall Mean ( X ) X = X X X X k k1 2 3+ + +... Step 6: Find average value of range ( R ) R = R R R R k k1 2 3+ + +... Step 7: Complete control limits using attached table For X Control Chart Central Line - CL = X Upper Control Limit - UCL = X +A2 R Lower Control Limit - LCR = X - A2 R For R Control Chart Central Line - CL = R Upper Control Limit - UCL = D4 R Lower Control Limit - LCR = D3 R
- 25. P CONTROL CHART CONSTRUCTION An inspector at the end of the manufacturing line for the production of car wheel rims, at the end of each shift, inspects the lot of wheel rims made during that shift. On good days when the welder is running properly, over 400 wheels are made per batch. On poor days, as low as 50 to 60 wheels are made per batch. The inspector marks on his/her “check sheet” for each batch the total number of wheels inspected and the number of defects returned for rework in each lot. Class Example
- 27. Step 1: Collect Data Step 2: Divide data into subgroups (usually days or lot). Subgroup size should be greater than 50 units. n = number in each subgroup pn = number of defects in each subgroup Step 3: Compute fraction of defectives (for %, multiply by 100) p = pn/n Step 4: Find the Average Fraction of Defectives ( p ) p = ( ) ( ) total defectives total inspected = pn n ∑ ∑ Step 5: Compute the Control Limits for each Lot Central Line CL = p Upper Control Limit UCL = p + 3 p p n ( )1− Lower Control Limit LCR = p - 3 p p n ( )1−
- 28. Step 6:Draw P Control Chart
- 29. PN CONTROL CHART CONSTRUCTION Class Example On an assembly line of windshield wiper motors, the inspector selects randomly 100 motors per hour to examine. The inspector notes on the “check sheet” the number of defective motors in each 100 selected.
- 30. Step 1: Collect Data (lot size set constant) Step 2: Calculate Values p = ∑ ∑ n pn CL = p n UCL = p n + 3 pn p( )1− LCL = p n - 3 pn p( )1− Step 3: Plot Chart