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Quality and SPC Tools: An Overview

Quality and SPC Tools: An Overview. Quality Product. CM4120. Topics. Quality Advocates Quality Improvement Methodologies Six Sigma Quantitative Tools -Statistical Process Control (SPC) Tools. Process is “in control”?. Pause and Ponder?. What does “quality” mean?

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Quality and SPC Tools: An Overview

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  1. Quality and SPC Tools: An Overview Quality Product CM4120

  2. Topics • Quality Advocates • Quality Improvement Methodologies • Six Sigma • Quantitative Tools -Statistical Process Control (SPC) Tools Process is “in control”?

  3. Pause and Ponder? • What does “quality” mean? • Why is it important today? • How is the world changing? Anybody? Table Topic: Auto industry changes in the 1970’s!

  4. Short Answers! • Quality = “..what the customer wants!” • Companies cutting costs! • Global competition!

  5. Quality Advocates • People who proclaimed the importance of quality • Seven individuals dominant in this area: • Each known for different subject area • All agree that quality is critical to the long term success of industries in today’s global environment!

  6. Quality Basics • Quality (defined) • Characteristics of a product or service that bear on its ability to satisfy stated or implied needs • A product or service free of deficiencies • Customer determination • Only a customer can decide if, and how well a product meets their needs, expectations, requirements

  7. Ingredients for Success • Corporate Culture • Process Improvement • Variation • Productivity MINIMIZE! MAXIMIZE!

  8. Variation • Based on assumption that: • no two products (or occurrences) are exactly alike • variation is always present • Identified as difference between specified target value and the actual value obtained • Minimizing variation results in production of higher quality products

  9. Variation • Specifications • State product characteristics in terms of a desired target value • Tolerance Limits • Show the permissible changes in the value of a quality characteristic • Processes must be stable (minimize variation) • Process is “under control” when variation or variability is stable and predictable

  10. Productivity • Different from quality • Principal focus is on: • Working efficiently • Utilizing resources effectively • Examples: • Produce 10,000 units in 15 hours instead of 18 hours • However, must keep quality of products the same! Can you increase productivity while meeting quality standards set?

  11. SPC Advantages (summarized) • Uniform output • Reduced rework • Fewer defective products • Increased profit • Lower average cost • Fewer errors • Less scrap • Increased job satisfaction • Factual information for decision making • Increased customer satisfaction And more!

  12. Variation • Controlled Variation • Also called “common causes” • Variation due to nature of the process • Can only be removed by changing the process • Uncontrolled Variation • Also called “special causes” • Comes from sources external to process

  13. Six Sigma • What is it? • Term used to indicate a process is well controlled i.e., +/- 3 sigma from the centerline in a control chart • Often associated with Motorola (named one of its key operational initiatives “Six Sigma Quality”) Made famous by GE (Jack Welch)!

  14. Six Sigma • A management program? • (YES!) • Not primarily a technical program? • (YES!) • Technical proficiency indicated by a “belt system” (similar to Karate)? • (YES! Can you say Six Sigma Blackbelt?) Six Sigma Handbook is recommend! (See reference slide at end of presentation)

  15. Six Sigma • Greenbelts • Intermediate levels of experience • Blackbelts • Advanced levels of experience Based on dollar amounts of projects completed, years of experience quality training, etc.

  16. PDSA CYCLE

  17. SPC TOOLS HERE! SPC TOOLS HERE!

  18. TOOL 1 Check Sheets • “is a data recording device” Example: Automobiles arriving damaged Nonconformity Number Dented during shipping 3 Mechanical failure (engine) 12 Tires flattened 11 Windows broke 55 Missing molding 44

  19. Check or Tally Sheets • Data (outdoor temperature, oF) • (for 24 hour period) • 55 II • 56 IIII IIII II • 57 IIII IIII • 58 IIII I • 59 III • 60 II Number of occurrences Temperature

  20. Equipment Material Problem Environment Methods People Information Cause-and-Effect Diagrams“Fishbone Diagrams” TOOL 2 • “helps identify causes for nonconforming or defective products”

  21. Cause-and-Effect DiagramsEXAMPLE! • Forklift tire replacement in a plant! Material Equipment Defective? Chemical Resistant? Hot? Tires replaced Frequently! Environment Wreckless? Training? Maintenance? People Methods Information

  22. Flowcharts TOOL 3 • Graphical representation of all of the steps involved in an entire process or part of a process • Creating a flowchart • STEP 1 = Define process steps • STEP 2 = Sort steps in order of importance • STEP 3 = Place steps in “flow chart symbols” • STEP 4 = Evaluate steps for completeness What do the symbols look like?

  23. Flowcharts storage operation Symbols typically used! inspection delay transportation decision

  24. Figure 3-9 (Summers)

  25. Data Collection • Pause and ponder • What about SPC tools which require data sampling? • Is sampling technique used important? • ANSWER = YES!!!!! YES!!!! YES!!!!

  26. Populations vs. Samples • Population = “collection of all possible elements, values, or items associated with a situation” • Sample = “a subset of elements or measurements taken from a population” • Sample will represent the population ONLY if the sample is random (unbiased). NOTE: MORE DIFFICULT THAN IT SOUNDS!

  27. Data Collection • Statistics-Types • 1.) Deductive = describe a population or complete group of data • 2.) Inductive = deal with a limited amount of data or a sample • Data Types • 1.) Variables Data = quality characteristics which can be measured • 2.) Attribute Data = quality characteristics which are present or absent, conforming or nonconforming Can use SPC tools with “attribute data”!

  28. Data Analysis • Using statistics to define the location and spread • Location: • Central Tendency • Mean • Mode • Median • Spread: • Range • Standard Deviation Histograms at a glance! Let’s go to the board and discuss the basics!

  29. TOOL 4 Scatter Diagrams • “graphical technique that is used to analyze the relationship between two different variables” Negative or positive correlation shown? Y (defects) X (processing time)

  30. TOOL 4 Scatter Diagrams • “graphical technique that is used to analyze the relationship between two different variables” Negative or positive correlation shown? Y (defects) X (processing time)

  31. TOOL 4 Scatter Diagrams • “graphical technique that is used to analyze the relationship between two different variables” No correlation shown! Y (defects) X (processing time)

  32. Frequency Diagrams! 500 Frequency 300 100 Interval (classes) Histograms TOOL 5 • “graphical summary of the frequency of distribution of data”

  33. Histograms • Very similar to Frequency Diagrams • Have cells with ranges of data/values • Cells often called “bins” ! • Constructing Histograms • Step 1: Collect data and make tally sheet • Step 2: Calculate the “range”(R) • (R = highest value - lowest value) • Step 3: Create cells (must choose number to create) Rules of Thumb : fewer than 100 pieces of data use 4 to 9 cells, 100 to 500 use 8 to 17 cells, more than 500 use 15 to 20 cells

  34. Histograms • Constructing Histograms • Step 4: Label the Axes • Step 5: Post values (move from Tally Sheet to Histogram) • Step 6: Interpret the Histogram (look at shape!) • Shape? • Location? • Spread? Can tell you a lot! 500 Can make using ExcelTM! Frequency 300 100 Interval (classes)

  35. Pareto Charts • Developed by “Pareto” • Vilfredo Pareto • Italian economist • Start with check or tally sheets • Used to develop the “80-20 rule” • 80% of dollars lost due to quality problems can be attributed to 20% of the quality problems!

  36. Pareto Charts TOOL 6 • “graphical tool for ranking causes of problems from most significant to least significant” Frequency Diagrams! 300 Frequency 200 100 Problems (classes)

  37. Pareto Charts • Example: Automotive speedometer problems 300 Frequency 200 100 Loose wires Inaccurate Inoperative Needle bounce Improper install Other

  38. Control Charts TOOL 7 • “chart with a centerline showing the average of the data produced” UCL Temp Centerline LCL Date

  39. Run Charts • “similar to control charts however they follow a process over time, reflected on the X-axis” UCL Temp Centerline LCL Time

  40. Control Chart Functions • 1.) Provide a “decision making tool” • Adjust the process? • Leave process alone? • Investigate further? • Can provide information for timely decisions (i.e., can provide information regarding recent changes in process good or bad!) • Used to determine “process capability” Important to process industries!

  41. Control Chart Functions • 2.) Are problem solving tools • Used to identify problems • Used to locate problems • Can be used to determine when a process should be adjusted • Summary: Control Charts used for “decision making” and “problem solving”

  42. Variation • Definition: “where no two items or services are exactly the same” • Goal: Produce products with as little variation as possible • Note: We will consider “measurable variation” • Three types: • 1 within-piece variation • 2 piece-to-piece variation • 3 time-to-time variation

  43. Causes of Variation • Common (or Chance) Causes • Random changes in process which cannot be avoided • Due to inherent variation in all processes • Only removable by making changes in process • Special (or Assignable) Causes • Large variations in the process that can be identified as having a specific cause • Causes which are not “normal” to the process NOTE: THIS IS IMPORTANT TO KNOW! ANY QUESTIONS?

  44. Control Charts • Centerline (CL) • Shows where process average is centered or central tendency of data • Upper Control Limit (UCL) • Describes upper end of spread of data • Lower Control Limit (LCL) • Describes lower end of spread of data • Control Chart Variables • Measurable characteristics of a product or service Can you identify the UCL, CL, and LCL on this chart?

  45. X and R Charts • Used to monitor the variation of the subgroup averages that are calculated from the individual sampled data • Steps • 1 Define problem • 2 Select characteristic to be measured • 3 Choose a rational subgroup size to be sampled • (NOTE: Subgroup must be “homogenous”, i.e., sampled under same conditions, same machine, etc.) • 4 Collect data • 5 Determine the trial centerline for the X chart

  46. X and R Charts • Steps • 6 Determine trial control limits for the X chart • 7 Determine the trial control limits for the R chart • 8 Examine the process (control chart interpretation) • State of Process Control • Process is considered “in control” or “under control” when the performance of the process falls within the statistically calculated control limits • Process exhibits only “common causes”

  47. X and R Charts • NOTE: Equations for determining UCLx, LCLx, MEANx, UCLr, LCLr, MEANr are provided in numerous “quality” textbooks • Range Charts • Method of determining amount of variation in individual samples • X Charts • Used to evaluate the variation from subgroup to subgroup EASY TO DO!

  48. X BAR CHART 10.15 UCLx Mean 9.00 LCLx 8.15

  49. R CHART 10.00 UCLr Mean 5.00 0.00 Can also make X bar and s charts! (Similar, more accurate)

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