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Materials Management Systems

Materials Management Systems. Understanding Variation Chapter 16. Chapter 16: TQM Why Quality is Important. Costs and market share Company’s reputation Product liability International implications. Chapter 16: TQM What is Quality?. Conformance to requirements? Zero defects?

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Materials Management Systems

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  1. Materials Management Systems Understanding Variation Chapter 16 MGMT 375

  2. Chapter 16: TQMWhy Quality is Important • Costs and market share • Company’s reputation • Product liability • International implications MGMT 375

  3. Chapter 16: TQMWhat is Quality? • Conformance to requirements? • Zero defects? • Fitness for use? • Consistency? • “I can’t define it, but I know it when I see it”? MGMT 375

  4. Chapter 16: TQMGarvin’s 8 Dimensions of Quality DimensionMeaning Performance Primary operating characteristics. Features Secondary operating characteristics, added touches. Reliability Extent of failure free operation. Durability Amount of use before replacement is preferable to repair. Consistency Uniformity around a target Serviceability Resolution of problems and complaints. Aesthetics Subjective characteristics that relate to senses. Perceived Quality Indirect measures or inferences: reputation. MGMT 375

  5. Chapter 16: TQMWhat is Quality? Quality means user satisfaction: that goods and services satisfy the needs and expectations of the user. Arnold MGMT 375

  6. Why Improve Quality? MGMT 375

  7. Chapter 16: TQMQuality Chain Reaction MGMT 375

  8. Chapter 16: TQMTwo Ways to Improve Quality MGMT 375

  9. Chapter 16: TQMSources of Improvement MGMT 375

  10. Ch.16: Statistical Quality ControlProcess Definition • Process:“A ‘process’ is any set of conditions, or set of causes, which work together to produce a given result. In its narrowest sense the term ‘process’ refers to the operation of a single cause. In its broadest sense it may refer to the operation of a very complicated ‘cause system.’ Reference: Statistical Quality Control Handbook, Western Electric MGMT 375

  11. Ch.16: Statistical Quality Control • Statistical: With the help of numbers or data • Quality: we study the characteristics of our process • Control: In order to make it behave the way we want it to behave. Reference: Statistical Quality Control Handbook, Western Electric MGMT 375

  12. Ch.16: Understanding Variation • Variation exists in everything • Understanding variation is the key to improving quality • Two Kinds of Variation • Chance variation • Assignable variation MGMT 375

  13. Cause and Effect Diagrams Measurement Methods Materials Process Doc. Desired Effect or Undesired Effect PM Motivation Training Machines Manpower Environment MGMT 375

  14. Statistical Process Control (SPC) • Chance variations are the many sources of variation within a process that is in statistical control. They behave like a constant system of random chance causes. • If only natural causes of variation are present, the output of a process forms a distribution that is stable over time and is predictable. MGMT 375

  15. Statistical Process Control (SPC) • Assignable variation in a process can be traced to a specific reason. • Machine wear • Misadjusted equipment • Fatigued or untrained workers • If assignable causes of variation are present, the process output is not stable over time and is not predictable. MGMT 375

  16. SPC - Assignable Causes The operational definition of assignable variation is variation that causes out-of-control points on a control chart. MGMT 375

  17. Ch.16: Statistical Quality ControlNatural Patterns or Variations Natural patterns exhibit the following characteristics: • Most of the points are near the centerline. • A few points spread out and approach the control limits. • None (or only on rare occasions) of the points exceeds the control limits. Reference: Statistical Quality Control Handbook, Western Electric MGMT 375

  18. Ch.16: Statistical Quality ControlUnnatural Patterns or Variations Unnatural patterns exhibit the following characteristics: • Absence of points near the centerline produces a pattern known as a “mixture.” • Absence of points near the control limits produces an unnatural pattern known as “stratification.” • Presence of points outside of the control limits produces an unnatural pattern known as “instability.” Reference: Statistical Quality Control Handbook, Western Electric MGMT 375

  19. Ch.16: Statistical Quality ControlTests for Unnatural Patterns • Instability • A single point falls outside of the 3 sigma control limits. • Two out of three successive points fall in the outer one third of the control limits. • Four out of five successive points fall in the outer two thirds of the control limits. • Eight successive points fall on one side of the centerline. • Systematic variable • A long series of points are high, low, high, low without interruption. Reference: Statistical Quality Control Handbook, Western Electric MGMT 375

  20. Statistical Process ControlWhy use averages? • To create a normal distribution • Averages are more sensitive to change than individuals MGMT 375

  21. Mean The Process (2 of 2) • The distribution of a process’ output has a mean, , and a standard deviation, ; it can have a wide variety of shapes Processdistribution MGMT 375

  22. Process Capability (1 of 3) • When selecting a process to perform an operation, the inherent variability of process output should be compared to the range or tolerances allowed by the designer’s specifications MGMT 375

  23. LowerSpecification UpperSpecification Much of the process output fits within specification width Almost all of the process output fits within the specification width A significant portion of the process output falls outside of the specification width Process Capability (2 of 3) process distribution In other words, is the process capable of producing the item within specifications? MGMT 375

  24. Process Capability (3 of 3) • The process capability index (cp) compares the design specifications with a measure of process variability MGMT 375

  25. Lower designspecification Upper designspecification -3 Sigma mean +3 Sigma Three-Sigma Quality 1350 ppm 1350 ppm MGMT 375

  26. Lower designspecification Upper designspecification -3 Sigma mean +3 Sigma -6 Sigma +6 Sigma Three-Sigma Quality vs.Six-Sigma Quality 1350 ppm 1350 ppm 1.7 ppm 1.7 ppm mean MGMT 375

  27. Process Control (1 of 6) • Once a process is in operation, a goal is to maintain the status quo, i.e., keep the process “in control” • What can make the process no longer be in control, i.e., go “out of control”? • The presence of an assignable cause • The presence of an assignable cause may cause the process distribution to • shift to the left or right, and/or • increase the variability (flatten out) MGMT 375

  28. Time lower design specification upper design specification Process Control (2 of 6) • If the process mean shifts, more of output falls outside the specifications MGMT 375

  29. Time upper design specification lower design specification Process Control (3 of 6) • If the process mean shifts, more of output falls outside the specifications • If process variance increases, more of the output falls outside of the specifications MGMT 375

  30. Process Control (4 of 6) • In either case, the process is considered to be out of control • It should be stopped, investigated (the assignable cause found if present) and corrected (the process brought back to the status quo) MGMT 375

  31. Process Control (5 of 6) • Examples of assignable causes include • operator • raw material • equipment • environment MGMT 375

  32. Process Control (6 of 6) • How does management detect the presence of an assignable cause? • Process output is monitored to detect any changes by inspecting the output of the process • Inspection means assessing some characteristic of a unit of output MGMT 375

  33. Central Limit Theorem Simulation The distribution of a sample approaches normal even when the parent population is not normally distributed. MGMT 375

  34. Statistical Process Control • Tolerance or specification limits • Defined by an engineer • Related to product design requirements • Control limits • Defined by the process • Related to the variation in the process • Unrelated to product needs MGMT 375

  35. LowerSpecification UpperSpecification Much of the process output fits within specification width LowerSpecification UpperSpecification Almost all of the process output fits within the specification width LowerSpecification UpperSpecification A significant portion of the process output falls outside of the specification width Process Capability In other words, is the process capable of producing the item? MGMT 375

  36. /2 /2 Mean LCL UCL Probabilityof Type I error Type I Error MGMT 375

  37. Types of Sampling Errors MGMT 375

  38. Abnormal variationdue to assignable sources Out ofcontrol UCL Mean Normal variationdue to chance LCL Abnormal variationdue to assignable sources 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Sample number Control Chart MGMT 375

  39. 1 2 3 4 Observations from Sample Distribution UCL LCL Sample number MGMT 375

  40. Data Types • Attribute - characteristic evaluated generates data that are counted (good or bad, yes or no). • Variable - characteristic evaluated can be measured within a range of values MGMT 375

  41. UCL x-Chart LCL UCL LCL Mean and Range Charts (process mean is shifting upward) Sampling Distribution Detects shift Does notdetect shift R-chart MGMT 375

  42. UCL Does notreveal increase x-Chart LCL UCL Mean and Range Charts Sampling Distribution (process variability is increasing) R-chart Reveals increase LCL MGMT 375

  43. Variables and Attributes • Attributes data refers to quality characteristics that either conform to specification or do not (examples: visual inspection for color, missing parts, scratches, go-no-go gauging) Either the part is within tolerance or it is not. MGMT 375

  44. Control Charts for Variables • The purpose of control charts is to help distinguish between chance variations and variations due to assignable causes. • Variables are characteristics that have continuous dimensions. • Control charts for the mean, (x-bar), and the range, (R), are used to monitor processes that have continuous dimensions. MGMT 375

  45. Control Charts for Variables • The x-bar chart tells whether changes have occurred in the central tendency of a process. • The R-chart values indicate that a gain or loss in uniformity has occurred. MGMT 375

  46. Parameters • Two basic parameters used: • Mean - measure of central tendency • Range - measure of dispersion • The range is defined as the difference between the largest and smallest items in one sample. MGMT 375

  47. Control Charts for Attributes • Attributes are typically classified as defective or nondefective. • Two kinds of attribute control charts: • Those that measure the percent defective in a sample -p-charts. • Those that count the number of defects per unit of output - c-charts. MGMT 375

  48. Tolerances • Tolerances are limits of deviation from perfection and are established by the product design engineers to meet a particular design function • Both the USL and LSL are related to the product specification and are independent of any process. MGMT 375

  49. Two Types of Defect • Excessive Spread, Incapable Process • Range • Standard deviation • Mean Shift • Both the USL and LSL are related to the product specification and are independent of any process. MGMT 375

  50. Variables and Attributes • Variables data can be measured on a continuous scale (examples: weight, dimensions, pH, temperature, pressure, etc.) MGMT 375

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