1. BUILDING FROM THE BASICS GROUP B GROUP MEMBERS:ABIRA IMRAN HIRA ISHAQUE MARYAM YOUNUS SADIA QAYYUM SANA SHAKIL

2. ABIRA IMRAN TOPICS THAT I WILL PRESENT ARE:  INTRODUTION OF TO OUR TOPIC.  HISTOGRAM.

3. INTRODUCTION: BUILDING FROM BASICS

4. QUALITY ? Quality is a consumer decision factors in the selection among competing product s and services. “Quality is relating to one and more desirable characteristics that a product or service should posses.” “Quality means conformance to valid customer requirements.” QUALITY IS THE WAY OF LIFE

5. QUALITY CONTROL? Quality Control is about :  How to make things better.  Uncovering a problem and finding the solutions.  Improve the product quality and reduce process variability.  Identifies specifications to which the product or service must conform in order to be of value to the consumer.

6. TOTAL QUALITY MANAGEMENT: Total quality management focus on:  Customer driven quality standards.  Managerial leadership.  Continuous improvement.  Process design

7. CATEGORIES OF TQM:  Descriptive statistics.  Acceptance sampling.  Statistical process control.

8. HISTORY OF SPC: Kaoru Ishikawa.  He is from university of Tokyo.  Known for “Democratizing Statistics”.

9. STATISTICAL PROCESS CONTROL (SPC):  DEFINITION: “ Statistical process control (SPC) is the application of statistical techniques to determine whether the output of a process conforms to the product or service design. “

10. WHAT SPC SEEKS TO?? SPC seeks to maximize profit by:  Improving product quality.  Increasing productivity.  Reducing waste.  Reducing defects.  Improving customer value.

11. STATISTICAL PROCESS CONTROL TOOLS ARE:  HISTOGRAM.  PARETO ANALYSIS.  CHECK SHEET.  SCATTER PLOT.  CAUSE AND EFFECT DIAGRAM.  CONTROL CHARTS.  STRATIFICATION.

13. HISTOGRAM

14. HISTORY:  Pearson was a scientist in victorian London.  A.M Guerry published a histogram in 1833.  Karl Pearson first used the histogram in 1891.

15. DEFINITION: “Histogram is one of a graphical technique to display tabulated frequencies. It illustrates what proportion of cases fall into each of several categories.”

16. USES OF HISTOGRAM:  Relationship identification.  Factor effect determination.  Outlier detection.  Shows distribution.

18. WHEN WE USE HISTOGRAM?  To summarize large data sets graphically.  Compare measurement to specification.  Want to see the shape of distribution.  Analyze process according to customer’s requirement.  Analyzing what the output from a supplier’s process look like.

19. SADIA QAYYUM  CHECK SHEET.  PARETO ANALYSIS

20. CHECK SHEET Utilizing Check Sheets to Improve Quality

21. CHECK SHEETS  What is a check sheet?  A basic tool for monitoring quality improvement processes  A simple data collection device  There are two varieties of check sheets  Tabular  Schematic

22.  COMMON TYPES,  Cause Check Sheets  Used to keep track of how often a problem happens or records the cause to a certain problem.  Classification Check Sheets  Used to keep track of the frequency of major classifications involving the delivery of products or services

23. Check Sheet - Example 1. Identify Objective 2. Decide time period 3. Design Check Sheets 4. Test Data 5. Collect the data 6. Interpret results

24. BENEFITS:  Efficiency/Speed  Systematic and Organized  Ease of use/Simplicity  Can be used in conjunction with other charts and diagrams for a more in depth analysis

25. CHECK SHEET EXAMPLE The figure below shows a check sheet used to collect data on telephone interruptions. The tick marks were added as data was collected over several weeks.

27. PARETO ANALYSIS

28. The Pareto effect is named after Vilfredo Pareto, an economist and sociologist who lived from 1848 to 1923. H İ STORY OF PARETO ANALYS İ S

29.  This technique helps to identify the top 20% of causes that needs to be addressed to resolve the 80% of the problems.

30. WHAT IS IT FOR? WHERE COULD WE USE IT?  selecting problems, causes or solutions.  visibly demonstrate priorities.  method of comparing and sorting.  ’80/20 Rule’ to select the ‘vital few’

31. THE PARETO CHART A Pareto chart is a graphical representation that displays data in order of priority.

32. Identify items to compare.  Plan the measurement  Plot the chart.  Select the focus.  Take actions.  Plot the chart HOW DO WE USE IT?

33. EXPECTED BENEFITS: Pareto Analysis helps you focus on the most important actions and thus leads to the best solutions and the optimum return from your efforts and investments.

34. SANA SHAKIL  SCATTER PLOT.  CAUSE AND EFFCT DIAGRAM.

35. SCATTER DIAGRAM GRAPHICAL PRESENTATION OF THE DATA TO IDENTIFY PATTERNS OR RELATIONSHIP

36. INTRODUCTION:  Sometimes two separate things appear to change together and there may be suspicion that they are related somehow.  The Scatter Diagram visually shows how well correlated they are.  The Japanese guru Kaoru Ishikawa included Scatter Diagrams as one of his 7 basic tools.

37. DEFINITION: “ A scatter plot or scatter graph is a type of mathematical diagram using Cartesian coordinates to display values for two variables for a set of data”.

38. BENEFITS:  One advantage of the scatter plot is that a number of measurement strategies can be used including frequency counts, duration, or latency recording.  Another way to record the data is to indicate low rates of occurrence with one symbol and higher rates of responding with a different code.  The exact number of behaviors can also be written into the cells to provide more detailed information

39. WHEN WE USE SCATTER PLOTS?  Use it to provide an input to cause and effect analysis.  Identify the purpose.  Determine the two factors to compare.

40. GRAPH:

41. GRAPHS SHOWING TYPES OF CORRELATION BETWEEN VARIABLES:

42. CAUSE AND EFFECT DIAGRAM :

43. INTRODUCTION:  Ishikawa diagrams (also called fishbone diagrams, herringbone diagrams, cause-and-effect diagrams, or Fishikawa) are causal diagrams created by Kaoru Ishikawa (1968) that show the causes of a specific event.causal diagramsKaoru Ishikawacauses  Common uses of the Ishikawa diagram are product design and quality defect prevention, to identify potential factors causing an overall effect.product design  Each cause or reason for imperfection is a source of variation.

44. DEFINITION: “ A diagram that shows the causes of an event and is often used in manufacturing and product development to outline the different steps in a process, demonstrate where quality control issues might arise and determine which resources are required at specific times”.

45. BENEFITS:  Helps determine root causes  Indicates possible causes of variation  Increases process knowledge

46. WHEN WE USE CAUSE AND EFFECT DIAGRAM?  To identify the possible root causes, the basic reasons, for a specific effect,problem or condition.  To analyze existing problems so that corrective action can be taken.

47. GRAPH:

49. HIRA ISHAQUE  CONTROL CHARTS.  STRATIFICATION.

50. CONTROL CHARTS

51. HISTORY OF CONTROL CHARTS:  Developed in 1920 by Dr. Walter A. Shewhart.  Shewhart worked for Bell telephone labs.

52. DEFINITION: “ Control charts are statistically based graphical tools used to monitor the behavior of the process”.

53. BENEFITS: Control charts helps us to :  Quantify the variation of a process.  Center a process.  Monitor a process in real time.  Determine whether to take action on a process.

55. TYPES OF CONTROL CHARTS: Two types of control charts,  Variable control charts.  Attribute control charts.

56. VARIABLE CONTROL CHARTS:  Deal with items that can be measured.  Examples 1) Weight 2) Height 3) Speed 4) Volume

57. TYPES OF VARIABLE CONTRL CHARTS:  X-Bar chart.  R chart.

58. VARIABLE CONTROL CHART:  X chart: deals with a average value in a process

59. VARIABLE CONTROL CHART:  R chart: takes into count the range of the values

60. ATTRIBUTE CONTROL CHARTS: “ Control charts that factor in the quality attributes of a process to determine if the process is performing in or out of control”.

61. TYPES OF ATTRIBUTE CONTROL CHARTS:  P chart.  C Chart.  U Chart.

62. ATTRIBUTE CONTROL CHARTS:  P Chart: a chart of the percent defective in each sample set.

63. ATTRIBUTE CONTROL CHARTS:  C chart: a chart of the number of defects per unit in each sample set.

64. ATTRIBUTE CONTROL CHARTS:  U chart: a chart of the average number of defects in each sample set.

65. STARTIFICATION

66. HISTORY: “ It was introduced by Kaoru Ishikawa who in turns was influenced by a series of lectures”.

67. DEFINITION: “ Stratification is a technique used in combination with other data analysis tools. When data from a variety of sources or categories have been lumped together, the meaning of the data can be impossible to see. This technique separates the data so that patterns can be seen ”.

68. WHEN TO USE STRATIFICATION:  Before collecting data.  When data come from several sources or conditions, such as shifts, days of the week, suppliers or population groups.  When data analysis may require separating different sources or conditions.

69. STRATIFICATION PROCEDURE  Which information should be selected.  When plotting or graphing use different marks or colors to distinguish data from various sources.

70. STRATIFICATION EXAMPLE:

71. STRATIFICATION CONSIDERATIONS  Here are examples of different sources that might require data to be stratified:  Equipment  Shifts  Departments  Materials  Suppliers  Time of day  Survey data usually benefit from stratification.  Always consider before collecting data whether stratification might be needed during analysis.

72. CONCLUSION:  Above seven basic quality tools help you to address different concerns in an organization.  Therefore, use of such tools should be a basic practice in the organization in order to enhance the efficiency.  Trainings on these tools should be included in the organizational orientation program, so all the staff members get to learn these basic tools.