Tools for QM

1. Tools for QM

2. HISTOGRAM • A Histogram is used to display in bar graph format measurement data distributed by categories. • USED FOR:-- Making decisions about a product or process that could be improved after examining the variation (example: Should the school invest in a computer-based tutoring program for low achieving students in Algebra I after examining the grade distribution?; are more shafts being produced out of specification that are too big rather than too small?) -- Displaying easily the variation in the process (example: Which units are causing the most difficulty for students?; is the variation in a process due to parts that are too long or parts that are too short?)

3. STEPS IN CONSTRUCTING A HISTOGRAM: • Gather and tabulate data on a product or process. This could be time, weight, size, frequency of occurrences, test scores, pass/fail rates, number of days to complete a cycle, diameter of shafts built, etc. • Calculate the range of the data by subtracting the smallest number in the data set from the largest. Call this value R. • Decide about how many bars (or classes) you want to display in your eventual histogram. Call this number K. • Determine the fixed width of each class by dividing the range, R by the number of classes K. Call this number h, for interval width. Reference for value K in Histogram

4. STEPS IN CONSTRUCTING A HISTOGRAM: • Create a frequency table of upper and lower class limits. The lowest value in the data set minus h/2 amounts to the lower limit of the first class. Add the interval width h to the lower limit of the first class or add h/2 to the lowest data value to determine the upper limit of the first class, which becomes the lower limit of the second class. Adding the internal width (i) to the lower limit of the second class determines the upper limit for the second class. Repeat this process until the largest upper limit exceeds the biggest piece of data. You should have K classes or categories in total. • Sort, organize, or categorize the data in such a way that you can count or tabulate how many pieces of data fall into each of the classes or categories in your table above. These are the frequency counts and will be plotted on the Y axis of the histogram.

5. STEPS IN CONSTRUCTING A HISTOGRAM: • Create the framework for the horizontal and vertical axes of the histogram. On the horizontal axis plot the lower and upper limits of each class determined above. The scale on the vertical axis should run from zero to the first number greater than the largest frequency count determined above. • Plot the frequency data on the histogram framework by drawing vertical bars for each class. The height of each bar represents the number or frequency of values occurring between the lower and upper limits of that class.

6. Example of Histogram • The data below are the spelling test scores for 20 students on a 50 word spelling test. The scores (number correct) are: 48, 49, 50, 46, 47, 47, 35, 38, 40, 42, 45, 47, 48, 44, 43, 46, 45, 42, 43, 47. • The largest number is 50 and the smallest is 35. Thus, the range, R = 15. We will use 5 classes, so K=5. The interval width h= R/K = 15/5=3.

7. Example of Histogram • The completed table (with frequencies tabulated) will look like the following:

8. Pareto’s Diagram • Vilfredo Pareto (1848-1923) discovered that: -- 80% of the wealth in Italy was held by 20% of the population; -- 20% of customers accounted for 80% of sales; -- 20% of parts accounted for 80% of cost, etc. These observations were confirmed by Juran (1960) and resulted in what is known as the Pareto Principle.

9. Pareto’s Diagram • The Pareto Principle states that: "Not all of the causes of a particular phenomenon occur with the same frequency or with the same impact" • Such characteristics can be highlighted using Pareto Charts

10. Pareto’s Diagram • This is a diagram in bar form, which helps determine which problems should be solved and in what order. It gives a visual representation of ranking according to quantitative criteria such as frequency, cost, number of occurrences, result of a vote, etc. • Pareto diagrams show the most frequently occurring factors.

11. Pareto’s Diagram • Steps： 1. Determine the categories of problems or causes to be compared. Begin by organizing the problems or causes into a narrowed down list of categories (usually 8 or less). 2. Select a Standard Unit of Measurement and the Time Period to be studied. It could be a measure of how often something occurs (defects, errors, tardies, cost overruns, etc.); frequencies of reasons cited in surveys as the cause of a certain problem; or a specific measurement of volume or size. The time period to be studied should be a reasonable length of time to collect the data.

12. Steps 3. Collect and Summarize the Data. Create a three-column table with the headings of "error or problem category", "frequency", and "percent of total". In the "error or problem category" column list the categories of problems or causes previously identified. In the "frequency" column write in the totals for each of the categories over the designated period of time. In the "percent of total" column, divide each number in the "frequency" column by the total number of measurements. This will provide the percentage of the total.

13. Steps 4. Create the framework for the horizontal and vertical axes of the Pareto Chart. The horizontal axis will be the categories of problems or causes in descending order with the most frequently occurring category on the far left (or at the beginning of the horizontal line). There will be two vertical axes-one on the far left and one on the far right. The vertical axis on the far left point will indicate the frequency for each of the categories. Scale it so the value at the top of the axis is slightly higher than the highest frequency number. The vertical axis on the far right will represent the percentage scale and should be scaled so that the point for the number of occurrences on the left matches with the corresponding percentage on the right.

14. Steps 5. Plot the bars on the Pareto Chart. Using a bar graph format, draw the corresponding bars in decreasing height from left to right using the frequency scale on the left vertical axis. To plot the cumulative percentage line, place a dot above each bar at a height corresponding to the scale on the right vertical axis. Then connect these dots from left to right, ending with the 100% point at the top of the right vertical axis.

15. Steps 6. Interpret the Pareto Chart. Use common sense-just because a certain problem occurs most often doesn't necessarily mean it demands your greatest attention. Investigate all angles to help solve the problems-What makes the biggest difference? What will it cost to correct the problems? What will it cost if we don't correct this problem? Analysis of Pareto charts help to make best use of limited resources by targeting the most important problems to tackle.

16. Ishikawa diagram • Dr. Kaoru Ishikawa, a Japanese quality control statistician, invented the fishbone diagram. Therefore, it may be referred to as the Ishikawa diagram. The fishbone diagram is an analysis tool that provides a systematic way of looking at effects and the causes that create or contribute to those effects. Because of the function of the fishbone diagram, it may be referred to as a cause-and-effect diagram. The design of the diagram looks much like the skeleton of a fish. Therefore, it is often referred to as the fishbone diagram. • This « fishbone » type diagram is used in problem-solving circles to give a visual representation of the logical sequence of causes (organized into categories) that produce one and the same effect. The diagram is so constructed as to unambiguously classify the ideas and sollicit new ones.

17. Steps: • Distribute the possible causes highlighted into the following five categories (the 5 M ’s) :Machines, Manpower, Methods, Materials, Milieu • The categories can take other names as appropriate to the problem, there may be more or less than 5 categories (preferably no more than 6), however in all cases, the categories must be clearly defined so that all members of the group agree on their meaning. Plot the base of the diagram in the form of a « fishbone »:

18. Steps: • Use an idea-generating technique (e.g., brainstorming) to identify the factors within each category that may be affecting the problem/issue and/or effect being studied. The team should ask... "What are the machine issues affecting/causing..." Generally, on the central fishbone, enter only the direct causes of the effect you are studying. • Repeat this procedure with each factor under the category to produce sub-factors. Continue asking, "Why is this happening?" and put additional segments each factor and subsequently under each sub-factor. • Continue until you no longer get useful information as you ask, "Why is that happening?" • Number each idea on the fishbone diagram, and provide each person with a piece of paper. Each person is to select the five ideas he or she thinks have the most merit in defining the causes, or opportunity, and rank these five from most important to least important. list each team member scores against the idea, and add them up. Select those ideas scored higher.

20. Scatter diagram • Scatter diagrams are used to study possible relationships between two variables. Although these diagrams cannot prove that one variable causes the other, they do indicate the existance of a relationship, as well as the strength of that relationship. • A scatter diagram is composed of a horizontal axis containing the measured values of one variable and a vertical axis representing the measurements of the other variable.

21. Scatter diagram • The purpose of the scatter diagram is to display what happens to one variables when another variable is changed. The diagram is used to test a theory that the two variables are related. The type of relationship that exits is indicated by the slope of the diagram.

22. Scatter diagram: Key terms • Variable - a quality characteristic that can be measured and expressed as a number on some continuous scale of measurement. • Relationship - Relationships between variables exist when one variable depends on the other and changing one variable will effect the other. • Data Sheet - contains the measurements that were collected for plotting the diagram. • Correlation - an analysis method used to decide whether there is a statistically significant relationship between two variables. • Regression - an analysis method used to identify the exact nature of the relationship between two variables.

23. Construction of Scatter Diagram • Collect and construct a data sheet of 50 to 100 paired samples of data, that you suspect to be related. Construct your data sheet as follows:

24. Construction of Scatter Diagram • Draw the axes of the diagram. The first variable (the independent variable) is usually located on the horizontal axis and its values should increase as you move to the right. The vertical axis usually contains the second variable (the dependent variable) and its values should increase as you move up the axis.

25. Construction of Scatter Diagram • Plot the data on the diagram. The resulting scatter diagram may look as follows:

26. Scatter Diagram • The scatter diagram is a useful tool for identifying a potential relationship between two variables. The shape of the scatter diagram presents valuable information about the graph. It shows the type of relationship which may be occurring between the two variables.

27. Scatter Diagram: Example • Situation: The new commissioner of the American Basketball League wants to construct a scatter diagram to find out if there is any relationship between a players weight and her height. How should she go about making her scatter diagram?

28. Scatter Diagram: Example • Collect the data (use 50-100 paired samples).

29. Scatter Diagram: Example • Draw and label your x and y axes.

30. Scatter Diagram: Example • Plot the data on the diagram.

31. Scatter Diagram: Example • Interpret your chart. • According to this scatter diagram the new commisioner was right. There does seem to be a positive correlation between a player's weight and her height. In other words, the taller a player is the more she tends to weight.

32. Scatter Diagram -1  r  +1

33. Flow Chart • Flow charts • have no statistical basis • are excellent visualisation tools • Flow charts show • the progress of work • the flow of material or information through a sequence of operations • Flow charts are useful in an initial process analysis • Flow charts should be complemented by process flow sheets or process flow diagrams (more detailed) if available • Everyone involved in the project should draw a flow chart of the process being studied so as to reveal the different perceptions of how the process operates

34. Run Chart • Run charts are simply plots of process characteristics against time or in chronological sequence. They do not have statistical basis, but are useful in revealing -- trends -- relationships between variables

35. Run Chart This graph shows how a variable has changed over time. By analyzing the data points, an operator can determine if the operation is doing what it is supposed to do. There may be excessive variation in the data, a disturbing trend, or random unacceptable points.

36. SPC • SPC stands for Statistical Process Control • SPC does not refer to a particular technique, algorithm or procedure • SPC is an optimisation philosophy concerned with continuous process improvements, using a collection of (statistical) tools for • data and process analysis • making inferences about process behaviour • decision making • SPC is a key component of Total Quality initiatives • Ultimately, SPC seeks to maximise profit by • improving product quality • improving productivity • streamlining process • reducing wastage • reducing emissions • improving customer service, etc.

37. SPC • Commonly used tools in SPC include -- Flow charts -- Run charts -- Pareto charts and analysis -- Cause-and-effect diagrams -- Frequency histograms -- Control charts -- Process capability studies -- Acceptance sampling plans -- Scatter diagrams • These tools are usually used to complement each other, rather than employed as stand-alone techniques

38. A P C D PDCA: Problem Solving Plan Problem : discrepancy between reality and what is wanted, expected or the objective • 1. Characterise the problem • 2. Analyse the causes • 3. Decide the solutions • 4. Implement the solutions • 5. Check effectiveness • 6. Standardise and generalise Do Check Act

39. Brainstorming • Purpose: As a group, seek as many new and original ideas as possible, without initially worrying whether they are relevant or not. • Method • Each member must be able to freely express all his ideas. • Keep the session fairly short. • Put forward one idea at a time. • Do not criticise any of the ideas mentioned, do not criticise your own ideas. • Jot down all ideas without exception using the exact words used. • Bounce off the ideas of others. • Listen. • Put forward as many ideas as possible (even apparently silly ones).

40. Brainstorming • Advice • -- In this type of creative session, you have to ignore all of the usual constraints or fears (fear of your superiors, fear of sounding ridiculous, of being judged, desire for respect from others). Above all, do not hold back any ideas that might come to mind. • -- The team leader must create an atmosphere that is conducive to the production of ideas. For instance, he can launch the first silly idea... • --The leader must act as a moderator, for instance not allowing everyone to talk at the same time, ensuringthat all have the chance to express their ideas. At the same time, he must not be merely the secretary. • --It is important to maintain a fairly fast rate of idea production. • The session can finish with a round tablewhere after allowing 1 minute to think, each person is asked to put out a new idea.

41. Brainstorming • Example: Solutions for a complete change : - Stop using the vehicle and use an alternative means of transport : . Public transport for weekend shopping trips . Public transport, or a bicycle for short professional journeys - Solutions for continuous improvement : (no change in the actual process) . Stop buying second-hand parts . Replace faulty parts with new parts (quality of the setting, within a guaranteed time).

42. Effective Meeting • 5 – 7 participants • A set objective • Carefully defined roles • Appropriate venue proposed • Good timekeeping • Summary (minutes) Good timekeeping Objective achieved Participants satisfied

43. Effective Meeting • Tools: • Leader presence • voice • gaze • attitude • Practical resources • overhead projector • paper board • documents • Communication tools • questions • post-its • round table • vote • brainstorming • etc. • Method: • Introduction • Agenda • Objective • Plan • Means • Phase One • Synthesis • Phase Two • Conclusion

44. Effective Meeting • Rules: • No meeting without a specific, agreed-upon objective • Concerned participants, peers, from all disciplines • A leader who provides a method, tools and listens • Active participation on the part of all involved • Mututal respect • Production piloted by the leader who guarantees the methods and rigorous time-keeping • A summary (minutes)

45. Effective Meeting • Role of leader: • Prepares & sets objectives for the meeting • Proposes methods and the associated tools to achieve the objectives • Handles, regulates the flows of information • Insists on explanation of vague or ambiguous statements • Controls non-verbal signals • Sums up, or has others sum up • Encourages the expression of ideas • Challenges generalisations • Encourages creative responses, ideas • Protects minority opinions • Instigates a climate of trust

46. Effective Meeting • Role of Participants • Arrives on time • Expresses his opinion, participates • Advances arguments in favor of his ideas • Listens to and respects others • Speaks at the opportune time • Organizes what he says / when he says it • Prepares for the meeting