7 QC Tools

1. 7 QC Tools

2. Basic QC Tools 1. Pareto Diagram 2. Cause & Effect Diagram 3. Graph 4. Check Sheet 5. Scatter Diagram 6. Histogram 7. Control Chart 7 Tools

3. Pareto Diagram • Pareto charts are a type of bar chart in which the horizontal axis represents categories of interest, rather than a continuous scale. The categories are often “defects.” • This tool is based on the idea that the majority of defects are caused by few defective item, which classifies the quality problem into the “vital few” and “trivial many” (80-20 rule). • A cumulative percentage line helps you judge the • added contribution of each category. • Pareto charts can help to focus improvement efforts on • areas where the largest gains can be made.

4. 80-20 rule Example Figure 1 : Example of Pareto diagram

5. Procedure 1. Decide on the problem to be addressed or items to study and collect data. 2. Decide also the period for which the data is to be collected. 3. Arrange the data in order of decreasing size. 4. Calculate the cumulative number and percentage. 5. Draw horizontal and vertical axes on graph paper. 6. Draw the bar graph. 7. Draw the vertical axis on the right edge and scale it. 8. Draw the cumulative curve. Complete the diagram with titles and units of reference.( Figure 1)

6. Cause and Effect Diagram • The cause and effect diagram analysis was first developed by Professor Kaoru Ishikawa of the University of Tokyo in the 1940s’, is also known as the ‘Fishbone Diagram’ or the ‘Ishikawa Diagram’. • His first application of this technique was in the Fulsai iron work 1953. Due to its’ final form, some people called it the “Fishbone Diagram”. • This tool is a picture of lines and symbols designed to represent the relationship between the effects as problems and the causes influencing them. • There is no “correct” way to construct a fishbone diagram, some types lend themselves well to many different situations.

7. Factor Small bone Effect Backbone Middle bone Example Figure 2 : Example of Cause and Effect Diagram

8. Uses of Ishikawa Diagram 1. To recognize important causes 2. To understand all effects and causes 3. To compare operational procedures 4. To find major solutions 5. To figure out, what to do? 6. To improve the process

9. Procedure 1. State the problem as precisely as possible and draw the back bone. 2. Draw the large bone. 3. Get all members involved by participating in the brainstorming session to obtain as many ideas as possible. 4. The ideas collected are then critically examined to classify them into the main grouping and subsequent grouping (middle bone, small bone and fine bone). (Figure 2) 5. Dram the middle bones, small bones and fine bones. 6. Check to see whether any causes have been left. 7. Identify the important causes by members vote, proper analysis of data and Pareto diagram. 8. Fill in all related information such title, product, process, etc..

10. Graph • Graph refer to the results of statistical analysis of data (numbers) which are shown in diagrammatic form to communicate information. • There are numerous types of graphs as listed are commonly use; a. Bar graph b. Line graph c. Radar graph f. Pie graph • Each of above graphs is applicable based on analysis requirement.

11. 5% 95% Example Bar Graph Line Graph Radar Graph Pie Graph

12. Check Sheet Check sheets are sheets that are design in advance to collect the necessary data easily and systematically, which allow the efficient checking of all items for inspection and verification.

13. Procedure 1. Specify the aim of collecting data 2. Decide on the item to be check 3. Decide on the method for stratification 4. Format the check sheet 5. Analyze the data 6. Make clear the causes 7. Implementation of counter measure 8. Grasp the effect 9. Standardization of operations to practice the new and improves method properly.

14. Scatter Diagram • Scatter diagram is a diagram where the relationship between two characteristic value are plotted and analyze as to whether a correlation exists between the two set of data. • Several types of correlation could be found from scatter diagram are; 1. Positive strong correlation 2. Negative strong correlation 3. Positive moderate correlation 4. Negative moderate correlation 5. Absence of correlation

15. Example Figure 3 : Example of Scatter Diagram (Positive strong correlation)

16. Procedure 1. Collect and count the number of data 2. Determine the largest (L) and smallest (S) value of data 3. Select number of classes (bars) Number of Data Number of Classes (K) 30 - 50 5 - 8 51 - 100 6 - 10 101 - 300 7 - 13 4. Find class interval (H) H = L - S / K 5. Determine starting point of classes 6. Calculate mid value of each class (half of the measurement unit) 7. Count frequency of data 8. Prepare the histogram

17. Histogram • A histogram is a vertical bar chart that depicts the distribution of a set of data. • It is a useful tool to study the dispersion of data and analyze certain quality characteristic of the product or service to which the data in histogram refers. • A histogram does not reflect the process behavior over time

18. Example Figure 4 : Example of Histogram

19. Procedure 1. Collect and count the number of data 2. Determine the largest (L) and smallest (S) value of data 3. Select number of classes (bars) Number of Data Number of Classes (K) 30 - 50 5 - 8 51 - 100 6 - 10 101 - 300 7 - 13 4. Find class interval (H) H = L - S / K 5. Determine starting point of classes 6. Calculate mid value of each class (half of the measurement unit) 7. Count frequency of data 8. Prepare the histogram