Scatter diagram and control chart
- 1. Scatter diagram and Control Chart By DR.A.NITHYA
- 2. 4. Scatter Diagrams A method for the identification the relationship (effect) between two factors (Causes).
- 3. Scatter diagrams What is it used for? • Validating "hunches" about a cause-and-effect relationship between two variables. • Displaying the direction of the relationship (positive, negative, etc.) • Displaying the strength of the relationship
- 4. Scatter diagrams Constructing scatter diagram • In order to construct a scatter diagram you need two variables to be plotted against each other. One on the x axis the other on the y axis. • The relationship is then plotted. Variable a Variable b relationship
- 5. Scatter diagrams Constructing scatter diagram • This process is continued, showing the effect of changes in one of the variables against the other variable. Variable a Variable b
- 6. Scatter diagrams Interpreting a scatter diagram • The diagram below shows a Strong Positive relationship between the variables (an in crease in a results in a positive increase in b, which is almost uniform.) Variable a Variable b
- 7. Scatter diagrams Interpreting a scatter diagram • The diagram below shows a Strong Negative relationship between the variables (an in crease in a results in a decrease in b, which is almost uniform.) Variable a Variable b
- 8. Scatter diagrams Interpreting a scatter diagram • The diagram below shows a Weak Positive relationship between the variables. Variable a Variable b
- 9. Scatter diagrams Interpreting a scatter diagram • The diagram below shows a Weak Negative relationship between the variables. Variable a Variable b
- 10. Scatter diagrams Interpreting a scatter diagram • The diagram below shows a that there is no relationship between the variables. Variable a Variable b
- 11. 5. Control Charts A method for monitoring a process for preventing defects.
- 12. Control charts What are control charts • Control charting is the most technically sophisticated tool of the 7 quality tools. • It was developed in the 1920s by Dr. Walter A. Shewhart of the Bell Telephone Labs. Dr. Shewhart developed the control charts as a statistical approach to the study of manufacturing process variation. • The purpose was to improve the process effectiveness and therefore reduce costs. • These methods are based on continuous monitoring of the process variation.
- 13. Control charts Why use control charts • A Control chart is a device for describing in a precise manner what is meant by statistical control. • it helps the process perform consistently and predictably. • it can minimise the variation in output. • it can help to achieve lower product costs. • it can help to increase effective capacity. • it can help to meet customer expectations
- 14. Control charts Types of control charts • You will come across two types of Control Charts used in SPC (Statistical Process Control). 1.Attribute SPC 2.Variable SPC
- 15. Control charts Attribute control charts • Attribute data is based upon two conditions (pass/fail, go/no-go, present/absent) which are counted, recorded and analysed. • Control chart techniques are important for the following reasons: Attribute-type situations exist in any process. Attribute-type data is already available in many situations – (existing inspections, repair reasons, reject segregation & sorting) In these cases, no additional data collection is required, you just have to convert the data into chart form. Where new data must be collected, attribute information is usually quick and inexpensive to obtain.
- 16. Control charts Variable control charts • Control charts for variables are used to control the variation of processes in cases where the characteristic under investigation is a measurable quantity.
- 17. Control charts Variable control charts • Xbar&R CHARTS. • Xbar&R charts are used as a pair;
- 18. Control charts Example of an Attribute control chart
- 19. Control charts Example of a variable control chart Moving Range Variable Control Chart (Sub-group Sampling) Process Characteristic Oven temperature X Bar 181 R Bar UCL R Frequency Upper Spec: 185.0 Lower Spec 175.0 Upper Control Limit Lower Control Limit 60 Piece Capability Study X1 182.0 182.0 183.0 176.0 183.5 184.0 183.5 183.0 183.0 170.0 176.0 182 182.5 176.0 183.5 183.0 183.0 184.0 183.0 184.0 183.5 176.0 176.0 176.0 182.0 176.0 178.0 176.0 186.0 187.0 182.0 X2 183.0 176.0 183.0 176.0 176.0 183.5 182.5 182.0 183.0 173.5 176.0 176 182.0 183.5 184.5 184.0 183.5 184.0 183.0 186.0 184.5 183.0 183.0 176.0 176.0 176.0 175.0 176.0 185.0 186.0 176.0 X3 176.0 183.0 184.0 183.5 184.0 182.5 182.0 176.5 184.5 172.0 183.5 176 176.0 184.0 182.5 182.5 180.0 180.0 182.0 184.0 184.0 184.0 183.0 183.0 176.0 175.0 174.0 183.0 183.0 186.0 183.5 X4 X5 X bar 180.3 180.3 183.3 178.5 181.2 183.3 182.7 180.5 183.5 171.8 178.5 178.0 180.2 181.2 183.5 183.2 182.2 182.7 182.7 184.7 184.0 181.0 180.7 178.3 178.0 175.7 175.7 178.3 184.7 186.3 180.5 R 7.0 7.0 1.0 7.5 8.0 1.5 1.5 6.5 1.5 3.5 7.5 6.0 6.5 8.0 2.0 1.5 3.5 4.0 1.0 2.0 1.0 8.0 7.0 7.0 6.0 1.0 4.0 7.0 3.0 1.0 7.5 Op R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc Time Date 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 NEW CALCULATED LIMITS X bar 180.823 R Bar 4.6094 UCL X 185.524 LCL X 176.121 UCL R 30.089 Cp 0.61 Cpk 0.51 Sigma 2.7274 ESPC coating 0.0 5.0 10.0 15.0 UCL 170 172 174 176 178 180 182 184 186 188 190 UCL LCL USL LSL xbar 1 2 3 X bar R bar