Seven tools of TQM

Seven tools of TQM/ Seven tools of Total Quality Management/ Tools of TQM

1. Tools Of TQM Presented By- Varun saxena

2. Seven Problem Solving Tools Pareto Analysis Flowcharts Checklists Histograms Scatter Diagrams Control Charts Cause-and-Effect Diagrams

3. Pareto Chart A Pareto Chart is a vertical bar chart in which the bars are arranged in the descending order of their height starting from the left and prioritize the problems or issues. USES To prioritize problems To analyze a process To identify root causes To verify that whatever improvement process you implement continues to work

4. Pareto Analysis NUMBER OF CAUSE DEFECTS PERCENTAGE Poor design 80 64 % Wrong part dimensions 16 13 Defective parts 12 10 Incorrect machine calibration 7 6 Operator errors 4 3 Defective material 3 2 Surface abrasions 3 2 125 100 %

5. Pareto Chart Percent from each cause Causes of poor quality Machine calibrations Defective parts Wrong dimensions Poor Design Operator errors Defective materials Surface abrasions 10 20 30 40 50 60 70 (64) (13) (10) (6) (3) (2) (2)

6. Flow Charts Operation Decision Start/ Finish Start/ Finish Operation Operation Operation Operation Decision Flow charts are nothing but graphical representation of steps involved in a process. Flow charts give in detail the sequence involved in the material, machine and operation that are involved in the completion of the process. Thus, they are the excellent means of documenting the steps that are carried out in a process.

7. Check Sheet A simple means of data collection. Check sheets are nothing but forms that can be used to systematically collect data. Data is read by observing the location and number of marks on the sheet.

8. Check Sheet COMPONENTS REPLACED BY LAB TIME PERIOD: 22 Feb to 27 Feb 2017 REPAIR TECHNICIAN: Tom TV SET MODEL Integrated Circuits |||| |||| Capacitors |||| |||| |||| |||| |||| || Resistors || Transformers |||| Commands CRT |

9. Check Sheet USES To gather data To test a theory To evaluate alternate solutions To verify that whatever improvement process you implement continues to work Steps Team agrees on what to observe Decide who collects data Decide time period for collecting data Design check sheet Collect data Compile data in the check sheet Review check sheet

10. 5 10 15 20 1 2 6 13 10 16 19 17 12 16 2017 13 5 6 2 1 Histogram Used to graphically represent groups of data. Histograms help in understanding the variation in the process. It also helps in estimating the process capability.

11. Scatter Diagram Y X It is a graph of points plotted. This graph is helpful in comparing two variables. The distribution of the points helps in identifying the cause and effect relationship between two variables.

12. Control Chart A control chart is nothing but a run chart with limits. This is helpful in finding the amount and nature of variation in a process.

13. Histograms do not take into account changes over time. Control charts can tell us when a process changes

14. Cause and Effect Diagram Developed by Dr Kaoru Ishikawa in 1943. It is also known by the name of 1) Ishikawa diagram, 2)Fishbone diagram. This diagram is helpful in representing the relationship between an effect and the potential or possible causes that influences it. This is very much helpful when one want to find out the solution to a particular problem that could have a number of causes for it and when we are interested in finding out the root cause for it.

15. Cause and effect Diagram There is a systematic arrangement of all possible causes which give rise to the effect in Ishikawa diagram. Before taking up problem for a detailed study, it is necessary to list down all possible causes through a brainstorming session so that no important cause is missed. The causes are then divided into major sources or variables. 15

16. Cause and effect Diagram Quality Problem Out of adjustment Tooling problems Old / worn Machines Faulty testing equipment Incorrect specifications Improper methods Measurement Poor supervision Lack of concentration Inadequate training Human Deficiencies in product design Ineffective quality management Poor process design Process Inaccurate temperature control Dust and Dirt Environment Defective from vendor Not to specifications Material- handling problems Materials