1. RISK MANAGEMENT Topic:Managing Quality Risk through control chart NewGate India Hyderabad, Andhra Pradesh- 500038 Website: www.newgate.in Email: contact@newgate.in Slideshare URL : 1 http://www.slideshare.net/newgateindia

2. Is Risk a symbol of danger or symbol of opportunityAnswer: Both

3. Risk ManagementRiskUncertainty of outcomeTerminologiesPure Risk- Always leads to lossSpeculative Risk- May Result in loss or GainStatic Risk- Results in lossDynamic Risk- May Result in loss or GainAcceptable RiskNon Acceptable Risk

4. Control Charts for Variables

5. Types of Risks1. Material Risk- Building,Plant & Machinery, Furniture,Fixtures,fittings,Stocks.2. Consequential Risk- Loss of production,Loss of profit,Loss of market,Good will.3. Social Risk4. Legal Risk- Product liability,Public liability.5. Political Risk- Subsidies,Sanctions etc.

6. Best Practice Risk Management Framework for Risk Management can be benchmarked in terms of: Policies Methodologies Resources 6

7. Risk Evaluation Arrange them in order of priority Provide information for deciding the most appropriate way of handling. Ranking risks according to : 1. Frequency of loss 2. Potential severity of loss.

8. Risk Analysis Risk and Human behavior looks into psychology of risk. How others look at the risk? How they behave in the face of risk? How they behave in groups? Perception of Risk.

9. Risk analysis is to be carried out with properperception of risk of risk and cost involved inAnalysis.Not to stick to one methodUnderstand company and industryShould be financially reasonableAccurate record keepingAmount of imagination of required

10. Risk Reduction / Loss Prevention1. Reduce probability of loss and its severity.2. Most important for PM process.3. Risk Reduction / Prevention can be from Loss preventionEnsuring SafetyFire protection / DetectionEnvironmental protection

11. Variation It is the measure of deviation from mean/average value Variation may be quite large or very small. If variation is very small, it may appear that items are identical, but precision instruments will show differences.

12. Categories of variation Within-piece variation One portion of surface is rougher than another portion. A piece-to-piece variation Variation among pieces produced at the same time. Time-to-time variation Service given early would be different from that given later in the day.

13. Source of variation Equipment Tool wear, machine vibration, Material Raw material quality Environment Temperature, pressure, humadity Operator Operator performs- physical & emotional

14. Control Chart Viewpoint Variation due to Common or chance causes Assignable causes Control chart may be used to discover assignable causes

15. Run chart - without any upper/lower limits Specification/tolerance limits Control limits - statistical

16. Control chart functions Control charts are powerful aids to understanding the performance of a process over time. Noise Input Output PROCESS Whats causing variability?

17. Control charts identifyvariation Chance causes - common cause inherent to the process or random and not controllable if only common cause present, the process is considered stable or in control Assignable causes - special cause variation due to outside influences if present, the process is out of control

18. Types of Data Continuous data Product characteristic that can be measured Length, size, weight, height, time, velocity Discrete data Product characteristic evaluated with a discrete choice Good/bad, yes/no

19. Control chart for variables Variables are the measurable characteristics of a product or service. Measurement data is taken and arrayed on charts.

20. Control charts for variables X-bar chart In this chart the sample means are plotted in order to control the mean value of a variable (e.g., size of piston rings, strength of materials, etc.). R chart In this chart, the sample ranges are plotted in order to control the variability of a variable. S chart In this chart, the sample standard deviations are plotted in order to control the variability of a variable. S2 chart In this chart, the sample variances are plotted in order to control the variability of a variable.

21. Control chart components Centerline shows where the process average is centered or the central tendency of the data Upper control limit (UCL) and Lower control limit (LCL) describes the process spread

22. The Control Chart MethodX bar Control Chart:UCL = XDmean + A2 x RmeanLCL = XDmean - A2 x RmeanCL = XDmean R Control Chart: UCL = D4 x Rmean LCL = D3 x Rmean CL = Rmean Capability Study: PCR = (USL - LSL)/(6s); where s = Rmean /d2

23. Control Chart Examples UCL Variations Nominal LCL Sample number

24. Determine trial centerline The centerline should be the population mean, Since it is unknown, we use X Double bar, or the grand average of the subgroup averages. m X i X i 1 m

25. UCL & LCL calculation UCL X 3LCL X 3 standard deviation

26. Determining an alternative value forthe standard deviation m R i R i 1 m UCL X A 2 R LCL X A 2 R

27. Example: Control Charts for Variable Data Slip Ring Diameter (cm)Sample 1 2 3 4 5 X R 1 5.02 5.01 4.94 4.99 4.96 4.98 0.08 2 5.01 5.03 5.07 4.95 4.96 5.00 0.12 3 4.99 5.00 4.93 4.92 4.99 4.97 0.08 4 5.03 4.91 5.01 4.98 4.89 4.96 0.14 5 4.95 4.92 5.03 5.05 5.01 4.99 0.13 6 4.97 5.06 5.06 4.96 5.03 5.01 0.10 7 5.05 5.01 5.10 4.96 4.99 5.02 0.14 8 5.09 5.10 5.00 4.99 5.08 5.05 0.11 9 5.14 5.10 4.99 5.08 5.09 5.08 0.15 10 5.01 4.98 5.08 5.07 4.99 5.03 0.10 50.09 1.15

28. Calculation From Table above: Sigma X-bar = 50.09 Sigma R = 1.15 m = 10 Thus; X-Double bar = 50.09/10 = 5.009 cm R-bar = 1.15/10 = 0.115 cmNote: The control limits are only preliminary with 10 samples.It is desirable to have at least 25 samples.

29. 3-Sigma Control Chart FactorsSample size X-chart R-chart n A2 D3 D4 2 1.88 0 3.27 3 1.02 0 2.57 4 0.73 0 2.28 5 0.58 0 2.11 6 0.48 0 2.00 7 0.42 0.08 1.92 8 0.37 0.14 1.86

30. Trial control limitX-bar chart UCLx-bar = X-D bar + A2 R-bar = 5.009 + (0.577)(0.115) = 5.075 cm LCLx-bar = X-D bar - A2 R-bar = 5.009 - (0.577)(0.115) = 4.943 cmR-chart UCLR = D4R-bar = (2.114)(0.115) = 0.243 cm LCLR = D3R-bar = (0)(0.115) = 0 cm

31. X-bar Chart 5.10 UCL 5.08 5.06 5.04 X bar 5.02 5.00 CL 4.98 4.96 LCL 4.94 0 1 2 3 4 5 6 7 8 9 10 11 Subgroup

32. R Chart 0.25 UCL 0.20Range 0.15 CL 0.10 0.05 LCL 0.00 0 1 2 3 4 5 6 7 8 9 10 11 Subgroup

33. 6.70 6.65 Run Chart 6.60 Mean, X-bar 6.55 6.50 6.45 6.40 6.35 6.30 0 5 10 15 20 25 Subgroup number 0.35 0.3 0.25Range, R 0.2 0.15 0.1 0.05 0 0 5 10 15 20 25 Subgroup number

34. X-bar Chart

35. R Chart

36. Trial Control Limits & Revised Control Limit 6.65 6.60 Revised control limits 6.55 Mean, X-bar UCL = 6.46 6.50 6.45 6.40 CL = 6.40 6.35 6.30 LCL = 6.34 0 2 4 6 8 Subgroup 0.20 UCL = 0.18 0.15 Range, R 0.10 CL = 0.08 0.05 0.00 0 2 4 6 8 LCL = 0 Subgroup

37. Revise the chartsIn certain cases, control limits are revisedbecause: 1. out-of-control points were included in the calculation of the control limits. 2. the process is in-control but the within subgroup variation significantly improves.

38. The Normal Distribution = Standard deviation Mean -3 -2 -1 +1 +2 +3 68.26% 95.44%LSL USL 99.74% -3 +3 CL

39. 34.13% of data lie between and 1 above the mean (). 34.13% between and 1 below the mean. Approximately two-thirds (68.28 %) within 1 of the mean. 13.59% of the data lie between one and two standard deviations Finally, almost all of the data (99.74%) are within 3 of the mean.

40. Normal Distribution Review Define the 3-sigma limits for sample means as follows: 3 3(0.05) Upper Limit 5.01 5.077 n 5 3 3(0.05) Lower Limit 5.01 4.943 n 5 What is the probability that the sample means will lie outside 3-sigma limits? Note that the 3-sigma limits for sample means are different from natural tolerances which are at 3

41. Common Causes

42. Process Out of Control The term out of control is a change in the process due to an assignable cause. When a point (subgroup value) falls outside its control limits, the process is out of control.

43. Assignable Causes Average (a) Mean Grams

44. Assignable Causes Average (b) Spread Grams

45. Assignable Causes Average (c) Shape Grams

46. Improvement

47. Chart zones Based on our knowledge of the normal curve, a control chart exhibits a state of control when: Two thirds of all points are near the center value. The points appear to float back and forth across the centerline. The points are balanced on both sides of the centerline. No points beyond the control limits. No patterns or trends.

48. What Is Six Sigma?Sigma is a letter Degree of variation; in the Greek Level of performance in terms of defects; Alphabet Statistical measurement of process capability; Benchmark for comparison; Process improvement methodology; It is a Goal; Strategy for change; A commitment to customers to achieve an acceptable level of performance 48

49. Six Sigma Definitions Business Definition A break through strategy to significantly improve customer satisfaction and shareholder value by reducing variability in every aspect of business. Technical Definition A statistical term signifying 3.4 defects per million opportunities. 49

50. Sigma Defects Per Million Rate ofLevel Opportunities Improveme nt 1 690,000 2 308,000 2 times 3 66,800 5 times 4 6,210 11 times 5 230 27 times 6 3.4 68 times 50

51. Six Sigma Project MethodologyProject Phases Define Measure Analyze Improve Control Identify, Collect data Analyze data, Improvement Establish evaluate and on size of the establish and strategy standards to select projects selected confirm the Develop ideas maintain for problem, vital few to remove root process; improvement identify key determinants causes Design the Set goals customer of the Design and controls, Form teams. requirements, performance. carry out implement and Determine key Validate experiments, monitor. product and hypothesis Optimize the Evaluate process process. financial characteristic. Final solutions impact of the project 51

52. Learning Outcome1. Risk can fixed only when it is scalable2. More than one form of risk can be present in a project3. 100% assurance on risk control can be guranteed4. Reduction in Risk automatically enhances the quality of product

53. PSGIM, Coimbatore E-procurement system of Honeywell & Vedanta BENCHMARK 2 0 1 1 Questions Please ???? 53 Fri 25 Feb