1. S. Chopra/Operations/Quality1 Operations Management: Process Quality & Improvement Module u Quality & the Voice of the Customer »What is Quality? »Quality Programs in practice »Voice of the Customer u Process Capability and Improvement »Process Capability »Checking for Improvement (Quality Wireless) u Control Charts & Voice of the Process »Statistical Process Control (SPC) »Quality Wireless (B) u Why 6-Sigma? »Flyrock Tires

2. S. Chopra/Operations/Quality2 8 Dimensions of Quality u Performance u Features u Serviceability u Aesthetics u Perceived Quality u Reliability u Conformance u Durability Q of design Q of process conformance to design = process capability

3. S. Chopra/Operations/Quality3 Elements of TQM u Management by fact u Cross-functional (process) approach u Culture and leadership –Customer focus –Employee focus –High performance focus »Continuous improvement »Benchmarking u External alliances - the value chain Source: Eitan Zemel

4. S. Chopra/Operations/Quality4  1 Leadership 110  2 Strategic Planning 80 –Strategy Development Process u 3 Customer and Market Focus 80  4 Information and Analysis 80  5 Human Resource Development and Management 100  6 Process Management 100 –Product and Service Processes –Support Processes –Supplier and Partnering Processes  7 Business Results 450 u TOTAL POINTS 1000 Malcolm Baldridge National Quality Award

5. S. Chopra/Operations/Quality5 Malcolm Baldridge Award Winners u Ames Rubber Corporation (1993) u Armstrong World Industries Building Products Operations (1995) u AT&T Consumer Communications Services (1994) u AT&T Network Systems Group (1992) u AT&T Universal Card Services (1992) u Cadillac Motor Car Company (1990) u Chugach School District (2001) u Clarke American Checks (2001) u Corning Telecommunications Products Division (1995) u Dana Corporation (2000) u Eastman Chemical Company (1993) u Federal Express Corporation (1990) u Globe Metallurgical Inc. (1988) u Granite Rock Company (1992) u GTE Directories Corporation (1994) u IBM Rochester (1990) u Karlee Company, Inc. (2000) u Los Alamos National Bank (2000) u Marlow Industries (1991) u Milliken & Company (1989) u Motorola Inc. (1988) u Operations Management International (2000) u Pal’s Sudden Service (2001) u Pearl River School District (2001) u The Ritz-Carlton Hotel Company (1992) u Solectron Corporation (1991) u Texas Instruments Incorporated - Defense Systems & Electronics Group (1992) u University of Wisconsin-Stout (2001) u Wainwright Industries, Inc. (1994) u Wallace Co., Inc. (1990) u Westinghouse Electric Corporation - Commerical Nuclear Fuel Division (1988) u Xerox Corporation - Business Products & Systems (1989) u Zytec Corporation (1991) Last Updated: May 28, 2002

6. S. Chopra/Operations/Quality6 ISO 9000 u Series of standards agreed upon by the International Organization for Standardization (ISO) u Adopted in 1987 u More than 100 countries u A prerequisite for global competition? u ISO 9000: “document what you do and then do as you documented.” Source: Adapted from Chase & Aquilano Design Procurement Production Final test Installation Servicing ISO 9003 ISO 9002 ISO 9001

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9. 9 Costs of Quality u Cost of Conformance –Cost of Appraisal –Cost of Prevention u Cost of Non-Conformance –Cost of Internal Failure –Cost of External Failure 100:1 10:1 1:1 Product Design Process Design Production Improve Product Quality Lever Benefits of Building Q in Early Low Visibility Reward High Visibility Reward Time

10. S. Chopra/Operations/Quality10 Components of Quality u Voice of the customer –Customer Needs –Quality of Design u Voice of the process –Quality of Conformance –Process Capability u Process Control and Improvement

11. S. Chopra/Operations/Quality11 Voice of the Customer: Linking Customer Needs to Business Processes Business ProcessCustomer Need Internal Metric Overall Quality Product (30%) Sales (30%) Installation (10%) Repair (15%) Billing (15%) Reliability (40 %) % Repair Call Easy to Use (20%) % Calls for Help Features/Functions (40%) Function Performance Test Knowledge (30%) Supervisor Observations Response (25%) % Proposals Mad on Time Follow-Up (10%) % Follow-Up Made Delivery Interval (30%) Average Order Interval Does Not Break (25%) % Repair Reports Installed When Promised % Installed on Due Date No Repeat Trouble (30%) % Repeat Reports Fixed Fast (25%) Average Speed of Repair Kept Informed (10%) % Customers Informed Accuracy, No Surprise (45%) % Billing Inquiries Response on First Call (35%) % Respolved First Call Easy to Understand (10%) % Billing Inquiries Source: Kordupleski et al., CMR ‘93.

12. S. Chopra/Operations/Quality12 Voice of the Customer: Quality Function Deployment u What do customers want? u Are all preferences equally important? u Will delivering perceived needs deliver a competitive advantage? u How can we change the product? u How do engineering characteristics influence customer perceived quality? u How does one engineering attribute affect another? u What are the appropriate targets for the engineering characteristics?

13. House of Quality Source: Hauser and Clausing 1988 Customer Requirements Importance to Cust. Easy to close Stays open on a hill Easy to open Doesn’t leak in rain No road noise Importance weighting Engineering Characteristics Energy needed to close door Check force on level ground Energy needed to open door Water resistance 1066923 7 5 3 3 2 X X X X X Correlation: Strong positive Positive Negative Strong negative X * Competitive evaluation X = Ours A = Comp. A B = Comp. B (5 is best) 1 2 3 4 5 X AB X AB A X B X A B Relationships: Strong = 9 Medium = 3 Small = 1 Target values Reduce energy level to 7.5 ft/lb Reduce force to 9 lb. Reduce energy to 7.5 ft/lb. Maintain current level Technical evaluation (5 is best) 5 4 3 2 1 B A X BA X B A X B X A BXA BA X Door seal resistance Accoust. Trans. Window Maintain current level Maintain current level X - + --+ +

14. S. Chopra/Operations/Quality14 Linked Houses From Customer To Manufacturing Engineering Characteristics Parts Characteristics Key Process Characteristics Production Characteristics House of Quality Parts Deployment Process Planning Production Planning IIIIIIIV Engineering Characteristics Parts Characteristics Key Process Characteristics Customer Attributes

15. S. Chopra/Operations/Quality15 Benefits of QFD Startup and Preproduction costs at Toyota Auto Body Japanese automaker with QFD made fewer changes than US company without QFD time 20 - 24 months 90% of total Japanese changes complete Job # 1 Japan US Design Changes 14 - 17 months 1 - 3 months 1 - 3 months Before QFD After QFD (39% of preQFD costs) t Job # 1 Source: Hauser and Clausing 1988

16. S. Chopra/Operations/Quality16 More New Product Development Tools u Value analysis / Value engineering u Design for manufacturability u Robust design

17. S. Chopra/Operations/Quality17 Value Analysis/Value Engineering u Achieve equivalent or better performance at a lower cost while maintaining all functional requirements defined by the customer –Does the item have any design features that are not necessary? –Can two or more parts be combined into one? –How can we cut down the weight? –Are there nonstandard parts that can be eliminated?

18. S. Chopra/Operations/Quality18 Robust Quality: Taguchi’s View of Cost of Variability Traditional ViewTaguchi’s View Non-conformance to design cost $$$ 0 Lower Tolerance Design Spec Upper Tolerance Actual value Lower Tolerance Design Spec Upper Tolerance

19. S. Chopra/Operations/Quality19 Quality & the Voice of the Customer: Key Learning Objectives u Elements of TQM / Baldridge / ISO 9000 u Costs of Quality u Components of Quality u Voice of the Customer –Linking business processes to customer needs –Product Design Methodologies: »Convert customer needs to product and process specifications: QFD »Value Engineering

20. S. Chopra/Operations/Quality20 Operations Management: Process Quality & Improvement Module u Quality & the Voice of the Customer »What is Quality? »Quality Programs in practice »Voice of the Customer u Process Capability and Improvement »Process Capability »Checking for Improvement (Quality Wireless) u Control Charts & Voice of the Process »Statistical Process Control (SPC) »Quality Wireless (B) u Why 6-Sigma? »Flyrock Tires

21. S. Chopra/Operations/Quality21 Process Capability u Percent defective –Proportion of output that does not meet customer specifications u Sigma-capability –Number of standard deviations from the mean of the process output to the closest specification limit.

22. S. Chopra/Operations/Quality22 Quality Wireless (A): Capability Out of SpecsWithin Specs

23. S. Chopra/Operations/Quality23 Quality Wireless (A): Capability u Proportion of days within specification in 2003-04 = 491/731 = 0.672 u The call center had a mean hold time of 99.67 with a standard deviation of 24.24. With a specification of 110 seconds or less, σ-capability of call center = (110 – 99.67)/24.24 = 0.426 The call center is a 0.426-sigma process. Expected fraction of days within specifications from a 0.426-sigma process = NORMSDIST(0.426) = 0.665

24. S. Chopra/Operations/Quality24 What is Process Improvement?

25. S. Chopra/Operations/Quality25 Continuous Improvement: PDCA Cycle (Deming Wheel) Institutionalize the change or abandon or do it again. Execute the change. Study the results; did it work? 1. Plan 2. Do3. Check 4. Act Plan a change aimed at improvement.

26. S. Chopra/Operations/Quality26 Quality Wireless (A): Checking for Improvement u Performance in April 2005: Mean = 79.50, Standard deviation = 16.86 u What is the probability of observing such a sample if performance has not improved relative to 2003-04? –Mean hold in 2003-04 = 99.67 –Standard deviation = 24.24 –Given that April 2005 had 30 days, we need to consider distribution of samples of size 30. The standard deviation of sample means = 24.24/√30 = 4.43 –Probability of observing a sample of size 30 with mean 79.50 or less = NORMDIST(79.50, 99.67, 4.43, 1) = 2.64E-06

27. S. Chopra/Operations/Quality27 Operations Management: Process Quality & Improvement Module u Quality & the Voice of the Customer »What is Quality? »Quality Programs in practice »Voice of the Customer u Process Capability and Improvement »Process Capability »Checking for Improvement (Quality Wireless) u Control Charts & Voice of the Process »Statistical Process Control (SPC) »Quality Wireless (B) u Why 6-Sigma? »Flyrock Tires

28. S. Chopra/Operations/Quality28 Has Process Performance Changed? Quality Wireless (B) u Average hold time from September 1-10 =86.6 seconds –Ray yells at supervisors u Performance improves from September 11-20 to an average hold of 74.4 seconds u What do you think of Ray’s management style?

29. S. Chopra/Operations/Quality29 Performance of Inventory Manager J F M A M J J A S O N WIP Award Given Manager repents and kicks... J F M A M J J A S O N D J F WIP J F M A M J J A S O N D J F M A M J WIP.. and concludes that kick... mgt works !? month

30. S. Chopra/Operations/Quality30 Statistical Process Control: Source of Variability u Inherent (common cause) u External (assignable cause) è Objective: Identify inherent variability and eliminate external variability. A process is in control if it has only inherent variability. u To improve the system, attack common causes (methods, people, material, machines). This is the role of management.

31. S. Chopra/Operations/Quality31 Various Patterns in Control Charts Pattern Description Possible Causes NormalRandom Variation Lack of StabilityAssignable (or special) causes (e.g. tool, material, operator, overcontrol Cumulative trendTool Wear CyclicalDifferent work shifts, voltage fluctuations, seasonal effects

32. S. Chopra/Operations/Quality32 SPC – Quality Wireless (B) u After the improvements, daily hold time has an average of 79.50 and a standard deviation of 16.86. u Since we are considering samples of size 10 (10 days), we need to consider the distribution of sample means. Sample means have an average of 79.50 and a standard deviation of 16.86/√10 = 5.33. u Probability of observing 86.6 or higher even if process is in control = 1-NORMDIST(86.6, 79.50, 5.33, 1) = 0.0915

33. S. Chopra/Operations/Quality33 SPC – Quality Wireless (B) u Probability of observing 74.4 or lower even if process is in control = NORMDIST(74.4, 79.50, 5.33, 1) = 0.1693 u What we need is a hypothesis test each time we observe a sample – Does the sample belong to the in- control population or not?

34. S. Chopra/Operations/Quality34 SPC – Setting Control Limits u Upper Control Limit = UCL = Mean + 3σ Xbar u Lower Control Limit = LCL = Mean - 3σ Xbar u In the case of Quality Wireless –UCL = 79.50 + 3×5.33 = 95.49 –LCL = 79.50 - 3×5.33 = 63.51 u The process was in control when samples with means of 86.6 and 74.4 were observed.

35. S. Chopra/Operations/Quality35 Control Charts & Voice of the Process: Key Learning Objectives u The role of variability in evaluating performance u A process –in control has only inherent (from common cause) variation –out of control has variation from an assignable cause u SPC framework for process control and improvement

36. S. Chopra/Operations/Quality36 Operations Management: Process Quality & Improvement Module u Quality & the Voice of the Customer »What is Quality? »Quality Programs in practice »Voice of the Customer u Process Capability and Improvement »Process Capability »Checking for Improvement (Quality Wireless) u Control Charts & Voice of the Process »Statistical Process Control (SPC) »Quality Wireless (B) u Why 6-Sigma? »Flyrock Tires

37. S. Chopra/Operations/Quality37 Why 6-Sigma? u 2 sigma: u 69.146% of products and/or services meet customer requirements with 308,538 defects per million opportunities. u 4 sigma: u 99.379% of products and/or services meet customer requirements... but there are still 6,210 defects per million opportunities. u 6 sigma: u 99.99966% – As close to flaw-free as a business can get, with just 3.4 failures per million opportunities (e.g. products, services or transactions).

38. S. Chopra/Operations/Quality38 Why 6-Sigma? u Impact of # of parts/stages in a process

39. S. Chopra/Operations/Quality39 Why 6-Sigma? Robustness to Mean Shifts 100 130160 LSLUSL  = 10 100 143 160 LSLUSL  = 10 LSLUSL  = 5 100 130160 LSLUSL  = 5 100 143160 99.9 %

40. S. Chopra/Operations/Quality40 Why 6-Sigma? 6-Sigma Quality at Flyrock At the extruder, the rubber for the AX-527 tires had thickness specifications of 400  10. Susan and her staff had analyzed many samples of output from the extruder and determined that if the extruder settings were accurate, the output produced by the extruder had a thickness that was normally distributed with a mean of 400 and a standard deviation of 4. If the setting is accurate, what proportion of the rubber extruded will be within specifications?

41. Process Capability: Sigma Capability u Sigma capability is the number of standard deviations from the mean to the closest specification limit. u Sigma capability of extrusion process = Susan has asked operators to take a sample of 10 sheets of rubber each hour from the extruder and measure the thickness of each sheet. Based on the average thickness of this sample, operators will decide whether the extrusion process is in control or not. Given that Susan plans 3-sigma control limits, what upper and lower control limits should she specify to the operators?

42. S. Chopra/Operations/Quality42 Impact of Mean Shift u If a bearing is worn out, the extruder produces a mean thickness of 403 when the setting is 400. Under this condition, what proportion of defective sheet will the extruder produce? Assuming the control limits in (2), what is the probability that a sample taken from the extruder with the worn bearings will be out of control? On average, how many hours are likely to go by before the worn bearing is detected.

43. S. Chopra/Operations/Quality43 Why 6-Sigma? Rapid Detection u What if extrusion is to become a 6-Sigma process? –Target mean = –Target standard deviation = u Process improvement has resulted in the extrusion process having a mean of 400 and a standard deviation of 1.667. What should the new control limits be? What is the proportion of defectives produced?

44. S. Chopra/Operations/Quality44 Improving Process Capability u Return to the case of the worn bearing in (3) where extrusion produces a mean thickness of 403 when the setting is 400. Under this condition, what proportion of defective sheets will the extruder produce (for the 6-sigma process)? Assuming the control limits in (5), what is the probability that a sample taken from the extruder with the worn bearings will be out of control? On average, how many hours are likely to go by before the worn bearing is detected.

45. S. Chopra/Operations/Quality45 Key Learning Objectives: SPC u Specification limits: Voice of the customer u Process capability is a measure of the quality delivered (external): links VoP with VoC u Improving capability may require variability reduction and/or mean shift u Control limits used to verify if process is in control (internal), i.e., is maintaining capability: Voice of the process u Higher process capability reduces defectives and speeds up detection of assignable cause