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Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.1 Chapter 17 Quality management.

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Presentation on theme: "Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.1 Chapter 17 Quality management."— Presentation transcript:

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2 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.1 Chapter 17 Quality management Pearson Education Ltd. Naki Kouyioumtzis

3 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.2 Quality management Design Planning and control Operations strategy Improvement The operation supplies… the consistent delivery of products and services at specification or above The market requires… consistent quality of products and services Capacity planning and control

4 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.3 In Chapter 17 – Quality planning and control – Slack et al. identify the following key questions: What is quality and why is it so important? How can quality problems be diagnosed? What steps lead towards conformance to specification? What is Total Quality Management (TQM)? Key operations questions

5 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.4 Quality up Profits up Processing time down Inventory down Capital costs down Complaint and warranty costs down Rework and scrap costs down Inspection and test costs down Productivity up Image up Scale economies up Price competition down Sales volume up Revenue up High quality puts costs down and revenue up Operation costs down Service costs down

6 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.5 Customers’ expectations for the product or service Customers’ perceptions of the product or service Gap Expectations > perceptions Expectations = perceptions Expectations < perceptions Perceived quality is governed by the gap between customers’ expectations and their perceptions of the product or service Gap Perceived quality is poor Perceived quality is good Perceived quality is acceptable Customers’ expectations for the product or service Customers’ perceptions of the product or service Customers’ expectations for the product or service Customers’ perceptions of the product or service

7 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.6 The operation’s domain Management’s concept of the product or service The customer’s domain Previous Experience Word of mouth communications Image of product or service Customers’ own specification of quality Organization’s specification of quality The actual product or service Gap 1 Gap 2 Gap 3 Gap 4 A ‘Gap’ model of Quality Customers’ expectations concerning a product or service Customers’ perceptions concerning the product or service Gap ?

8 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.7 The perception – expectation gap Gap Action required to ensure high perceived quality Main organizational responsibility Gap 3Operations Ensure actual product or service conforms to internally specified quality level Gap 4 Marketing Ensure that promises made to customers concerning the product or service can really be delivered Gap 1 Ensure consistency between internal quality specification and the expectations of customers Marketing, operations, product/service development Gap 2 Ensure internal specification meets its intended concept of design Marketing, operations, product/service development

9 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.8 Quality characteristics of goods and services Functionality – how well the product or service does the job for which it was intended. Appearance – aesthetic appeal, look, feel, sound and smell of the product or service. Reliability – consistency of product or services performance over time. Durability – the total useful life of the product or service. Recovery – the ease with which problems with the product or service can be rectified or resolved. Contact – the nature of the person-to-person contacts that take place.

10 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.9 Attribute and variable measures of quality AttributesVariables Defective or not defective? Measured on a continuous scale Light bulb works or does not work? Light emission of bulb Number of defects in a turbine blade. Length of blade

11 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.10 Variables things you can measure Variables things you can measure Attributes things you can assess accept/reject Attributes things you can assess accept/reject Quality fitness for purpose Quality fitness for purpose Reliability ability to continue working at accepted quality level Reliability ability to continue working at accepted quality level Quality Quality of Design degree to which design achieves purpose Quality of Design degree to which design achieves purpose Quality of Conformance faithfulness with which the operation agrees with design Quality of Conformance faithfulness with which the operation agrees with design Aspects of quality

12 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.11 What does Total Quality Management include? Total Quality Management Includes all parts of the organization Includes all staff of the organization Includes consideration of all costs Includes every opportunity to get things right Includes all the systems that affect quality And it never stops!

13 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.12 Total quality management can be viewed as a natural extension of earlier approaches to quality management Quality is strategic Teamwork Staff empowerment Involves customers and suppliers Quality systems Quality costing Problem solving Quality planning Statistics Process analysis Quality standards Error detection Rectification Prevents ‘out of specification’ products and services reaching market Solves the root cause of quality problems Broadens the organizational responsibility for quality Makes quality central and strategic in the organization Inspection Quality control Quality assurance Total Quality Management

14 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.13 External supplier External customer The internal customer–supplier concept involves understanding the relationship between processes Between each process, the requirements of the ‘customer’ process must be understood and met by the 'supplier’ process Process 1 Process 3 Process 2 Process 4 Process 5 Process 6

15 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.14 The traditional cost of quality model Cost of errors = costs of prevention and appraisal Total cost of quality Cost of quality provision = costs of internal and external failure Costs ‘Optimum’ amount of quality effort Amount of quality effort

16 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.15 Costs Amount of quality effort Total cost of quality Cost of errors = costs of prevention and appraisal Cost of quality provision = costs of internal and external failure ‘Optimum’ amount of quality effort The traditional cost of quality model with adjustments to reflect TQM criticisms

17 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.16 EFQM ‘Business excellence’ model Leadership People Partnerships and resources Processes Key performance results Policy and strategy Customer results People results Society results

18 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.17 The quality gurus Quality is free – the optimum is zero defects Deming’s 14 points How to use statistics Total quality control Quality as fitness for use, rather than conformance to specification Loss function Minimize variation Quality circles and cause and effect diagrams Philip Crosby W. Edwards Deming Armand FeigenbaumKaoru Ishikawa Joseph JuranGenichi Taguchi

19 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.18 The cost of rectifying errors becomes increasingly expensive the longer the errors remain uncorrected in the development and launch process Cost to rectify error Stage in the development and launch process Pilot production Market use PrototypeDesign Concept 1000 100 10 1 10, 000

20 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.19 Time Costs of quality Appraisal Internal failure Appraisal Prevention Total cost of quality Increasing the effort spent on preventing errors occurring in the first place brings a more than equivalent reduction in other cost categories

21 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.20 Effectiveness of the TQM initiative The pattern of some TQM programmes which run out of enthusiasm Introduction Learning and understanding Growth Increasing enthusiasm Levelling off Starting to hit the more difficult problems Disillusionment Waning enthusiasm Repackaging Attempts to revitalize the programme

22 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.21 Time Some measure of operations performance Some aspect of the performance of a process is often measured over time. Question ‘Why do we do this?’ Question ‘Why do we do this?’ Process control charting

23 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.22 Time Some measure of operations performance Trend can indicate whether performance is getting better or worse Question ‘But why is variation important?’ Question ‘But why is variation important?’ Process control charting (Continued) ‘And how do we know if the variation in process performance is ‘‘Natural’’ in terms of being a result of random causes, or is indicative of some ‘‘Assignable’’ causes in the process?’

24 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.23 Time Some measure of operations performance The last point plotted on this chart seems to be unusually low. How do we know if this is just random variation or the result of some change in the process which we should investigate? Some kind of ‘Guide lines’ or ‘Control limits’ would be useful. Process control charting (Continued)

25 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.24 0.8 2.23.6 After the first sample 0.8 2.23.6 After the second sample 0.8 2.23.6 By the end of the day 0.8 2.23.6 By the end of the second day 0.8 2.23.6 Fitting a normal distribution to the histogram of sampled call times Sampling over a period of time… Process control charting (Continued)

26 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.25 Process control charting The chances of measurement points deviating from the average is predictable in a normal distribution 40 100 160 Elapsed time of call (seconds) Frequency 68% of points –2 standard deviations +2 standard deviations 95.4% of points –3 standard deviations +3 standard deviations 99.7% of points –1 standard deviation +1 standard deviation A standard deviation  = sigma

27 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.26 Time Some measure of operations performance If we understand the normal distribution which describes random variation when the process is operating normally, then, we can use the distribution to draw the control limits. In this case, the final point is very likely to be caused by an ‘assignable’ cause, i.e. the process is likely to be out of control. Process control charting

28 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.27 A P X X X X Process variability Scatter PRECISION : P Off target ACCURACY : P

29 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.28 Low process variation allows changes in process performance to be readily detected TIME Process distribution A A TIME Process distribution A Process distribution B A B B

30 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.29 UCL C/L LCL Alternating and erratic behaviour – Investigate. In addition to points falling outside the control limits other unlikely sequences of points should be investigated

31 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.30 In addition to points falling outside the control limits other unlikely sequences of points should be investigated (Continued) Suspiciously average behaviour – Investigate. UCL C/L LCL

32 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.31 In addition to points falling outside the control limits other unlikely sequences of points should be investigated (Continued) UCL C/L LCL Two points near control limit – Investigate.

33 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.32 In addition to points falling outside the control limits other unlikely sequences of points should be investigated (Continued) UCL C/L LCL Five points one side of centre line – Investigate.

34 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.33 In addition to points falling outside the control limits other unlikely sequences of points should be investigated (Continued) UCL C/L LCL Apparent trend in one direction – Investigate.

35 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.34 In addition to points falling outside the control limits other unlikely sequences of points should be investigated (Continued) UCL C/L LCL Sudden change in level – Investigate.

36 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.35 USL LSL Process variation 3 sigma process variation = 66,800 Defects per million opportunities 4 sigma process variation = 6200 Defects per million opportunities 5 sigma process variation = 230 Defects per million opportunities 6 sigma process variation = 3.4 Defects per million opportunities Process variation and its effect on process Defects per Million Opportunities (DPMO) USL LSL USL LSL USL LSL

37 Slack, Chambers and Johnston, Operations Management, 6 th Edition, © Nigel Slack, Stuart Chambers, and Robert Johnston 2010 17.36 Percentage actual defective in the batch Probability of accepting the batch 0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 1.0 Producer’s risk (0.05) Consumer’s risk (1.0) AQL LTPD 0 0.060.050.040.030.020.01 0.07 0.08 In this ideal operating characteristic, the probability of accepting the batch if it contains more than 0.04% defective items is zero, and the probability of accepting the batch if it contains less than 0.04% items defective is 1. In this real operating characteristic (where n = 250 and c = 1), both type 1 and type 2 errors will occur. Type 1 error Type 2 error Ideal and real operating characteristics


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