1. Pearson Education Ltd. Naki Kouyioumtzis
Chapter 17
Quality management
Pearson Education Ltd. Naki Kouyioumtzis

2. The operation supplies…
Capacity planning and control
Operations strategy
Design
Improvement
Quality management
Planning and control
The operation supplies…
the consistent delivery of products and services at specification or above
The market requires… consistent quality of products and services

3. Key operations questions
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)?

4. High quality puts costs down and revenue up
Quality up
Image up
Processing time down
Service costs down
Inspection and test costs down
Rework and scrap costs down
Inventory down
Complaint and warranty costs down
Capital costs down
Price competition down
Sales volume up
Productivity up
Revenue up
Scale economies up
Operation costs down
The net effect of all these consequences is that revenues increase and costs reduce. In other words, the overall effect of raising quality levels is to increase profitability.
Profits up

5. Perceived quality is governed by the gap between customers’ expectations and their perceptions of the product or service
Customers’ expectations for the product or service
Customers’ perceptions of the product or service
Gap
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
Gap
Expectations > perceptions
Expectations = perceptions
Expectations < perceptions
So the continuum between quality being perceived as poor through to it being perceived as good is primarily a function of the nature and extent of any gaps between customers’ expectations and their perceptions. The implication of this is that in order to manage customers’ perceived quality levels, both their expectations and their perceptions must be managed.
Perceived quality is poor
Perceived quality is good
Perceived quality is acceptable

6. A ‘Gap’ model of Quality
The customer’s domain
Previous
Experience
Word of mouth communications
Image of product or service
Gap 4
Customers’ expectations concerning a product or service
Customers’ perceptions concerning the product or service
Gap ?
Customers’ own specification of quality
The actual product or service
Gap 1
The operation’s domain
Finally, the organization may be influencing the customers’ image of the product or service, for example through its advertising or other promotional activity, in such a way as to conflict with its actual reality. This is called gap 4.
Organization’s specification of quality
Gap 3
Management’s concept of the product or service
Gap 2

7. The perception – expectation gap
Action required to ensure high
perceived quality
Main organizational
responsibility
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
Gap 3
Operations
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

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.

9. Attribute and variable measures of quality
Attributes
Variables
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

10. Aspects of quality Quality Quality Reliability fitness for purpose
ability to continue
working at accepted
quality level
Quality of Design
degree to which
design achieves purpose
Quality of Conformance
faithfulness with which the
operation agrees with design
Variables
things you can measure
Attributes
things you can assess
accept/reject

11. Total Quality Management
What does Total Quality Management include?
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!

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
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
Quality systems
Quality costing
Problem solving
Quality planning
Statistics
Process analysis
Quality standards
Error detection
Rectification
Inspection
Quality control
Quality assurance
Total Quality Management

13. The internal customer–supplier concept involves understanding the relationship between processes
External supplier
External customer
Process 1
Process 3
Process 2
Process 4
Process 5
Process 6
Between each process, the requirements of the ‘customer’ process must be understood and met by the 'supplier’ process

14. The traditional cost of quality model
Total cost of quality
Cost of errors = costs of prevention and appraisal
Costs
Cost of quality provision = costs of internal and external failure
‘Optimum’ amount of quality effort
Amount of quality effort

15. The traditional cost of quality model with adjustments to reflect TQM criticisms
Cost of errors = costs of prevention and appraisal
Total cost of quality
Costs
‘Optimum’ amount of quality effort
Cost of quality provision = costs of internal and external failure
Amount of quality effort

16. EFQM ‘Business excellence’ model
Leadership
People
Partnerships and resources
Processes
Key performance results
Policy and strategy
Customer results
People results
Society results

17. The quality gurus Quality is free – the optimum is zero defects
Philip Crosby
Quality is free – the optimum is zero defects
W. Edwards Deming
Deming’s 14 points
How to use statistics
Armand Feigenbaum
Total quality control
Kaoru Ishikawa
Quality circles and cause and effect diagrams
Joseph Juran
Quality as fitness for use, rather than conformance to specification
Genichi Taguchi
Loss function
Minimize variation

18. Stage in the development and launch process
The cost of rectifying errors becomes increasingly expensive the longer the errors remain uncorrected in the development and launch process
1000
100 10 1
10, 000
Cost to rectify error
Stage in the development and launch process
Pilot production
Market use
Prototype
Design
Concept

19. Total cost of quality Appraisal Internal failure Costs of quality
Increasing the effort spent on preventing errors occurring in the first place brings a more than equivalent reduction in other cost categories
Time
Costs of quality
Total cost of quality
Appraisal
Internal failure
Appraisal
Prevention

20. The pattern of some TQM programmes which run out of enthusiasm
Effectiveness of the TQM initiative
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

21. Some measure of operations performance
Process control charting
Some aspect of the performance of a process is often measured over time.
Question
‘Why do we do this?’
Time
Some measure of operations performance

22. Some measure of operations performance
Process control charting (Continued)
Trend can indicate whether performance is getting better or worse
Question
‘But why is variation important?’
Time
Some measure of operations performance
‘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?’

23. Some measure of operations performance
Process control charting (Continued)
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.
Time
Some measure of operations performance

24. Process control charting (Continued)
Sampling over a period of time…
0.8
2.2
3.6
After the second sample
0.8
2.2
3.6
After the first sample
0.8
2.2
3.6
Fitting a normal distribution to the histogram of sampled call times
0.8
2.2
3.6
By the end of the day
0.8
2.2
3.6
By the end of the second day

25. Process control charting
The chances of measurement points deviating from the average is predictable in a normal distribution
Process control charting
–3 standard
deviations
+3 standard
99.7% of points
–2 standard
deviations
+2 standard
95.4% of points
–1 standard
deviation
+1 standard
A standard
S = sigma
Frequency
68% of points
Elapsed time of call (seconds)

26. Some measure of operations performance
Process control charting
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.
Time
Some measure of operations performance

27. X X X Process variability A P A P A P A P Off target ACCURACY : P
Scatter PRECISION : P X
A P
A P

28. Low process variation allows changes in process performance to be readily detected
TIME
Process distribution A
Process distribution B A B
Process distribution B B
Process distribution A A
TIME

29. Alternating and erratic behaviour – Investigate.
In addition to points falling outside the control limits other unlikely sequences of points should be investigated
Alternating and erratic behaviour – Investigate.
UCL
C/L
LCL

30. Suspiciously average behaviour – Investigate.
In addition to points falling outside the control limits other unlikely sequences of points should be investigated (Continued)
UCL
C/L
LCL
Suspiciously average behaviour – Investigate.

31. Two points near control limit – Investigate.
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.

32. Five points one side of centre line – Investigate.
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.

33. Apparent trend in one direction – Investigate.
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.

34. Sudden change in level – Investigate.
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.

35. Process variation and its effect on process Defects per Million Opportunities (DPMO)
LSL
USL
LSL
USL
LSL
USL
LSL
USL
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

36. Ideal and real operating characteristics
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.
Producer’s risk (0.05)
1.0
0.9
0.8
0.7
In this real operating characteristic (where n = 250 and c = 1), both type 1 and type 2 errors will occur.
0.6
Probability of accepting the batch
0.5
0.4
Type 1 error
Type 2 error
0.3
0.2
0.1
AQL
LTPD
Consumer’s risk (1.0)
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
Percentage actual defective in the batch