1. Process Improvement: Quality Assurance, Control, and Management
Miles Hamby, Ph.D.
Copyright©2011 Miles M. Hamby

2. Quality Definitions
Quality ~ conformance to requirements and “fitness for use” (Juran)
Quality Management ~ “ensuring the process will consistently produce the desired product.” (Hamby)
Philosophy ~ Gold plating is bad; prevention of over inspection is good

3. Quality Characteristics
Grade vs. Quality
Grade: meets spec requirements
Quality: behaves as expected
Prevention vs. Inspection
Management Responsibility
Processes
Customer Satisfaction
Keep customer informed
Stick to requirements

4. Quality Processes Quality Planning
Quality standards and methods to meet them
Planning
Quality Assurance
Improvements, audits, measurement comparisons, considering standards appropriateness
Executing
Quality Control
Measuring/testing errors, measuring schedule performance, comparing results to standard
Controlling

5. Quality Planning Tools
Standards
Benchmarking (past analysis)
Benefit/Cost Analysis (BCI)
Flowchart (future analysis)
Design of Experiments (what if?)
Fishbone Diagram (also used in QC)
Cost of Quality (costs of conformance & non-conformance)

6. Cost of Quality Cost of Conformance Prevention Appraisal Planning
Training
Auditing
Controlling
Cost of Nonconformance
Failure Costs
Internal (pre customer)
External (post customer)
Scrap
Rework
Expediting
Warranty
Service
Recalls

7. Quality Assurance Tools
Evaluation against standards on regular basis
Re-evaluation of standards, methods, and procedures
Quality Audit: structured review of quality activities that identifies lessons learned

8. Quality Control Tools Inspection Pareto Diagram Fishbone Diagram
Checklists
Statistical Sampling
Control Charts
Flow charting (also used in Quality Planning)
Trend Analysis

9. Quality Techniques Continuous Process Improvement (Kaizen)
Just in Time (JIT)
Total Quality Management (TQM) (Juran)

10. Key Quality Gurus Walter Shewhart Edward Demming Joseph Juran
Phillip Crosby
Genichi Taguchi
Kaoru Ishikawa

11. “Grandfather of Quality Management”
Walter Shewhart (1891 – 1968)
“Grandfather of Quality Management”
“The object of industry is … to reduce everything possible to routines requiring a minimum amount of human effort.”
Shewhart Cycle – PDCA
“Deviations in the results of a routine process outside [statistical] limits indicate that the routine has broken down and will no longer be economical until the cause of trouble is removed.”

12. Shewhart Control Charts
Product Variation – due to “assignable” causes and “chance” causes
Objective – reduce variation from assignable causes
Technique – use Statistical charts to measure variation
UCL = Accepted value + k*process standard deviation
LCL = Accepted value - k*process standard deviation

13. Edward Demming (1900 – 1993) 14 POINTS
1."Create constancy of purpose towards improvement". Replace short-term reaction with long-term planning.
2."Adopt the new philosophy". The implication is that management should actually adopt his philosophy, rather than merely expect the workforce to do so.
3."Cease dependence on inspection". If variation is reduced, there is no need to inspect manufactured items for defects, because there won't be any.
4."Move towards a single supplier for any one item." Multiple suppliers mean variation between feedstocks.
5."Improve constantly and forever". Constantly strive to reduce variation.
6."Institute training on the job". If people are inadequately trained, they will not all work the same way, and this will introduce variation.
7."Institute leadership". Deming makes a distinction between leadership and mere supervision. The latter is quota- and target-based.

14. Demming’S 14 Points (cont)
8."Drive out fear". Demming sees management by fear as counter- productive in the long term, because it prevents workers from acting in the organization's best interests.
9."Break down barriers between departments". Another idea central to TQM is the concept of the 'internal customer', that each department serves not the management, but the other departments that use its outputs.
10."Eliminate slogans". Another central TQM idea is that it's not people who make most mistakes - it's the process they are working within. Harassing the workforce without improving the processes they use is counter- productive.
11."Eliminate management by objectives". Demming saw production targets as encouraging the delivery of poor-quality goods.
12."Remove barriers to pride of workmanship". Many of the other problems outlined reduce worker satisfaction.
13."Institute education and self-improvement".
14."The transformation is everyone's job".

15. If answer to any is “no”, then Management controllable
Joseph Juran (1904 – 200)
First to think of the “cost of poor quality”
“TQM” ~ Total Quality Management
Juran’s Quality Process
Measure your product
Compare it to a standard
Act on the difference
Who has control over errors ~
80% controllable by management; only 20% by operator
Does the operator know what he is supposed to be doing?
Does the operator know what he is doing?
Does the operator have the tools to do what he is doing?
If answer to any is “no”, then Management controllable

16. Phillip Crosby (1926 – 2001) “Zero Defects”
Originated with Martin-Marietta, adopted by Dept of Defense in 60s
Quality is conformance to requirements
Defect prevention is preferable to quality inspection and correction
“Zero” Defects is the quality standard
Quality is measured in monetary terms – the Price of Nonconformance (PONC)

17. Kaoru Ishikawa (1915 – 1989)
Cause and Effect - loss of quality in a product is and effect caused by something in the process
Fishbone diagram - Product is the “head” of the fish; “bones” are the various process
inputs; “sub-branches” within each bone are “causes” of errors in the process.
Introduced Quality Circle concept to Japanese manufacturing

18. Genichi Taguchi (1924 - ) Quality Loss function
Quality loss all the way through to the customer, including cost of scrap, rework, downtime, warranty claims and ultimately reduced market share.
Costs of quality varies with product deviation from the mean. Loss (L) is a function of the variance (σ) from the target (m).
L = k (x – t)2
Where: L = Loss in Dollars x = Quality Characteristic (diameter, no. of errors, etc) t = Target Value for x k = Constant

19. Optimal Quality and Responsibility
Marginal Analysis
Optimal quality is reached at point where incremental value from improvement = incremental cost to secure it.
Responsibility for Quality
Senior management is responsible for organizational quality
PM has ultimate responsibility for quality of product of project
Each team member is responsible for self inspection

20. Statistical Terms
Mean ~ Arithmetic average obtained by dividing the sum of data by the number of data in the set
Median ~ Middle value of a set of data in rank order
Mode ~ most frequently occurring value (possible to have more than one mode)
Standard Deviation (Sigma) ~ square root of the average sum of the squared deviations from the mean ~ indicates probability of occurrence in a distribution
Six-Sigma ~ plus and minus 3 standards deviation from the mean of a distribution

21. Estimating the Standard Deviation
PERT estimate
(Project Evaluation and Review Technique)
1Sigma (σ)  range between pessimistic estimate (P) and optimistic estimate (O) divided by 6 _ X
-1 σ 1σ
2 σ
3 σ
-3 σ
-2 σ  P O

22. Sigma - level
Number of “Sigma” represents level of quality desired, ie., number of errors acceptable
EG ~
6 sigma (± 3σ) translates to 27 errors out of 10,000 units (ie, 99.73% probability error-free)
12 sigma (± 6σ) translates to 1 error out of 10,000 units (ie, 99.99% probability error-free) _ X
-1 σ 1σ
2 σ
3 σ
-3 σ
-2 σ 
-6σ 6σ

23. Statistical Sampling Quality Control Chart
Graphic display of results, over time, of a process… used to determine if the process is “in control.”
To create a control chart:
Samples are taken
Variables are measured
Attributes are found and plotted on chart

24. Monitoring Project Results
Variable - anything measured
Attribute - binary value, ie, either right or wrong
Probability - likelihood event will occur, usually expressed as %

25. Control Chart Features
Control Limits
Acceptable range of variation of a process often shown as 2 dashed lines on chart
Upper and Lower Control Limits are determined by organization’s sigma quality standard
Specification Limits
Contractual requirements for performance and quality
Not calculated based on control chart
Outside chart control limits if project can meet
Inside chart control limits if project cannot meet

26. Statistical Process Control
Out of Statistical Process Control (“Out of control”)
Errors exceed UCL or LCL
Indicates lack of consistency or predictability in process

27. Rule of Seven
Heuristic - non-random data points grouped together in a series that total 7 on one side of mean
Assignable Cause - data point or Rule of Seven that requires investigation to determine cause of variation.

28. Process Improvement: Quality Assurance, Control, and Management
Miles Hamby, Ph.D.
Copyright©2011 Miles M. Hamby