Procurement

1
Project Contracting

• Procurement Quality Management
• Unit 10
• Quality Control

2
Agenda

• Recap of Unit 9
• Quality Control

Source PMBOK, 2000
3
Todays Learning Objectives

• Define the Quality Control Process
• Identify the Quality Control Tools
• Discuss the difference between quality planning,
  quality assurance and quality control

Source PMBOK, 2000
4
Quality Control
Source PMBOK, 3rd edition
5
Quality Control

• Many projects, because of their temporary and
  unique characteristics, do not directly use
  statistical methods
• However, products and services from vendors and
  suppliers directly impact project success
• Therefore, project managers should have a least a
  general understanding of the practices and
  procedures of statistical quality control

6
Quality Control Tools Techniques

• A statistical point of view moves decision-making
  from subjective ? objective
• This provides the benefits of
• Improved process information
• Better communication
• Discussion based on facts
• Consensus for action
• Information for process changes
• The measurement of variance and the resulting
  information forms the basis for continuous
  improvement

7
What do Quality control systems do?
8
Quality Control Tools Techniques

• Cause and effect diagram
• Control Charts
• Flowcharting
• Histogram
• Pareto Chart
• Run Chart
• Scatter Diagram
• Statistical Sampling
• Inspection
• Defect Repair Review

9
Cause-and-effect Analysis

• After identifying a problem, it is necessary to
  identify its cause
• Uses diagramming to identify the relationship
  between an effect and its cause
• Also known as fishbone diagrams

Cause
Effect
Machine
Method
Material
Problem Statement
Environment
Personnel
Measurement
Kernzer, Project Management, 2003
10
Cause-and-effect Analysis

• Steps
• Identify the problem
• Select interdisciplinary brainstorming team
• Setup categories
• Identify defect causes
• Random method
• Systematic method
• Process analysis method
• Identify corrective action

11
Control Charts

• Graphic displays of results over time to
  determine whether a project is in control
• Control charts measure variation
• Every process has some sort of deviation/variation
  
• The upper and lower control limits (UCL and LCL)
  assist in establishing conformance to standards

12
Control Charts Benefits

• The power of control charts is in their ability
  to determine if the cause of variance is special
  or common and whether the variation is in the
  allowable range
• Control charts aim to keep processes in
  satisfactory control, as opposed to downstream
  inspection which identify defects after the fact
• Therefore control charts are focused on
  prevention rather than detection/rejection

13
Control Chart Interpretation
Out Of Control
Runs

• Occurs when a data point exceeds either the UCL
  or LCL

• Occurs when successive points line up on one side
  of the process average
• If the run has a length of seven points, there is
  an abnormality in the process. Always investigate
  the rule of 7!

14
Control Chart Interpretation
Trends

• Occurs when there is a continued rise or fall
• If a trend has a length of seven points, there is
  an abnormality in the process

15
Control Chart Interpretation
Cycle/Periodicity

• Points show the same pattern of change over equal
  intervals

16
Causes of Variance

• Common cause (random)
• This source of random variation is present in any
  process (inherent in the process)
• This variation can be corrected only by a
  management decision to change the process and can
  be difficult to isolate the problem
• Special cause
• Can be controlled at the local level you can
  point to it and say that is the problem
• Indicated by a point on the control chart that is
  beyond the control limit or by a persistent trend
  approaching the control limit
• Unless all special causes are corrected, they
  will continue to affect the process in
  unpredictable ways

17
Definitions

• Tolerances The result is acceptable if it falls
  within the range specified by the tolerances
• Control Limits The process is in control if it
  falls within the control limits

18
Pareto Analysis

• Rank ordering items to guide corrective action.
• 80 of something is caused by 20 of something
  else!

19
Pareto Analysis
L. Ireland, Quality Management for Projects
Programs, 1991
Before Improvement
After Improvement
Overall Effect of Change
100
100
100
80
80
75
100
60
60
No. of Defective Cases
No. of Defective Cases
Percentage
Percentage
50
40
40
25
20
20
Wobble
Wobble
Noise
Others
Noise
Others
Case Wobble
Case Wobble
Improper Rotation
Improper Rotation
Pressure
Pressure
Axle Caulking
Axle Caulking
20
Scatter Diagrams

• Organizes data using two variables an
  independent variable and a dependent variable
• The data is then recorded on a graph showing the
  relationship between the variables

Y
X
Curvilinear Correlation
Y
Y
X
X
Positive Correlation
Negative Correlation
21
Histograms

• Graphical representation of data at a single
  point in time
• Useful in understanding the relative frequency of
  the data and its distribution

120
100
80
Frequency
60
40
20
Test
System Integration
Motor Static Test
Motor Integration
Manufacturing Process Failures
Kernzer, Project Management, 2003
22
The Normal Curve
23
Next Week

• Unit 11 Other Quality Issues and Topics
• Reading
• Text Chapters VI, VII