Badiru / Agustiady Statistical Techniques for Project Control

Erscheinungsjahr 2012
ISBN: 978-1-4200-8318-7
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 412 Seiten

Reihe: Industrial Innovation Series

Winner of the IIE Book of the Month for June 2012
A project can be simple or complex. In each case, proven project management processes must be followed. In all cases of project management implementation, control must be exercised in order to assure that project objectives are achieved. Statistical Techniques for Project Control seamlessly integrates qualitative and quantitative tools and techniques for project control. It fills the void that exists in the application of statistical techniques to project control.
The book begins by defining the fundamentals of project management then explores how to temper quantitative analysis with qualitative human judgment that makes project control nebulous but also offers opportunities to innovate and be creative in achieving control. The authors then discuss the three factors (time, budget, and performance) that form the basis of the operating characteristics of a project that also help determine the basis for project control. They then focus on computational network techniques for project schedule (time) control.

Although designed as a practical guide for project management professionals, the book also appeals to students, researchers, and instructors.

Autoren/Hrsg.

Badiru, Adedeji B.

Agustiady, Tina

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Management Projektmanagement

Inhaltsverzeichnis

Fundamentals of Project Management
Why Projects Fail
Management by Project
Integrated Project Implementation
Critical Factors for Project Success
Early Systems Engineering
DODAF Systems Architecture for Project Management
Project Management Body of Knowledge (PMBOK®)

Project Systems Structure

Project Systems Implementation Outline

Value of Lean Times

Project Decision Analysis
Systems Group Decision-Making Models
Hierarchy of Project Control

Statistics for Project Control

Modeling Project Environment

Use of Statistics in Project Control
Normal Distribution
Relationship to Six Sigma
Statistical Averages
Statistical Thinking: Computational Examples
Factors of Project Control

Examples of Statistics for Project Control
Statistics for Production Changeovers
General Control Steps
Formal and Informal Control
Schedule Control
Performance Control
Continuous Performance Improvement
Cost Control
Information Required for Project Control

Control Charts

Project Time Control
Critical Path Method
Determination of Critical Activities
Using Forward Pass to Determine Critical Path

Subcritical Paths

Gantt Chart

Activity Crashing and Schedule Compression

PERT Network Analysis

Modeling Activity Times

Beta Distribution

Triangular Distribution

Uniform Distribution

Statistical Analysis of Project Duration

Precedence Diagramming
Reverse Criticality in PDM Networks

References

Project Performance Control

Importance of Work Performance Measurement

Basic Techniques of Performance Work Sampling

Performance Confidence Interval

Sample Size Calculations

Control Charts for Performance Control

Applications of Work Sampling

Learning Curve Analysis for Performance Control

Univariate Learning Curve Models

Impacts of Multivariate Learning Curves

Summary of Cost, Time, and Performance Formulas

References

Project Cost Control

Cost Concepts and Definitions

Project Cash Flow Analysis

Effects of Inflation

Breakeven Analysis

Profit Ratio Analysis

Amortization of Capital

Project Cost Estimation

Budgeting and Capital Allocation

Cost Monitoring

Project Balance Technique
Activity-Based Costing
References

Project Quality Control

Quality Management: Step-By-Step Implementation

Six Sigma and Quality Management

Taguchi Loss Function

Identification and Elimination of Sources of Defects

Roles and Responsibilities for Six Sigma

Process Capability Analysis for Six Sigma
Lean Principles and Applications
Lean Six Sigma in Project Management

Lean Principles for Project Control

Lean and Six Sigma

Pull Technique
Lean Action Plan

Six Sigma and Statistical Modeling

Six Sigma and Statistics

Selecting Proper Statistical Techniques
Six Sigma Methodology
Hypothesis Testing

t Testing

Confidence Interval

Capability Analysis
Gage R&R

Project Control Case Studies

Gage R&R

Capability Studies

Analytical Studies

Multivariate Studies

Management Support for Project Control
Leadership
SigmSResource Allocation by Management

Appendix: Useful Statistical Distributions
Index