Using the Earned Value Management System to Improve Electrical Project Control

2012 ◽  
Vol 138 (3) ◽  
pp. 449-457 ◽  
Author(s):  
Awad S. Hanna
Keyword(s):  
Management System ◽  
Value Management ◽  
Project Control ◽  
Earned Value ◽  
Earned Value Management

Design and Realization of Defense Equipment Scientific Research Project Management System Based on Earned Value Management

2014 ◽  
Vol 971-973 ◽  
pp. 2317-2320
Author(s):  
Xiang Jun Yu ◽  
Chao Xie ◽  
Tian Ming Huang
Keyword(s):  
Project Management ◽  
Management System ◽  
Scientific Research ◽  
Design System ◽  
Value Management ◽  
Earned Value ◽  
Research Project ◽  
Earned Value Management ◽  
Project Management System ◽  
Scientific Research Project

This paper briefly introduces the basic connotation of earned value management, determine, from the target variable management process design, system function design and system implementation four aspects that the management of defense scientific research project management system design and implementation process based on the earned value, and some reasonable countermeasures to promote the use of the system.

Project Control Using a Bayesian Approach

2018 ◽  
pp. 5679-5689
Author(s):  
Franco Caron
Keyword(s):  
Bayesian Approach ◽  
Early Stage ◽  
Reliable Estimate ◽  
Value Management ◽  
Project Control ◽  
Earned Value ◽  
Earned Value Management ◽  
Project Complexity ◽  
Project Data ◽  
High Level

The capability to elaborate a reliable estimate at completion for a project since the early stage of project execution is the prerequisite in order to provide an effective project control. The non-repetitive and uncertain nature of projects and the involvement of multiple stakeholder increase project complexity and raise the need to exploit all the available knowledge sources in order to improve the forecasting process. Therefore, drawing on a set of case studies, this paper proposes a Bayesian approach to support the elaboration of the estimate at completion in those industrial fields where projects are denoted by a high level of uncertainty and complexity. The Bayesian approach allows to integrate experts' opinions, data records related to past projects and data related to the performance of the ongoing project. Data from past projects are selected through a similarity analysis. The proposed approach shows a higher accuracy in comparison with the traditional formulas typical of the Earned Value Management (EVM) methodology.

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