Monitoring project duration and cost in a construction project by applying statistical quality control charts

Abstract The earned value is a leading technique in monitoring and analyzing project performance and project progress. Although, it allows exact measurement of project progress, and can uncover any time and cost deviations from the plan, its capability in reporting accepted level of deviation is not well studied. This study presented an approach to overcome this limitation by applying statistical quality control charts to monitor earned value indices. For this purpose, project time and cost performance indices of a real construction project were monitored regularly on individual control charts. The results were quite promising, and not only competed well against traditional approaches, but also enhanced team's knowledge of project performance. At the end, it was concluded that the proposed approach improves substantially the project controlling scheme and enhances the capability of earned value technique.

[1]  Saad H.S. Al-Jibouri,et al.  Monitoring systems and their effectiveness for project cost control in construction , 2003 .

[2]  Denis F. Cioffi,et al.  Designing project management: A scientific notation and an improved formalism for earned value calculations , 2004 .

[3]  L. M. Naeni,et al.  A fuzzy approach for the earned value management , 2011 .

[4]  Ofer Zwikael,et al.  Prediction of project outcome The Application of statistical methods to earned value management and earned schedule performance indexes , 2009 .

[5]  Sou-Sen Leu,et al.  Project Performance Evaluation Based on Statistical Process Control Techniques , 2008 .

[6]  Walt Lipke Further Study of the Normality of CPI and SPI(t) , 2011 .

[7]  Mario Vanhoucke,et al.  A comparison of different project duration forecasting methods using earned value metrics , 2006 .

[8]  Rory Burke,et al.  Project Management: Planning and Control Techniques , 2001 .

[9]  Ronie Navon,et al.  Automated project performance control of construction projects , 2005 .

[10]  W. Edward Back,et al.  PROBABILISTIC FORECASTING OF PROJECT PERFORMANCE USING STOCHASTIC S CURVES , 2004 .

[11]  Douglas C. Montgomery,et al.  Introduction to Statistical Quality Control , 1986 .

[12]  H. Steyn A framework for managing quality on system development projects , 2008, PICMET '08 - 2008 Portland International Conference on Management of Engineering & Technology.

[13]  David S. Christensen,et al.  Some Empirical Evidence on the Non-Normality of Cost Variances on Defense Contracts , 2000 .

[14]  Rashmi Rohan Shenoy,et al.  Misuse and performance of individuals charts in statistical process control for single parameter distributions of unknown stability , 2008 .

[15]  F.T. Anbari,et al.  Earned Value Project Management Method and Extensions , 2003, IEEE Engineering Management Review.

[16]  Gabriel A. Barraza,et al.  Probabilistic Control of Project Performance Using Control Limit Curves , 2007 .

[17]  Quentin W. Fleming,et al.  Earned Value Project Management , 1996 .

[18]  Michael R. Duffey,et al.  A model for effective implementation of Earned Value Management methodology , 2003 .

[19]  Tarek Hegazy,et al.  Project performance control in reconstruction projects , 2000 .