Applying Fuzzy Control Chart in Earned Value Analysis: A New Application

As it is common in project management context, Earned value analysis usually integrates time and cost performance within the project scope. It helps the project manager to understand how to deal with project from two points of view. The first is to recognize current performance indexes and the second one is to provide a forecast to the future. However, most of decisions in this regard have taken based on Schedule Performance Index (SPI) and Cost Performance Index (CPI) while there is no a well organized control mechanism in which detect their situations as it is, not only numerically but also recognize/categorize current situation of the earned value management system linguistically. In this paper a fuzzy control chart approach associated with α-cut is presented in order to control earned value performance indexes including linguistics terms. Also a new application, based on a Multi Period-Multi Product (MPMP) production control problem is illustrated and successfully implemented. Key word: Earned value analysisfuzzy control chartlinguistic termproduction control problem

[1]  Ray W. Stratton.  Applying Earned Schedule Analysis to EVM data for Estimating Completion Date , 2007 .

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

[3]  Tzvi Raz,et al.  On the construction of control charts using linguistic variables , 1990 .

[4]  Hassen Taleb,et al.  On fuzzy and probabilistic control charts , 2002 .

[5]  T. Raz,et al.  Probabilistic and membership approaches in the construction of control charts for linguistic data , 1990 .

[6]  Alireza Faraz,et al.  Fuzzy Control Chart A Better Alternative for Shewhart Average Chart , 2007 .

[7]  Hiroshi Ohta,et al.  Control charts for process average and variability based on linguistic data , 1993 .

[8]  Osama Moselhi,et al.  Web‐based integrated project control system , 2004 .

[9]  Sooyoung Kim,et al.  Extended model for a hybrid production planning approach , 2001 .

[10]  Da Ruan,et al.  a-Cut fuzzy control charts for linguistic data , 2004 .

[11]  W. Woodall,et al.  A probabilistic and statistical view of fuzzy methods , 1995 .

[12]  Chi-Bin Cheng,et al.  Fuzzy process control: construction of control charts with fuzzy numbers , 2005, Fuzzy Sets Syst..

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

[14]  M. Marcucci.  MONITORING MULTINOMIAL PROCESSES , 1985 .

[15]  Chi-Bin Cheng.  Fuzzy process control based on fuzzy regression and possibility measures , 2003, 22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003.

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

[17]  Da Ruan,et al.  α‐Cut fuzzy control charts for linguistic data , 2004, Int. J. Intell. Syst..

[18]  Denis F. Cioffi.  A tool for managing projects: an analytic parameterization of the S-curve , 2005 .

[19]  Gad Vitner,et al.  Using data envelope analysis to compare project efficiency in a multi-project environment , 2006 .

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

[21]  Cengiz Kahraman,et al.  An alternative approach to fuzzy control charts: Direct fuzzy approach , 2007, Inf. Sci..

[22]  M. D. Byrne,et al.  Production planning: An improved hybrid approach , 2005 .

[23]  A. R. Crathorne,et al.  Economic Control of Quality of Manufactured Product. , 1933 .

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

[25]  M. D. Byrne,et al.  Production planning using a hybrid simulation – analytical approach , 1999 .