Rough Set Theory (RST) is a data mining technique which is used to deal with vagueness and uncertainty emphasized in decision making. The objective of this paper is to analyze Faults Repairing System (FRS) based on RST before and after applying a suggested algorithm for labor force redistribution. In the first, the indiscernibility relation groups together faults that are indiscernible into equivalence classes, which allowing calculating reducts, FRS analysis in the view of decision regions. Then, Labor Force Redistribution Algorithm (LFRA) is implemented to redistribute faults to malfunctions repairs technicians in the same central or in the cluster according to a set of parameters. Finally, analyzing FRS based on rough sets after applying LFRA. The proposed methodology will be implemented using TE Company as a case study. The results showed that LFRA will improve the accuracy of approximation, maximize the percentage of faults which certainly can be repaired on the same day and minimize the percentage of faults which certainly can’t be repaired on the same day.
E. Emam, O.; S. Farhan, M.; and A. Abohany, A.
"Faults Repairing Analysis Using Rough Sets after Implementation of Labor Force Redistribution Algorithm: A Case Study in Telecom Egypt,"
Information Sciences Letters: Vol. 6
, Article 2.
Available at: https://digitalcommons.aaru.edu.jo/isl/vol6/iss3/2