Document Details

Document Type : Thesis 
Document Title :
PRODUCTIVITY ANALYSIS OF TECHNICIANS IN ABDUL LATIF JAMEEL COMPANY
تحليل إنتاجية الفنيين بشركة عبداللطيف جميل
 
Subject : Faculty of Engineering - Department of Industrial Engineering 
Document Language : Arabic 
Abstract : This Thesis highlights the importance of performance measurement and productivity analysis. The thesis supports that performance measurement and productivity analysis are major factors in present times, which help the organizations and other agencies in the identification of problem areas. This in turn assists the management to set goals and objectives and work out strategies and action plans for the improvement. The improvement will allow the organizations to have a better market standing and customer’s satisfaction. Primarily, this study presents the evaluation of productivity of the young Saudi employees hired as technicians by Abdul Latif Jameel Company. These technicians are required to sell mechanical hours, on the basis of which they are provided with benefits and incentives. The Service Department is responsible for monitoring performance against the targets set by the firm. The Adaptive Neuro Fuzzy Inference System (ANFIS) has been used in this study for the productivity analysis of technicians in the Abdul Latif Jameel Company. A class of adaptive networks were proposed which was functionally equivalent to fuzzy inference systems. This ANFIS describes how to decompose the parameters set to facilitate the hybrid learning rules for the constitution of the ANFIS architecture that represents the Sugeno-type fuzzy inference system. It applies a combination of the least-squares method and back-propagation gradient descent method for training FIS membership function parameters to emulate a given data set As result, on the basis of errors value obtained through these methods, fuzzy inference of productivity has been determined. The productivity was vary according to the inputs and the method that been used. The ANFIS can produce crisp numerical outcomes to predict the technician’s performance. It provides an alternative solution to deal with imprecise data. It reflects the way people think and make judgments for a group of technicians as well as a single technician’s achievements. The results of the ANFIS model are as robust as statistical methods and encourage a more natural way to interpret the technician’s outcomes. 
Supervisor : Dr. Osman Taylan 
Thesis Type : Master Thesis 
Publishing Year : 1435 AH
2014 AD 
Co-Supervisor : DR. Muntasir M. Sheikh 
Added Date : Wednesday, October 15, 2014 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
عبدالله عبد العزيز الشهريAl-Shehri, Abdullah Abdul AzizResearcherMaster 

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