Research Article
Integrating Fuzzy AHP and Fuzzy TOPSIS Models for Construction Equipment Maintenance Strategy Selection
Girmay Getawa Ayalew*
,
Genet Melkamu Ayalew
Issue:
Volume 11, Issue 2, June 2025
Pages:
33-61
Received:
23 May 2025
Accepted:
13 June 2025
Published:
30 June 2025
Abstract: Maintenance is the combination of all technical, administrative, and managerial actions during the life cycle of an item intended to retain it in, or restore it to a state in which it can perform the required function under normal stated operating conditions. Maintenance management is a crucial element that governs the economic value of the organization itself. Maintenance costs constitute a major part of the total operating costs of all construction equipment. Currently, industries are facing a lot of challenges encountered due to the continually evolving world of technologies, and environmental and safety requirements. Thus, the study was focused on Integrating Fuzzy AHP and Fuzzy TOPSIS Models for Construction Equipment Maintenance Strategy Selection. The evaluation was a multiple-criteria decision-making problem. The fuzzy AHP and fuzzy TOPSIS methods were used as an evaluation tool. To achieve the objective, the data were collected from primary and secondary source of data collection. The method of data analysis for this study was made by integrated methodology, and the analysis was made by using Microsoft Excel. The study revealed that skill development, production waste, product quality, health and safety training, and facilities are important criteria. The finding revealed that preventive maintenance and time-based maintenance were the best maintenance strategies.
Abstract: Maintenance is the combination of all technical, administrative, and managerial actions during the life cycle of an item intended to retain it in, or restore it to a state in which it can perform the required function under normal stated operating conditions. Maintenance management is a crucial element that governs the economic value of the organiz...
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Research Article
Development of Cost Prediction Model for Improving Cost Estimate at Completion of Building Construction Projects Using MATLAB R2014a Simulink, and Regression Model
Girmay Getawa Ayalew*,
Genet Melkamu Ayalew
Issue:
Volume 11, Issue 2, June 2025
Pages:
62-89
Received:
21 June 2025
Accepted:
7 July 2025
Published:
28 July 2025
DOI:
10.11648/j.ijmfs.20251102.12
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Abstract: The success of a project is obtained through the proper management from the beginning to the end of the project. Several studies have been conducted in the project management field further to improve the earned value management methodology to forecast the project cost estimate at completion. However, this study provides to investigate a new research methodology proposed to provide more reliable CEAC by using MATLAB R2014a and Multiple regressions. Thus, the main objective of this study is to focus on the development of a cost prediction model for improving cost estimate at completion of building construction projects using MATLAB R2014a, and regression model. The study is conducted on an EVM data set comprising five real-life projects database gathering between 2021 and 2024. The analysis method was made by using Microsoft excel, MATLAB R2014a, and a statistical package for social science as an analysis tool. The finding of the study revealed that the dependability of EAC on input variable produced by the membership function, and rule viewer is 70% of the estimate at compilation which is quite an acceptable value. It was also found that the regression model shows excellent results in prediction with a coefficient of correlation is 95.70%, 99.90%, 96.10%, 92.40%, and 90.40% for the five projects. Similarly, the coefficient of determination is 91.70%, 99.99%, 92.40%, 85.40%, and 81.70% respectively for the five projects. Finally, it can be recommended that the developed model be conducted in building projects to demonstrate its practicality.
Abstract: The success of a project is obtained through the proper management from the beginning to the end of the project. Several studies have been conducted in the project management field further to improve the earned value management methodology to forecast the project cost estimate at completion. However, this study provides to investigate a new researc...
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