A comprehensive fuzzy decision-making method for determining optimum machining strategy in production line improvement

The manufacturing sector plays a significant role in utilizing the economy of a country. Statistically, more than 37.4% of the GDP of Malaysia belongs to industries. Having a production strategy, which relies on the reality of an industrial environment, will enhance the success of that busines...

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Main Author:	Alazemi, Fahad KH A O H
Format:	Thesis
Language:	English
Published:	2021
Subjects:	Fuzzy decision making Decision-making Mathematical optimization
Online Access:	http://psasir.upm.edu.my/id/eprint/97774/1/FK%202021%2051%20UPMIR.pdf
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spelling	my-upm-ir.977742022-07-01T08:22:06Z A comprehensive fuzzy decision-making method for determining optimum machining strategy in production line improvement 2021-09 Alazemi, Fahad KH A O H The manufacturing sector plays a significant role in utilizing the economy of a country. Statistically, more than 37.4% of the GDP of Malaysia belongs to industries. Having a production strategy, which relies on the reality of an industrial environment, will enhance the success of that business. Therefore, it is crucial to propose methods to skyrocket the production factors such as production time. An in-depth review of the literature during the last half-century found that many research studies have been carried out to utilize the production line performances. One major gap found by the literature review is that many industries do not pay enough attention to the factors that can enhance productivity. Such ignorance yields too many problems and sometimes failing to manufacture enough products to fulfill the market demand. Such problems often can be found in small and medium-scale companies in developing countries. Besides, in the real industrial environment, most factors are uncertain and can get various values depending on different conditions. Such phenomena even worsen the condition for forecasting the effective factors in an industrial company. The primary objective of current research is to develop a comprehensive fuzzy decision-making method for determining the optimum machining strategy in order to utilize the completion time of a product. For this purpose, finding the effective factors on completion time in production lines and identifying the correlations between factors are considered the next objectives. For this purpose, using the library study and interview with the experts, a list of factors was found. Then a questionnaire is designed and distributed to the academic and industry experts. According to the findings, the effective internal factors in minimizing product completion time can be divided into five main clusters: Technology, Human Resource, Machinery, Material, and Facility Design. Then using the statistical analysis, the correlations between factors are found. It is found that there are positive correlations exist between most of the factors in a range between -0.048 and 0.636 at a significant level of 0.05 which means they may have positive or negative interactions while happens at the same time in an industrial environment. In continue, using the regression method, the impact of each factor on the dependent variable for the research (product completion time) is determined. Using the data gathered from the experts, a Fuzzy Inference System (FIS) model was developed, which could reflect the uncertainty of the factors in decreasing (or increasing) the product completion time in manufacturing systems. Then, a hybrid Fuzzy-TOPSIS based heuristic is developed using MATLAB to solve the case studies. In order to evaluate the performance of the proposed heuristic method, a number of experiments are designed and solved by Taguchi Method (DOE). Then, the performance of the method was evaluated using several indicators, including completion time. Our findings showed that the Human resource, Machinery, Material, Technology and Social Environment positively minimize product completion time, respectively. It is found that the proposed Fuzzy-TOPSIS heuristic is capable of reducing the product completion time in a range between 0 and 10.3%. Fuzzy decision making Decision-making Mathematical optimization 2021-09 Thesis http://psasir.upm.edu.my/id/eprint/97774/ http://psasir.upm.edu.my/id/eprint/97774/1/FK%202021%2051%20UPMIR.pdf text en public doctoral Universiti Putra Malaysia Fuzzy decision making Decision-making Mathematical optimization Mohd Ariffin, Mohd Khairol Anuar
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English
advisor	Mohd Ariffin, Mohd Khairol Anuar
topic	Fuzzy decision making Decision-making Mathematical optimization
spellingShingle	Fuzzy decision making Decision-making Mathematical optimization Alazemi, Fahad KH A O H A comprehensive fuzzy decision-making method for determining optimum machining strategy in production line improvement
description	The manufacturing sector plays a significant role in utilizing the economy of a country. Statistically, more than 37.4% of the GDP of Malaysia belongs to industries. Having a production strategy, which relies on the reality of an industrial environment, will enhance the success of that business. Therefore, it is crucial to propose methods to skyrocket the production factors such as production time. An in-depth review of the literature during the last half-century found that many research studies have been carried out to utilize the production line performances. One major gap found by the literature review is that many industries do not pay enough attention to the factors that can enhance productivity. Such ignorance yields too many problems and sometimes failing to manufacture enough products to fulfill the market demand. Such problems often can be found in small and medium-scale companies in developing countries. Besides, in the real industrial environment, most factors are uncertain and can get various values depending on different conditions. Such phenomena even worsen the condition for forecasting the effective factors in an industrial company. The primary objective of current research is to develop a comprehensive fuzzy decision-making method for determining the optimum machining strategy in order to utilize the completion time of a product. For this purpose, finding the effective factors on completion time in production lines and identifying the correlations between factors are considered the next objectives. For this purpose, using the library study and interview with the experts, a list of factors was found. Then a questionnaire is designed and distributed to the academic and industry experts. According to the findings, the effective internal factors in minimizing product completion time can be divided into five main clusters: Technology, Human Resource, Machinery, Material, and Facility Design. Then using the statistical analysis, the correlations between factors are found. It is found that there are positive correlations exist between most of the factors in a range between -0.048 and 0.636 at a significant level of 0.05 which means they may have positive or negative interactions while happens at the same time in an industrial environment. In continue, using the regression method, the impact of each factor on the dependent variable for the research (product completion time) is determined. Using the data gathered from the experts, a Fuzzy Inference System (FIS) model was developed, which could reflect the uncertainty of the factors in decreasing (or increasing) the product completion time in manufacturing systems. Then, a hybrid Fuzzy-TOPSIS based heuristic is developed using MATLAB to solve the case studies. In order to evaluate the performance of the proposed heuristic method, a number of experiments are designed and solved by Taguchi Method (DOE). Then, the performance of the method was evaluated using several indicators, including completion time. Our findings showed that the Human resource, Machinery, Material, Technology and Social Environment positively minimize product completion time, respectively. It is found that the proposed Fuzzy-TOPSIS heuristic is capable of reducing the product completion time in a range between 0 and 10.3%.
format	Thesis
qualification_level	Doctorate
author	Alazemi, Fahad KH A O H
author_facet	Alazemi, Fahad KH A O H
author_sort	Alazemi, Fahad KH A O H
title	A comprehensive fuzzy decision-making method for determining optimum machining strategy in production line improvement
title_short	A comprehensive fuzzy decision-making method for determining optimum machining strategy in production line improvement
title_full	A comprehensive fuzzy decision-making method for determining optimum machining strategy in production line improvement
title_fullStr	A comprehensive fuzzy decision-making method for determining optimum machining strategy in production line improvement
title_full_unstemmed	A comprehensive fuzzy decision-making method for determining optimum machining strategy in production line improvement
title_sort	comprehensive fuzzy decision-making method for determining optimum machining strategy in production line improvement
granting_institution	Universiti Putra Malaysia
publishDate	2021
url	http://psasir.upm.edu.my/id/eprint/97774/1/FK%202021%2051%20UPMIR.pdf
_version_	1747813803498668032

A comprehensive fuzzy decision-making method for determining optimum machining strategy in production line improvement

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