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

• 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; http://psasir.upm.edu.my/id/eprint/97774/

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%.