Evaluation and Selection of the Quality Methods for Manufacturing Process Reliability Improvement-Intuitionistic Fuzzy Sets and Genetic Algorithm Approach
Апстракт
The aim of this research is to propose a hybrid decision-making model for evaluation and selection of quality methods whose application leads to improved reliability of manufacturing in the process industry. Evaluation of failures and determination of their priorities are based on failure mode and effect analysis (FMEA), which is a widely used framework in practice combining with triangular intuitionistic fuzzy numbers (TIFNs). The all-existing uncertainties in the relative importance of the risk factors (RFs), their values, applicability of the quality methods, as well as implementation costs are described by pre-defined linguistic terms which are modeled by the TIFNs. The selection of quality methods is stated as the rubber knapsack problem which is decomposed into subproblems with a certain number of solution elements. The solution of this problem is found by using genetic algorithm (GA). The model is verified through the case study with the real-life data originating from a signifi...cant number of organizations from one region. It is shown that the proposed model is highly suitable as a decision-making tool for improving the manufacturing process reliability in small and medium enterprises (SMEs) of process industry.
Кључне речи:
selection of quality methods / manufacturing process / intuitionistic fuzzy sets / genetic algorithmИзвор:
Mathematics, 2021, 9, 13Издавач:
- MDPI, Basel
DOI: 10.3390/math9131531
ISSN: 2227-7390
WoS: 000670946200001
Scopus: 2-s2.0-85109368349
Колекције
Институција/група
Mašinski fakultetTY - JOUR AU - Gojković, Ranka AU - Đurić, Goran AU - Tadić, Danijela AU - Nestić, Snežana AU - Aleksić, Aleksandar PY - 2021 UR - https://machinery.mas.bg.ac.rs/handle/123456789/3482 AB - The aim of this research is to propose a hybrid decision-making model for evaluation and selection of quality methods whose application leads to improved reliability of manufacturing in the process industry. Evaluation of failures and determination of their priorities are based on failure mode and effect analysis (FMEA), which is a widely used framework in practice combining with triangular intuitionistic fuzzy numbers (TIFNs). The all-existing uncertainties in the relative importance of the risk factors (RFs), their values, applicability of the quality methods, as well as implementation costs are described by pre-defined linguistic terms which are modeled by the TIFNs. The selection of quality methods is stated as the rubber knapsack problem which is decomposed into subproblems with a certain number of solution elements. The solution of this problem is found by using genetic algorithm (GA). The model is verified through the case study with the real-life data originating from a significant number of organizations from one region. It is shown that the proposed model is highly suitable as a decision-making tool for improving the manufacturing process reliability in small and medium enterprises (SMEs) of process industry. PB - MDPI, Basel T2 - Mathematics T1 - Evaluation and Selection of the Quality Methods for Manufacturing Process Reliability Improvement-Intuitionistic Fuzzy Sets and Genetic Algorithm Approach IS - 13 VL - 9 DO - 10.3390/math9131531 ER -
@article{ author = "Gojković, Ranka and Đurić, Goran and Tadić, Danijela and Nestić, Snežana and Aleksić, Aleksandar", year = "2021", abstract = "The aim of this research is to propose a hybrid decision-making model for evaluation and selection of quality methods whose application leads to improved reliability of manufacturing in the process industry. Evaluation of failures and determination of their priorities are based on failure mode and effect analysis (FMEA), which is a widely used framework in practice combining with triangular intuitionistic fuzzy numbers (TIFNs). The all-existing uncertainties in the relative importance of the risk factors (RFs), their values, applicability of the quality methods, as well as implementation costs are described by pre-defined linguistic terms which are modeled by the TIFNs. The selection of quality methods is stated as the rubber knapsack problem which is decomposed into subproblems with a certain number of solution elements. The solution of this problem is found by using genetic algorithm (GA). The model is verified through the case study with the real-life data originating from a significant number of organizations from one region. It is shown that the proposed model is highly suitable as a decision-making tool for improving the manufacturing process reliability in small and medium enterprises (SMEs) of process industry.", publisher = "MDPI, Basel", journal = "Mathematics", title = "Evaluation and Selection of the Quality Methods for Manufacturing Process Reliability Improvement-Intuitionistic Fuzzy Sets and Genetic Algorithm Approach", number = "13", volume = "9", doi = "10.3390/math9131531" }
Gojković, R., Đurić, G., Tadić, D., Nestić, S.,& Aleksić, A.. (2021). Evaluation and Selection of the Quality Methods for Manufacturing Process Reliability Improvement-Intuitionistic Fuzzy Sets and Genetic Algorithm Approach. in Mathematics MDPI, Basel., 9(13). https://doi.org/10.3390/math9131531
Gojković R, Đurić G, Tadić D, Nestić S, Aleksić A. Evaluation and Selection of the Quality Methods for Manufacturing Process Reliability Improvement-Intuitionistic Fuzzy Sets and Genetic Algorithm Approach. in Mathematics. 2021;9(13). doi:10.3390/math9131531 .
Gojković, Ranka, Đurić, Goran, Tadić, Danijela, Nestić, Snežana, Aleksić, Aleksandar, "Evaluation and Selection of the Quality Methods for Manufacturing Process Reliability Improvement-Intuitionistic Fuzzy Sets and Genetic Algorithm Approach" in Mathematics, 9, no. 13 (2021), https://doi.org/10.3390/math9131531 . .