TY  - JOUR
AU  - Vencl, Aleksandar
AU  - Stojanović, Blaža
AU  - Gojković, Ranka
AU  - Klančnik, Simon
AU  - Czifra, Árpád
AU  - Jakimovska, Kristina
AU  - Harničárová, Marta
PY  - 2022
UR  - https://www.tribomat.net/archive/2022/2022-03/TM-2022-03-02.pdf
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4286
AB  - The objective of this work was to investigate the influence of the addition of a small amount of SiC nanoparticles on the mechanical characteristics and wear resistance of ZA-27 alloy. The ZA-27 alloy-based nanocomposites were produced by a relatively cheap compocasting process preceded by mechanical alloying. Reinforcing elements were the silicon carbide (SiC) nanoparticles with an average size lower than 50 nm and in very small amounts of 0.2, 0.3 and 0.5 wt. %. Wear tests were realized on a block-on-disc tribometer under lubricated sliding conditions, at two sliding speeds (0.25 and 1 m/s), two normal loads (40 and 100 N) and a sliding distance of 1000 m. Optimisation of the SiC amount was performed by applying the Taguchi method, showing that the SiC amount of 0.5 wt. % is optimal for the given testing conditions. Prediction of the results and wear maps were also conducted. The analysis of variance showed that the SiC amount has the greatest influence on wear rate (70.8 %), followed by the normal load (19.8 %), and the sliding speed (3.9 %), while the influences of all interactions between these factors did not have any significant influence.
PB  - Balkan Scientific Centre
T2  - Tribology and Materials
T1  - Enhancing of ZA-27 alloy wear characteristics by addition of small amount of SiC nanoparticles and its optimisation applying Taguchi method
EP  - 105
IS  - 3
SP  - 96
VL  - 1
DO  - 10.46793/tribomat.2022.014
ER  - 

@article{
author = "Vencl, Aleksandar and Stojanović, Blaža and Gojković, Ranka and Klančnik, Simon and Czifra, Árpád and Jakimovska, Kristina and Harničárová, Marta",
year = "2022",
abstract = "The objective of this work was to investigate the influence of the addition of a small amount of SiC nanoparticles on the mechanical characteristics and wear resistance of ZA-27 alloy. The ZA-27 alloy-based nanocomposites were produced by a relatively cheap compocasting process preceded by mechanical alloying. Reinforcing elements were the silicon carbide (SiC) nanoparticles with an average size lower than 50 nm and in very small amounts of 0.2, 0.3 and 0.5 wt. %. Wear tests were realized on a block-on-disc tribometer under lubricated sliding conditions, at two sliding speeds (0.25 and 1 m/s), two normal loads (40 and 100 N) and a sliding distance of 1000 m. Optimisation of the SiC amount was performed by applying the Taguchi method, showing that the SiC amount of 0.5 wt. % is optimal for the given testing conditions. Prediction of the results and wear maps were also conducted. The analysis of variance showed that the SiC amount has the greatest influence on wear rate (70.8 %), followed by the normal load (19.8 %), and the sliding speed (3.9 %), while the influences of all interactions between these factors did not have any significant influence.",
publisher = "Balkan Scientific Centre",
journal = "Tribology and Materials",
title = "Enhancing of ZA-27 alloy wear characteristics by addition of small amount of SiC nanoparticles and its optimisation applying Taguchi method",
pages = "105-96",
number = "3",
volume = "1",
doi = "10.46793/tribomat.2022.014"
}

Vencl, A., Stojanović, B., Gojković, R., Klančnik, S., Czifra, Á., Jakimovska, K.,& Harničárová, M.. (2022). Enhancing of ZA-27 alloy wear characteristics by addition of small amount of SiC nanoparticles and its optimisation applying Taguchi method. in Tribology and Materials
Balkan Scientific Centre., 1(3), 96-105.
https://doi.org/10.46793/tribomat.2022.014

Vencl A, Stojanović B, Gojković R, Klančnik S, Czifra Á, Jakimovska K, Harničárová M. Enhancing of ZA-27 alloy wear characteristics by addition of small amount of SiC nanoparticles and its optimisation applying Taguchi method. in Tribology and Materials. 2022;1(3):96-105.
doi:10.46793/tribomat.2022.014 .

Vencl, Aleksandar, Stojanović, Blaža, Gojković, Ranka, Klančnik, Simon, Czifra, Árpád, Jakimovska, Kristina, Harničárová, Marta, "Enhancing of ZA-27 alloy wear characteristics by addition of small amount of SiC nanoparticles and its optimisation applying Taguchi method" in Tribology and Materials, 1, no. 3 (2022):96-105,
https://doi.org/10.46793/tribomat.2022.014 . .

TY  - 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 . .