Improving the efficiency of production processes in the manufacturing industry based on methods of multicriteria analysis and metacheuristics

Problem procjene i rangiranja grešaka koje mogu dovesti do Lean gubitaka imaju presudan uticaj na efektivnost i pouzdanost proizvodnog kao i ostalih poslovnih procesa preduzeća. U ovoj doktorskoj disertaciji su razvijena dva nova fazi višekriterijumska modela optimizacije zasnovan na Analizi mogućih grešaka i efekata grešaka (prema eng. Failure Mode and Effect Analysis - FMEA), odnosno FMEA okviru za rangiranje grešaka na nivou svakog Lean gubitka. Na samom početku izvršena je identifikacija i grafički prikaz grešaka korišćenjem Išikava dijagrama. Ocjena identifikovanih grešaka vrši se u odnosu na tri faktora rizika (RF) definisana u FMEA metodi. Nedostaci FMEA metode, koje su sugerisani od strane drugih autora, su prevaziđeni kombinacijom ove metode sa pravilima fazi logike i metodama višekriterijumskog odlučivanja (prema eng. Multi Criteria Decision Making - MCDM). U prvom modelu relativna važnost RF i njihove vrijednosti opisani su unaprijed definisanim lingvističkim iskazima koji su modelirani sa trapezoidnim intuitivnim fazi brojevima (prema eng. Trapezoidal intuitionistic fuzzy numbers - TrIFN). Za određivanje vektora težine RF koristi se Analitički hijerarhijski proces proširen sa TrIFN (prema eng. Fuzzy Analytic Hierarchy Process with TrIFN - IFAHP). Rang identifikovanih grešaka daje se upotrebom predložene metode Višekriterijumskog kompromisnog rangiranja proširene sa TrIFN (prema eng. VIKOR with TrIFN - IF-VIKOR). Na kraju, urađena je analiza osjetljivosti koja pokazuje stabilnost predloženog pristupa. U drugom modelu, procjena i rangiranje grešaka koji dovode do Lean gubitaka daju se korišćenjem fazi MCDM metoda proširenih sa intervalnim intuitivnim fazi brojevima (prema eng. Interval valued intuitionistic fuzzy numbers - IVIFN). Relativna važnost RF i njihove vrijednosti opisani su unaprijed definisanim lingvističkim iskazima koji su modelirani sa IVIFN. Modifikovana fazi logika sa pravilima za IVIFN koristi se za određivanje nivoa rizika proizvodnog procesa. U drugom dijelu disertacije, predložen je hibridni model odlučivanja za ocjenu i izbor metoda/tehnika kvaliteta čija primjena dovodi do unaprjeđenja efektivnosti i pouzdanosti proizvodnih procesa u malim i srednjim preduzećima (MSP) prerađivačke industrije. Ovaj model kombinuje FMEA sa trougaoni intuitivni fazi brojevima (prema eng. Triangular intuitionistic fuzzy numbers – TIFN). Sve postojeće neizvjesnosti, relativna važnost RF, njihove vrijednosti, primjenljivost metoda kvaliteta, kao i troškovi primjene opisani su unaprijed definisanim jezičkim iskazima koji su modelirani TIFN. Izbor metoda kvaliteta naveden je kao KP problem, odnosno problem rastegljivog ranca koji se razlaže na potprobleme sa određenim brojem elemenata rješenja. Rješenje ovog problema pronalazi se korišćenjem genetskog algoritma (prema eng. Genetic algorithm - GA) (Gojković et al., 2021). Model je verifikovan kroz studiju slučaja sa podacima iz stvarnog života koji potiču od značajnog broja organizacija iz jednog regiona, čime je pokazan potencijal i primjenljivost razvijenih modela. Pokazano je da su predloženi modeli izuzetno pogodan kao alati za donošenje odluka za poboljšanje efektivnosti i pouzdanosti proizvodnog procesa u MSP prerađivačke industrije.The problem of evaluation and ranking failures that can lead to Lean waste has a critical effect on the safety and reliability of the manufacturing process, and other business processes of enterprises. In this doctoral dissertation, two new fuzzy multicriteria optimization models based on Failure Mode and Effect Analysis - FMEA have been developed to rank failures at the level of each Lean waste. At the beginning, failures were identified using the Ishikawa diagram. The evaluation of the identified failures is performed in relation to the three risk factors (RF) defined in the FMEA method. The disadvantages of the FMEA method, which have been suggested by other authors, have been overcome by combining this method with the fuzzy logic rols and the Multi Criteria Decision Making (MCDM). In the first model, the relative importance of RF and their values are described by predefined linguistic statements modeled with trapezoidal intuitionistic fuzzy numbers (TrIFN). The Fuzzy Analytic Hierarchy Process with TrIFN (IF-AHP) was used to determine the RF weight vector. The rank of identified failures is given using the proposed VIKOR with TrIFN (IF-VIKOR). Finally, a sensitivity analysis was performed showing the stability of the proposed approach. In the second model, estimation and ranking of failures leading to Lean waste are given using the fuzzy MCDM with interval valued intuitionistic fuzzy numbers (IVIFN). The relative importance of RF and their values are described by predefined linguistic statements modeled with IVIFN. A modified fuzzy logic ruls with IVIFN rules is used to determine the level of risk of the production process. In the second part of the dissertation, a hybrid decision-making model for evaluation and selection of quality methods/techniques is proposed, the application of which leads to the improvement of efficiency and reliability of production processes in small and medium enterprises (SMEs) of the manufacturing industry. This model combines FMEA with the triangular intuitionistic fuzzy numbers (TIFN). All existing uncertainties, the relative importance of RF, their values, the applicability of quality methods/techniques, as well as the costs of application are described by pre-defined linguistic statements modeled by TIFN. The choice of quality methods/techniques is stated as a KP problem. It is a Rubber Knapsack problem that decomposes into subproblems with a certain number of solution elements. The solution to this problem is found using a genetic algorithm (GA) (Gojković et al., 2021). The model was verified through a case study with real life data originating from a significant number of organizations from one region, showing the potential and applicability of the developed models. He showed that the proposed models are extremely suitable as decision-making tools for improving the efficiency and reliability of the production process in the SME manufacturing industry

Evaluation and Selection of the Quality Methods for Manufacturing Process Reliability Improvement-Intuitionistic Fuzzy Sets and Genetic Algorithm Approach

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

Evaluation and Selection of the Quality Methods for Manufacturing Process Reliability Improvement-Intuitionistic Fuzzy Sets and Genetic Algorithm Approach

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

Enhancing of ZA-27 alloy wear characteristics by addition of small amount of SiC nanoparticles and its optimisation applying Taguchi method

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

PRACTICES IN ENTREPRENEURSHIP EDUCATION IN SOUTH EAST EUROPE AND RUSSIA

The REBUS project emerged in countries where the younger generations are reluctant to engage in private business and entrepreneurship, preferring "safe" employment at the public (state owned) enterprises. Their awareness of own entrepreneurship potentials is very low, while the capacity of talented and skilled students often stays unutilized once being employed. Thus the REBUS project supports embedding entrepreneurship to the South East Europe and Russian universities, at the same time creating network for cooperation between EU and partner countries. One of the first activities was identification, analysis and description of common practices in entrepreneurship education. For this purpose, a comprehensive desk research was combined with expert interviews to inquire about approaches of learning and teaching, connections to lessons, courses and extracurricular activities and approaches to validate entrepreneurial competences. The stocktaking related to the knowledge and differentiation on entrepreneurial competences, leading questions of the surveys related to gaps between formalised (HE) and informal (personal oriented, e.g. in internships) learning and assessment, potentials for enhancements of acquisition of those competences, validation of entrepreneurial competences and selection of key sub-competences. This paper presents results of research and needs analysis (stocktaking) and project objectives and first results

Evaluation and Selection of the Quality Methods for Manufacturing Process Reliability Improvement—Intuitionistic Fuzzy Sets and Genetic Algorithm Approach

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

Improving the efficiency of production processes in the manufacturing industry based on methods of multicriteria analysis and metacheuristics

Problem procjene i rangiranja grešaka koje mogu dovesti do Lean gubitaka imaju presudan uticaj na efektivnost i pouzdanost proizvodnog kao i ostalih poslovnih procesa preduzeća. U ovoj doktorskoj disertaciji su razvijena dva nova fazi višekriterijumska modela optimizacije zasnovan na Analizi mogućih grešaka i efekata grešaka (prema eng. Failure Mode and Effect Analysis - FMEA), odnosno FMEA okviru za rangiranje grešaka na nivou svakog Lean gubitka. Na samom početku izvršena je identifikacija i grafički prikaz grešaka korišćenjem Išikava dijagrama. Ocjena identifikovanih grešaka vrši se u odnosu na tri faktora rizika (RF) definisana u FMEA metodi. Nedostaci FMEA metode, koje su sugerisani od strane drugih autora, su prevaziđeni kombinacijom ove metode sa pravilima fazi logike i metodama višekriterijumskog odlučivanja (prema eng. Multi Criteria Decision Making - MCDM). U prvom modelu relativna važnost RF i njihove vrijednosti opisani su unaprijed definisanim lingvističkim iskazima koji su modelirani sa trapezoidnim intuitivnim fazi brojevima (prema eng. Trapezoidal intuitionistic fuzzy numbers - TrIFN). Za određivanje vektora težine RF koristi se Analitički hijerarhijski proces proširen sa TrIFN (prema eng. Fuzzy Analytic Hierarchy Process with TrIFN - IFAHP). Rang identifikovanih grešaka daje se upotrebom predložene metode Višekriterijumskog kompromisnog rangiranja proširene sa TrIFN (prema eng. VIKOR with TrIFN - IF-VIKOR). Na kraju, urađena je analiza osjetljivosti koja pokazuje stabilnost predloženog pristupa. U drugom modelu, procjena i rangiranje grešaka koji dovode do Lean gubitaka daju se korišćenjem fazi MCDM metoda proširenih sa intervalnim intuitivnim fazi brojevima (prema eng. Interval valued intuitionistic fuzzy numbers - IVIFN). Relativna važnost RF i njihove vrijednosti opisani su unaprijed definisanim lingvističkim iskazima koji su modelirani sa IVIFN. Modifikovana fazi logika sa pravilima za IVIFN koristi se za određivanje nivoa rizika proizvodnog procesa. U drugom dijelu disertacije, predložen je hibridni model odlučivanja za ocjenu i izbor metoda/tehnika kvaliteta čija primjena dovodi do unaprjeđenja efektivnosti i pouzdanosti proizvodnih procesa u malim i srednjim preduzećima (MSP) prerađivačke industrije. Ovaj model kombinuje FMEA sa trougaoni intuitivni fazi brojevima (prema eng. Triangular intuitionistic fuzzy numbers – TIFN). Sve postojeće neizvjesnosti, relativna važnost RF, njihove vrijednosti, primjenljivost metoda kvaliteta, kao i troškovi primjene opisani su unaprijed definisanim jezičkim iskazima koji su modelirani TIFN. Izbor metoda kvaliteta naveden je kao KP problem, odnosno problem rastegljivog ranca koji se razlaže na potprobleme sa određenim brojem elemenata rješenja. Rješenje ovog problema pronalazi se korišćenjem genetskog algoritma (prema eng. Genetic algorithm - GA) (Gojković et al., 2021). Model je verifikovan kroz studiju slučaja sa podacima iz stvarnog života koji potiču od značajnog broja organizacija iz jednog regiona, čime je pokazan potencijal i primjenljivost razvijenih modela. Pokazano je da su predloženi modeli izuzetno pogodan kao alati za donošenje odluka za poboljšanje efektivnosti i pouzdanosti proizvodnog procesa u MSP prerađivačke industrije.The problem of evaluation and ranking failures that can lead to Lean waste has a critical effect on the safety and reliability of the manufacturing process, and other business processes of enterprises. In this doctoral dissertation, two new fuzzy multicriteria optimization models based on Failure Mode and Effect Analysis - FMEA have been developed to rank failures at the level of each Lean waste. At the beginning, failures were identified using the Ishikawa diagram. The evaluation of the identified failures is performed in relation to the three risk factors (RF) defined in the FMEA method. The disadvantages of the FMEA method, which have been suggested by other authors, have been overcome by combining this method with the fuzzy logic rols and the Multi Criteria Decision Making (MCDM). In the first model, the relative importance of RF and their values are described by predefined linguistic statements modeled with trapezoidal intuitionistic fuzzy numbers (TrIFN). The Fuzzy Analytic Hierarchy Process with TrIFN (IF-AHP) was used to determine the RF weight vector. The rank of identified failures is given using the proposed VIKOR with TrIFN (IF-VIKOR). Finally, a sensitivity analysis was performed showing the stability of the proposed approach. In the second model, estimation and ranking of failures leading to Lean waste are given using the fuzzy MCDM with interval valued intuitionistic fuzzy numbers (IVIFN). The relative importance of RF and their values are described by predefined linguistic statements modeled with IVIFN. A modified fuzzy logic ruls with IVIFN rules is used to determine the level of risk of the production process. In the second part of the dissertation, a hybrid decision-making model for evaluation and selection of quality methods/techniques is proposed, the application of which leads to the improvement of efficiency and reliability of production processes in small and medium enterprises (SMEs) of the manufacturing industry. This model combines FMEA with the triangular intuitionistic fuzzy numbers (TIFN). All existing uncertainties, the relative importance of RF, their values, the applicability of quality methods/techniques, as well as the costs of application are described by pre-defined linguistic statements modeled by TIFN. The choice of quality methods/techniques is stated as a KP problem. It is a Rubber Knapsack problem that decomposes into subproblems with a certain number of solution elements. The solution to this problem is found using a genetic algorithm (GA) (Gojković et al., 2021). The model was verified through a case study with real life data originating from a significant number of organizations from one region, showing the potential and applicability of the developed models. He showed that the proposed models are extremely suitable as decision-making tools for improving the efficiency and reliability of the production process in the SME manufacturing industry

Improving the efficiency of production processes in the manufacturing industry based on methods of multicriteria analysis and metacheuristics

Problem procjene i rangiranja grešaka koje mogu dovesti do Lean gubitaka imaju presudan uticaj na efektivnost i pouzdanost proizvodnog kao i ostalih poslovnih procesa preduzeća. U ovoj doktorskoj disertaciji su razvijena dva nova fazi višekriterijumska modela optimizacije zasnovan na Analizi mogućih grešaka i efekata grešaka (prema eng. Failure Mode and Effect Analysis - FMEA), odnosno FMEA okviru za rangiranje grešaka na nivou svakog Lean gubitka. Na samom početku izvršena je identifikacija i grafički prikaz grešaka korišćenjem Išikava dijagrama. Ocjena identifikovanih grešaka vrši se u odnosu na tri faktora rizika (RF) definisana u FMEA metodi. Nedostaci FMEA metode, koje su sugerisani od strane drugih autora, su prevaziđeni kombinacijom ove metode sa pravilima fazi logike i metodama višekriterijumskog odlučivanja (prema eng. Multi Criteria Decision Making - MCDM). U prvom modelu relativna važnost RF i njihove vrijednosti opisani su unaprijed definisanim lingvističkim iskazima koji su modelirani sa trapezoidnim intuitivnim fazi brojevima (prema eng. Trapezoidal intuitionistic fuzzy numbers - TrIFN). Za određivanje vektora težine RF koristi se Analitički hijerarhijski proces proširen sa TrIFN (prema eng. Fuzzy Analytic Hierarchy Process with TrIFN - IFAHP). Rang identifikovanih grešaka daje se upotrebom predložene metode Višekriterijumskog kompromisnog rangiranja proširene sa TrIFN (prema eng. VIKOR with TrIFN - IF-VIKOR). Na kraju, urađena je analiza osjetljivosti koja pokazuje stabilnost predloženog pristupa. U drugom modelu, procjena i rangiranje grešaka koji dovode do Lean gubitaka daju se korišćenjem fazi MCDM metoda proširenih sa intervalnim intuitivnim fazi brojevima (prema eng. Interval valued intuitionistic fuzzy numbers - IVIFN). Relativna važnost RF i njihove vrijednosti opisani su unaprijed definisanim lingvističkim iskazima koji su modelirani sa IVIFN. Modifikovana fazi logika sa pravilima za IVIFN koristi se za određivanje nivoa rizika proizvodnog procesa. U drugom dijelu disertacije, predložen je hibridni model odlučivanja za ocjenu i izbor metoda/tehnika kvaliteta čija primjena dovodi do unaprjeđenja efektivnosti i pouzdanosti proizvodnih procesa u malim i srednjim preduzećima (MSP) prerađivačke industrije. Ovaj model kombinuje FMEA sa trougaoni intuitivni fazi brojevima (prema eng. Triangular intuitionistic fuzzy numbers – TIFN). Sve postojeće neizvjesnosti, relativna važnost RF, njihove vrijednosti, primjenljivost metoda kvaliteta, kao i troškovi primjene opisani su unaprijed definisanim jezičkim iskazima koji su modelirani TIFN. Izbor metoda kvaliteta naveden je kao KP problem, odnosno problem rastegljivog ranca koji se razlaže na potprobleme sa određenim brojem elemenata rješenja. Rješenje ovog problema pronalazi se korišćenjem genetskog algoritma (prema eng. Genetic algorithm - GA) (Gojković et al., 2021). Model je verifikovan kroz studiju slučaja sa podacima iz stvarnog života koji potiču od značajnog broja organizacija iz jednog regiona, čime je pokazan potencijal i primjenljivost razvijenih modela. Pokazano je da su predloženi modeli izuzetno pogodan kao alati za donošenje odluka za poboljšanje efektivnosti i pouzdanosti proizvodnog procesa u MSP prerađivačke industrije.The problem of evaluation and ranking failures that can lead to Lean waste has a critical effect on the safety and reliability of the manufacturing process, and other business processes of enterprises. In this doctoral dissertation, two new fuzzy multicriteria optimization models based on Failure Mode and Effect Analysis - FMEA have been developed to rank failures at the level of each Lean waste. At the beginning, failures were identified using the Ishikawa diagram. The evaluation of the identified failures is performed in relation to the three risk factors (RF) defined in the FMEA method. The disadvantages of the FMEA method, which have been suggested by other authors, have been overcome by combining this method with the fuzzy logic rols and the Multi Criteria Decision Making (MCDM). In the first model, the relative importance of RF and their values are described by predefined linguistic statements modeled with trapezoidal intuitionistic fuzzy numbers (TrIFN). The Fuzzy Analytic Hierarchy Process with TrIFN (IF-AHP) was used to determine the RF weight vector. The rank of identified failures is given using the proposed VIKOR with TrIFN (IF-VIKOR). Finally, a sensitivity analysis was performed showing the stability of the proposed approach. In the second model, estimation and ranking of failures leading to Lean waste are given using the fuzzy MCDM with interval valued intuitionistic fuzzy numbers (IVIFN). The relative importance of RF and their values are described by predefined linguistic statements modeled with IVIFN. A modified fuzzy logic ruls with IVIFN rules is used to determine the level of risk of the production process. In the second part of the dissertation, a hybrid decision-making model for evaluation and selection of quality methods/techniques is proposed, the application of which leads to the improvement of efficiency and reliability of production processes in small and medium enterprises (SMEs) of the manufacturing industry. This model combines FMEA with the triangular intuitionistic fuzzy numbers (TIFN). All existing uncertainties, the relative importance of RF, their values, the applicability of quality methods/techniques, as well as the costs of application are described by pre-defined linguistic statements modeled by TIFN. The choice of quality methods/techniques is stated as a KP problem. It is a Rubber Knapsack problem that decomposes into subproblems with a certain number of solution elements. The solution to this problem is found using a genetic algorithm (GA) (Gojković et al., 2021). The model was verified through a case study with real life data originating from a significant number of organizations from one region, showing the potential and applicability of the developed models. He showed that the proposed models are extremely suitable as decision-making tools for improving the efficiency and reliability of the production process in the SME manufacturing industry

The Role of Investment Funds in Countries with Transition Economies

Investment funds, their foundation and development in Serbia, as a country with transition economy, should be viewed in the context of overall economic reforms, which are necessary for these kind of countries, to enable them to emerge from decades of stagnation and poverty, and create conditions for establishing an open market economy. Only within financial reforms, investment companies provide a significant contribution in the improvement of the national economies of the countries in transition. Through knowledge of their managers and scope of resources they possess, they have greater opportunities than individuals - from quality and professional market analysis, to the dispersion of risk by investing in various securities. This paper presents the impact of investment funds as institutional investors on financial market development, as well as their role in the privatization process and points out the problems and possibilities of development of investment funds in the countries in transition