Nikola Komatina
@fin.kg.ac.rs
Faculty of Engineering
University of Kragujevac
EDUCATION
PhD in Industrial Engineering and Engineering Management
RESEARCH, TEACHING, or OTHER INTERESTS
Industrial and Manufacturing Engineering, Safety, Risk, Reliability and Quality, Management Science and Operations Research, Statistics, Probability and Uncertainty
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Ana Marković, Blaža Stojanović, Nikola Komatina, and Lozica Ivanović
SAGE Publications
Automotive industry is characterized by mass production, a large share in the gross national income and high employment of workers with different knowledge and skills. Improving the production process, as well as product quality, is one of the most important tasks of automotive enterprise as well as government management. This research promotes a new fuzzy hybrid model for determining the priority of polymeric materials for manufacturing gears in an exact manner, which leads to an incremental improvement in the quality of the considered product. The analysis of polymeric materials and their characteristic is based on data from the relevant literature and experiences of the best practice. The relative importance of material characteristics is stated as fuzzy group decision making problem. The weights vector is determined by using the fuzzy Analytic Hierarchical Process and fuzzy geometric mean. The rank of polymeric materials is obtained by employing the proposed Technique for Order Preference by Similarity to Ideal Solution with triangular fuzzy numbers. The fuzzy algebra rules have been used for determining: (i) distances from Fuzzy Positive Ideal Solutions and Fuzzy Negative Ideal Solutions and (ii) closeness coefficient values. The proposed fuzzy hybrid model testing and verification are performed on real data in an automotive enterprise.
Nikola Komatina, Danijela Tadić, Aleksandar Aleksić, and Aleksandar D Jovanović
SAGE Publications
The selection of appropriate suppliers in an uncertain environment influences the sustainability and the competitive advantage of the automotive industry and hence presents one of the significant management problems. In the literature, it is suggested that an acceptable supplier may be determined concerning many criteria. In this manuscript, criteria selection is based on the relevant literature. Handling of different uncertainties is performed by using the type-2 fuzzy sets that have the capability of handling more considered impreciseness and uncertainties. In the presented research, the two-state model is proposed. In the first stage, the relative importance of criteria and sub-criteria are described by pre-defined linguistic expressions which are modeled by the interval type-2 triangular fuzzy numbers (IT2TFNs). The fuzzy weights vectors are given by using the fuzzy Analytic Hierarchical Process with IT2TFNs (IT2FAHP). After that, the ranking of suppliers is based on the modified Multi-Attributive Border Approximation area Comparison method (MABAC) with IT2TFNs (IT2FMABAC). The extension of the conventional MABAC includes: (a) modeling of sub-criteria values of IT2TFNs, (b) the fuzzy criteria values are calculated by using fuzzy algebra rules, (c) belonging of each supplier to border approximation areas (BAAs) is given by using procedure, and (d) the distance of suppliers to BAAs is determined by using the normalized Euclidean distance formulas. The proposed model is tested on the real-life data from the automotive supply chain. Through the presented research, it is shown that the proposed IT2FMABAC is a useful and reliable tool for the rational purchasing decision-making process.
Michael Huber, Nikola Komatina, Vladan Paunović, and Snežana Nestić
MDPI AG
In terms of uncertain business conditions, the ability of an enterprise to bounce back after severe disruptions, or simply resilience, may be seen as one of the major features needed to sustain successful business operations. This research has the objective of proposing an algorithm for the organizational resilience assessment in industrial companies and conducting an analysis of the relationship between the organizational Resilience Factors and Key Performance Indicators recovery times. As the variables that are an integral part of the research are exposed to a high degree of uncertainty, they are modeled using fuzzy set theory. The methodology used for the research is an enhanced fuzzy Delphi, where the fuzzy geometric mean is employed as an aggregation operator. The relationship between the organizational resilience factors and Key Performance Indicators’ recovery time is based on the correlation analysis. The proposed model is based on real data from one complex industrial enterprise. The main finding of the research is that calculations indicate a significant negative correlation between treated variables.
Aleksandar Aleksić, Dragan D. Milanović, Nikola Komatina, and Danijela Tadić
Wiley
AbstractOne of the important and persistent problems that engineers face in the automotive industry is the reliability of production equipment. This research promotes a new fuzzy multicriteria model for determining the priority of failures in an exact manner. In this way, the decision makers can determine the management activities whose application should result in enhanced manufacturing process reliability, promptly. The analysis of failures is based on Failure mode and effects analysis that is extended with added risk factors, which represents the incremental improvement compared to the current literature sources. The relative importance of risk factors and their values are presented by pre‐defined linguistic expressions modelled by the interval type‐2 fuzzy numbers. The assessment of risk factors' relative importance is set as a fuzzy group decision‐making problem. The weights vector is determined by using the extended Best‐Worst Method. The rank of failures is obtained by employing the modified VIseKriterijumska Optimizacija i kompromisno Resenje (Eng. Multi‐criteria optimization and compromise solution) which reflects the scientific contribution of the research, and simultaneously, the second incremental improvement of the proposed model compared to the existing state of the art. These incremental improvements are: (i) The fuzzy algebra rules have been used for determining the group utility value and (ii) and individual regret value is determined by comparing the two interval type‐2 fuzzy numbers. The model testing and verification are performed on real data in an automotive supply chain.
Nikola Komatina, Danijela Tadić, Goran Đurić, and Aleksandar Aleksić
SAGE Publications
The aim of this research is to propose the two-stage model to select a set of failures that need to be eliminated or reduced which leads to improved reliability and effectiveness of the manufacturing process in the automotive industry. In the first stage, uncertainties under the relative importance of risk factors and costs of manufacturing process downtime due to failure are modeled by type 2 fuzzy sets. The weights vector of risk factors is obtained by analytical hierarchical Process which is extended with type 2 fuzzy sets. Evaluation of risk factors at the level of each identified failure is based on failure mode and effect analysis which is widely used in practice. Determining the set of failures to be eliminated is set as a knapsack problem. The linear fitness function is defined as the ratio of the overall risk priority index and total costs. Maintenance costs incurred due to the realization of failure are limited by the available budget and in this knapsack problem are presented by a linear inequality. The solution to this problem is found by using the Genetic Algorithm and Variable Neighborhood Search. The model is verified with real-life data originating from automotive companies that exist in Serbia. Authors have managed to obtain suitable results on different knapsack problem instances. It is shown that the enhancement of the manufacturing process can be based on the proposed model.
Tijana Petrović, Jasmina Vesić Vasović, Nikola Komatina, Danijela Tadić, Đuro Klipa, and Goran Đurić
MDPI AG
In recent decades, many researchers and practitioners have believed that reaching a high level of business excellence leads to the continuous realization of a set of business goals. In the literature, a vast number of models for business excellence evaluation that contain different criteria depending on the cultural, technological, organizational, and socio-economic factors can be found. The aims of the proposed fuzzy two-stage model are to address some of the main shortcomings of the EFQM2020 model and to adapt it to the needs of process manufacturing. The relative importance of quality criteria and their values are presented by pre-defined linguistic expressions modeled by the triangular fuzzy numbers. The determination of the weight vector of criteria is stated as a fuzzy group decision-making problem and determined by using the fuzzy best-worst method. The proposed fuzzy multi-objective optimization by ratio analysis is implemented for determining the rank of enterprises. The management initiatives that should lead to the improvement of business excellence should be based on the business practices of enterprises that are highly placed in the rank. Testing and verification of the proposed model are performed on real data originating from enterprises operating in the same economic sector.
Nikola Komatina, Danijela Tadić, Aleksandar Aleksić, and Nikola Banduka
SAGE Publications
The change of market’s demand could be predictable to a certain degree at stable conditions but it may vary due to disruptive events. This research contributes by establishing the improvement of PFMEA (Process Failure Mode and Effect Analysis) analysis in the domain of assessment and determining severity risk factor, as well as identifying of failure priority. According to the researchers’ and practitioners’ suggestions, severity needs to be considered from the multiple aspects. The risk factor severity is considered from the aspects of product importance, quality, and cost. These aspects have different relative importance, which is determined in an exact way. The relative importance of the aspects, as well as the values of the risk factors, was described by linguistic expressions that are modeled by using the Interval type-2 trapezoidal fuzzy numbers (IT2TrFNs). IT2FBWM was used to determine weight vectors of risk factors. The priority of failures is determined according to the Action priority model which proposed by AIAG & VDA (Automotive Industry Action Group and German Association of the Automotive Industry). The proposed methodology is tested in a Case study where the real-life data originated from a company from the Republic of Serbia that operates as a part of an automotive supply chain.
Nikola Komatina, Marko Djapan, Igor Ristić, and Aleksandar Aleksić
MDPI AG
Sustainable development and project stakeholder management indicate a business practice where an organization strives to fulfil the demands of the important stakeholders for the project’s success. If one company relies on subassembly parts from its supplier, then it might be considered that it has high interest for enhancing the business continuity of the supplier. This issue has become more complex during 2020 due to turbulent business conditions where the problem of the safety and health of workers during daily work has become one of main reasons for business vulnerability. Besides the above-mentioned, project stakeholders may have different demands. The implementation of the management actions that lead to the fulfilment of stakeholder demands (SDs), such as addressing ongoing issues, are almost always limited by the available budget. The contribution of this research is providing the input for determining the actions which should address the most important SDs. Those activities may be seen as part of the strategy for external stakeholder management and successful long-term relationship. The determination of the priorities of SDs is based on a fuzzy multicriteria optimization model with type-2 fuzzy sets.
Nikola Banduka, Aleksandar Aleksić, Nikola Komatina, Amanda Aljinović, and Danijela Tadić
SAGE Publications
Traditionally, in the automotive industry, the risk posed by failures in manufacturing is based on the conventional process failure mode and effect analysis. The market changes, as well as limited financial resources dedicated to business improvement, induce the need for employment of advanced management tools. The rating of failures is derived from the research using the suggested fuzzy classification method based on the Pareto analysis. It is assumed that the classification criterion should be determined as the product of the overall product choice and the risk priority numbers given by applying the traditional process failure mode and effect analysis. All the uncertainties that exist in the problem under consideration are represented by linguistic expressions that are modeled on the interval type-2 triangular fuzzy numbers. The overall product choice is based on a fuzzy analytical hierarchy process with interval type-2 triangular fuzzy numbers. The execution of management initiatives based on the priority of failures can result in the improvement of the manufacturing process and overall business efficiency. The proposed model is tested using real-life data from a single vehicle manufacturer operating in the Western Balkans and representing a part of a global automotive supply chain.
Marija Milanovic, Mirjana Misita, and Nikola Komatina
IOS Press
, Nikola Komatina, Snežana Nestić, , Aleksandar Aleksić, and
Faculty of Technical Sciences
The customer needs shape business activities continuously so the need for improving effectiveness stands as mandatory for overall business success. This paper analyses existing models for measuring the business processes performance from the aspect of their applicability to the procurement process. The paper first explains the concepts of enterprise performance, business process performance, and key performance indicators. Subsequently, a literature review of the identification problem of procurement process performance and key performance indicators is given. The models discussed and explained in this paper are Balanced Scorecard, SCOR model, performance measurement matrix, ABC model, and DOE/NV model. The model comparison was based on several relevant criteria.
Marija Savković, Aleksandar Aleksić, Danijela Tadić, Nikola Komatina, and Tijana Cvetić
Faculty of Engineering, University of Kragujevac
Nikola Komatina, Aleksandar Aleksić, and Danijela Tadić
Faculty of Engineering, University of Kragujevac
This paper explains the importance of ELV recycling in the Republic of Serbia as well as the influence of the circular economy on the automotive industry. The advantages and significance of recycling of motor vehicles at the end of the life cycle, as well as the justification for the reuse of resources and the preservation of the environment, have been presented. Also, the paper presents the development of ELV recycling equipment and its importance for the entire state industry and economy.
Goran Ðurić, Časlav Mitrović, Nikola Komatina, Danijela Tadić, and Goran Vorotović
IOS Press
A. Aleksic, M. Runic Ristic, N. Komatina, and D. Tadic
Production Engineering Institute (PEI), Faculty of Mechanical Engineering
Management of a reverse supply chain (RSC) often takes place in an uncertain environment, so it is supposed to be analyzed through the proactive approach for avoidance/elimination of risks. Management initiatives based on the as‐ sessed risk level and priority of potential failure mode (PFM) should lead to the increase of business effectiveness, the competitive advantage and sustain‐ ability of the RSC. Therefore, the focus of this research is set to proposing the reliable method that would be user‐friendly and suitable for the determina‐ tion of risk level and priority of PFMs in RSC. Uncertainties related to the severities of Potential Effect(s) of Failure (PEF) and their frequencies’, as well as detection of PFMs are described by pre‐defined linguistic expressions and modelled by the interval type‐2 trapezoidal fuzzy numbers (IT2TrFNs). The assessment of the relative importance of risk factors is set as a fuzzy group decision‐making. The weights vector is calculated based on the procedure of fuzzy number comparison. The value of each risk factor at the level of each PFM is assessed through the predefined linguistic expressions modelled by IT2TrFNs. The rank is obtained by modified Technique for Order of Prefer‐ ence by Similarity to Ideal Solution (TOPSIS) method. The proposed model is tested on a real‐life data from RSC that operates in Serbia. In the domain of practical implications, it may be noticed that the application of the proposed model could decrease the influence of potential causes of failures modes on the overall RSC business activities especially in the terms of strategic man‐ agement and human resource practices. The novelty of the proposed model may be underlined as it is used for the analysis of different RSC activities and many interconnected issues may be solved by the proposed management measures after conducted analysis. © 2019 CPE, University of Maribor. All rights reserved.