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Corporate and organizational performance assessment is an important activity for both the managers and other stakeholders, as it provides them with an asset to evaluate their own strengths and weaknesses in relation to the competition, as well as guidelines for selecting appropriate measures to address the existing problems. The issue of criteria selection has been overcome through the literature review and the issue of criteria weights is handled by applying group decision making procedure. The procedure itself consists of using predefined linguistic expressions that are modelled by triangular fuzzy numbers and the aggregation of decision makers’ opinion based on the rules of rough sets algebra. The values of the decision matrix are determined by prognosis method and they are described by crisp values. The proposed algorithm is tested on the insurance companies that operate in the Republic of Serbia

The ongoing research in the field of decision-making can be analyzed from different perspectives. Research trends indicate that multi-attribute decision-making (MADM) methods have a significant impact on engineering and management scientific areas. Since many of the problems existing in the mentioned areas are associated with a certain level of uncertainty, type 2 fuzzy sets represent a common solution for the enhancement of conventional MADM methods. In this way, the decision-makers are encouraged to use linguistic expressions for the assessment of attributes’ relative importance and their values. The purpose of this paper is to review a determination of attributes’ relative importance, and their values, as well as the extension of ranking methods with type 2 fuzzy sets. The papers are systematically adjoined to groups consisting of hybrid models with the following characteristics: (1) indicating the procedure for modeling attribute relative importance and their values, (2) determining the extension of MADM methods with type 2 fuzzy sets to determine attributes’ vector weights, and (3) the extension of MADM for attributes ranking with type 2 fuzzy sets. This study reviewed a total of 42 papers in the domain of engineering and management published from 2013 to 2023 in different journals indexed by the Springer, Science Direct, Emerald, Wiley, ProQuest, Taylor, and Francis research platforms.

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.

The main objective of this paper is the analysis of the impact of recycling equipment in the automotive industry in terms of circular economy (CE). Also, paper point out the opportunities and benefits of applications equipment for recycling and principles of CE in the automotive industry in Serbia. Analysis of market needs and examining the existing equipment for recycling team who work on the project TR 35033 made: mobile baling press for baling shellfish and other scrap metal, a device for dispensing oil and automatic shredder for recycling cables. Application of the circular economy in the automotive industry is reflected in the remanufacturing a wide variety of components and parts (engines, water pumps, alternators etc.). The main benefits of applications equipment for recycling and CE in the automotive industry include: maximizing the utilization of resources and increasing the reuse of materials from products that have completed their "life cycle", maximizing the life of the product, reduce environmental pollution, reducing costs etc.

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.

Project-oriented manufacturing companies aim to produce high-quality products according to customer requirements and a minimum rate of complaints. In order to achieve this, performance indicators, especially those related to product quality, must be measured and monitored by managers. This research proposes a fuzzy multi-criteria model for the selection of key performance indicators that are critical to product quality. The uncertainties in the relative importance of decision-makers, performance indicators, and their values are described by sets of natural language words that are modeled by the interval-valued intuitionistic fuzzy numbers. The assessment of the relative importance of the decision-makers and the determination of their weights are based on the inclusion comparison probability between the closeness intuitionistic fuzzy sets. The determination of the weights vector of performance indicators is based on the integration of an interval-value fuzzy weighted geometric operator and the inclusion comparison probability between the closeness intuitionistic fuzzy sets. TOPSIS expanded with interval-valued intuitionistic fuzzy numbers for ranking performance indicators is proposed. The developed model was tested on the real data collected from three manufacturing companies in the Republic of Serbia. Based on the obtained results, the top-ranked performance indicators were marked as critical for product quality and selected as quality key performance indicators.

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.

This paper develops multirelational data base for major depression costs. It lists how data are collected and stored into the fact base and dimension base. Uncertain data is described linguistically and modelled by fuzzy sets. Linguistic expressions are stored in dimension base. Models of major depression treatment costs are developed for each patient and all population. On the basis of this model and multirelational data base MD-OLAP a model for major depression treatment costs is developed.

In this paper, a new method for ELV dismantling selection is proposed which has purpose to determine the sequence of dismantling of ELV which arrive to dismantling center. Its solution is of the most importance for ELV waste management problem, as it influences the choice and efficiency of ELV waste management strategies in dismantling centers. It is realistically posed that the choice of locations depends on multiple, rather conflicting criteria. The criteria values can be either crisp or uncertain. The main contribution of this paper is the development of methodology for determining the dismantling order of coming ELV and/ or ELV which are already in the dismantling centers. The uncertain criteria values are described by linguistic expressions modeled by triangular fuzzy numbers. The extension of the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied to rank the ELV which are in the dismantling center.

In this paper, short retrospection of the multi criteria mathematical models and fuzzy expert systems from available literature for support of the decision processes in medical treatment is presented. The significance of the application of methods and techniques of artificial intelligence, primarily the theory of fuzzy sets in modeling of clinical uncertainties and ranking of the possible solutions is demonstrated. Special attention is focused to possibility of the application of medical expert systems in the process of determination and monitoring of the optimal therapy procedure for individuals. Summary of the possibilities for application of the medical expert systems in the republic of Serbia is presented.

This article presents new model of enterprises resource planning implementation planning process in manufacturing enterprises based on assessment of risk sources. This assessment was performed by applying analytic hierarchy process. Analytic hierarchy process method allows variation of relative importance of specific risk sources dependent on the section from which the risk source originates (organizational environment, technical issues, people issues, adoption process management, and external support). Survey was conducted on 85 manufacturing enterprises involved with an enterprises resource planning solution. Ranking of risk sources assessments returns most frequent risks of enterprises resource planning implementation success in manufacturing enterprises, and representative factors were isolated through factor analysis by risk source origin. Finally, results indicate that there are hidden causes of failed implementation, for example, risk source “top management training and education,” from risk origin “adoption process management.”

HACCP (Hazard Analysis Critical Control Points) is a scientifically based set of principles that is designed to prevent food borne illness. This dynamic system uses a combination of food handling procedures, monitoring and record keeping to have food safe. HACCP is based around seven established principles. This paper proposes fuzzy approach in establishing critical limits in process of ensuring food safety.