MATLAB Fuzzy Research Articles

Testing and analysis of a D-STATCOM prototype connected to the electrical network

In this article Flexible AC Transmission Systems (FACTS) devices are addressed, especially the design and implementation of a D-STATCOM prototype, making a comparison between the theoretical behavior and the aforementioned prototype. A fuzzy logic-based strategy was used for voltage control, employing the Matlab Fuzzy Logic Designer tool. The neural network was trainned with the network voltage, the voltage of the inverter stage, the current, the active and reactive power, and the power factor as inputs. Initially, the load power factor was 0.62 and the prototype operation allowed the voltage to be increased above the grid voltage, which is reflected in the forward current, modifying the power factor to a value of 0.91 while maintaining the same voltage. Finally, the results demonstrate the relationship between the increase of the inverter stage of the prototype above the electrical power line, obtaining a variable capacitor thus adjusting the power factor.

Development and Synthesis of Linguistic Models for Catalytic Cracking Unit in a Fuzzy Environment

This research develops a method for synthesizing linguistic models of fuzzy systems with fuzzy input and output parameters that are described by linguistic variables. Based on the proposed method, linguistic models of the Title 1000 catalytic cracking unit for heavy residues at the Shymkent oil refinery are developed, describing the dependence of the volume and quality of gasoline on the input and operating parameters of the facility, which are fuzzy. It is substantiated that the use of a fuzzy approach, which allows the use of the experience, knowledge, and intuition (intelligence) of the decision maker and subject matter experts, is the most suitable effective method for synthesizing models of complex, fuzzily described objects and processes for comparison with other methods. The main idea of the proposed work is to solve the problems of shortage and fuzziness of initial information when developing models and optimizing the operating modes of a catalytic cracking unit through the use of knowledge, experience, and intuition of experts in this field. To solve the problems of the shortage of initial quantitative information and the fuzziness of available information when developing mathematical models, it is proposed to systematically use statistical methods, expert assessment methods, and a heuristic method based on fuzzy logic. The scientific novelty of the research lies in the development of a method for synthesizing linguistic models in a fuzzy environment and an algorithm for its implementation, which makes it possible to describe the dependence of the fuzzy values of the object’s output parameters on its fuzzy input and operating parameters. The proposed approach allows the formalization and synthesis of models of fuzzily described objects when other methods of model development are not applicable or do not give the expected results. The results of the work were simulated in the MATLAB Fuzzy Logic Toolbox.

A Fuzzy Ballast Water Risk Assessment Model in Maritime Transport

Recent years have witnessed a growing awareness of the critical role that maritime transport plays in global sustainability, given its significant environmental, economic, and social impacts. Central to this concern is the management of ballast water, which, if not properly treated, can lead to the introduction of invasive species, biodiversity loss, and substantial economic and health repercussions. Traditional risk assessment models often fail to capture the complex uncertainties inherent in environmental risks associated with ballast water. This study introduces an innovative fuzzy logic-based risk assessment model designed to enhance decision-making processes in maritime operations by accurately assessing and mitigating the environmental risks of ballast water discharge. The model, structured using three fuzzy systems, integrates human reasoning with mathematical precision, providing an effective tool for sustainable maritime practices. The integrated fuzzy system employs 18 variables as inputs and yields three outputs (ballasting, ballast exchange, and de-ballasting risk). To evaluate the performance of the developed system, various data sets are used and tested through the MATLAB Fuzzy Toolbox. By aligning maritime operations with sustainability principles, this research contributes to the preservation of marine ecosystems, supports the economic stability of marine-dependent industries, and safeguards public health, underscoring the interconnectivity of maritime transport management with overarching sustainability objectives.

STRATEGIC AND LEADING DOMINANTS OF OVERCOMING ECONOMIC - MANAGEMENT DEVIATIONS OF CONSTRUCTION PROJECTS USING FUZZY LOGIC

The article defines the directions of functioning of the construction industry and stakeholders of construction enterprises, reveals the main directions and peculiarities of the functioning of construction enterprises in the conditions of martial law (during the full-scale invasion of the Russian Federation on the territory of Ukraine) and substantiated directions of transformational development in the period of post-war reconstruction. The components of the theoretical-methodological platform for the formation and implementation of development management of construction enterprises have been developed using a methodical approach to the evaluation of strategic sets of the enterprise based on the improvement of the classical quantitative strategic planning matrix (QSPM, Quantitative Strategic Planning Matrix). As a conceptual basis for identifying such factors, the McKinsey “7S” model was used, according to which all factors are grouped according to the signs of belonging to the following components: strategy, skills, common values (corporate culture), structure, employees, systems and style. As a result of the study, the factors affecting the formation and implementation of the adaptive capacity of the construction enterprise to the transformational changes of the operating system are proposed: labor productivity in the studied period; the ratio of administrative expenses to wages in operating expenses; the share of employees with higher education in the total number of management personnel; experience of management personnel; the ratio of labor costs to wage costs. The processes of economic-mathematical modeling of the influence of system factors on the integral indicator of the level of transformational ability of the enterprise are determined. To achieve the goals, the work uses methods of strategic diagnostics and fuzzy methods of multi-criteria evaluation with the help of the Matlab Fuzzy Logic Toolbox application program package.

Fuzzy Logic Method for Measuring Sustainable Decent Work Levels as a Corporate Social Responsibility Approach

The purpose of this study was to propose an interactive computer system that utilises the MATLAB Fuzzy Logic Designer to measure the level of implementation of SDG 8, which focuses on sustainable decent work (SDW) and economic growth. This study used policies and laws as parameters to determine the presence or absence of SDW. The fuzzy method was implemented in car windshield manufacturing in the auto parts industry as a case study to define and quantify work conditions and to determine the level of sustainable decent work (SDWL). The study described environmental conditions, such as noise, lighting, and heat stress; ergonomic factors, such as exposure time, the mass of the object manipulated, and lifting frequency; and organisation at work, such as workplace violence, salary, and workday, as linguistic variables. The level of the presence or absence of SDW was defined as their membership functions. The resulting vectors determined the absence of SDW with a score of 1.5 in two linguistic variables: environmental conditions and ergonomic factors. Some features of SDW in the linguistic variable organisation at work had an SDW score of 5. The SDWL vector determined a final score of 1.24, indicating the absence of decent work in production areas. This study found that the workers suffer a lack of long and healthy lives and a bad standard of living without economic growth due to work-related musculoskeletal disorders and work illnesses, increasing their out-of-pocket spending and catastrophic health expenses. As a CSR approach, assessing SDWLs helped managers improve policies and work conditions.

A Fuzzy-Based System for Autonomous Unmanned Aerial Vehicle Ship Deck Landing.

This paper introduces a fuzzy logic-based autonomous ship deck landing system for fixed-wing unmanned aerial vehicles (UAVs). The ship is assumed to maintain a constant course and speed. The aim of this fuzzy logic landing model is to simplify the task of landing UAVs on moving ships in challenging maritime conditions, relieving operators from this demanding task. The designed UAV ship deck landing model is based on a fuzzy logic system (FLS), which comprises three interconnected subsystems (speed, lateral motion, and altitude components). Each subsystem consists of three inputs and one output incorporating various fuzzy rules to account for external factors during ship deck landings. Specifically, the FLS receives five inputs: the range from the deck, the relative wind direction and speed, the airspeed, and the UAV's flight altitude. The FLS outputs provide data on the speed of the UAV relative to the ship's velocity, the bank angle (BA), and the angle of descent (AOD) of the UAV. The performance of the designed intelligent ship deck landing system was evaluated using the standard configuration of MATLAB Fuzzy Toolbox.

Proposal of a facilitating methodology for fuzzy FMEA implementation with application in process risk analysis in the aeronautical sector

PurposeThis study aims to propose a facilitating methodology for the application of Fuzzy FMEA (Failure Mode and Effect Analysis), comparing the traditional approach with fuzzy variations, supported by a case application in the aeronautical sector.Design/methodology/approachBased on experts' opinions in risk analysis within the aeronautical sector, rules governing the relationship between severity, occurrence, detection and risk factor were defined. This served as input for developing a fuzzyfied FMEA tool using the Matlab Fuzzy Logic Toolbox. The tool was applied to the sealing process in a company within the aeronautical sector, using triangular and trapezoidal membership functions, and the results were compared with the traditional FMEA approach.FindingsThe results of the comparative application of traditional FMEA and fuzzyfied FMEA using triangular and trapezoidal functions have yielded valuable insights into risk analysis. The findings indicated that fuzzyfied FMEA maintained coherence with the traditional analysis in identifying higher-risk effects, aligning with the prioritization of critical failure modes. Additionally, fuzzyfied FMEA allowed for a more refined prioritization by accounting for variations in each variable through fuzzy rules, thereby improving the accuracy of risk analysis and providing a more realistic representation of potential hazards. The application of the developed fuzzyfied FMEA approach showed promise in enhancing risk assessment in the aeronautical sector by considering uncertainties and offering a more detailed and context-specific analysis compared to conventional FMEA.Practical implicationsThis study emphasizes the potential of fuzzyfied FMEA in enhancing risk assessment by accurately identifying critical failure modes and providing a more realistic representation of potential hazards. The application case reveals that the proposed tool can be integrated with expert knowledge to improve decision-making processes and risk mitigation strategies within the aeronautical industry. Due to its straightforward approach, this facilitating methodology could also prove beneficial in other industrial sectors.Originality/valueThis paper presents the development and application of a facilitating methodology for implementing Fuzzy FMEA, comparing it with the traditional approach and incorporating variations using triangular and trapezoidal functions. This proposed methodology uses the Toolbox Fuzzy Logic of Matlab to create a fuzzyfied FMEA tool, enabling a more nuanced and context-specific risk analysis by considering uncertainties.

Biodiesel Production from Sal Oil: A Mamdani-Type Fuzzy Inference System Using the Fuzzy Logic Toolbox Graphical User Interface (Gui) Tools

This paper describes the performance evaluation of fuzzy logic controller in Biodiesel Production system using MATLAB Simulink and MATLAB Fuzzy Logic Toolbox. Biodiesel (fatty acid alkyl esters) is derived from triglycerides by transesterification with alcohol, has attracted considerable attention during the past decade as a renewable, biodegradable, and nontoxic fuel. Vegetable oils are produced from numerous oil seed crops and many of them are used for edible purpose. The oil obtained from Sal seeds (Shorea Robusta) even though used by local tribes in Indian forests for edible purpose, it is still classified as non-edible oil. Sal tree is abundantly available in forests of Indian subcontinent and this wood is used in building construction and manufacture of furniture because of its characteristic hardness. In this paper maximum output yield-Biodiesel Production has been done (SOME-Sal Oil Methyl Esters) by optimizing reaction parametersin relation to the Excess Methanol Quantity (EMQ, 150%),Reaction Temperature (RT, 65°C), Catalyst Quantity (CQ, NaOH - 0.25 W%) by Max-Min (MAMDANI) Method Fuzzy Inference System using the Fuzzy Logic Toolbox Graphical User Interface (GUI) Tools of MATLAB (Intelligent System).

Evaluation of Technological Innovation Initiatives for Indian MSMEs Using the Fuzzy-Based Model

Micro, small and medium enterprises (MSMEs) are considered as a growing sector of the country due to their huge growth potential and possible social or economic effect, especially on employment and revenue generation. Existent globalised competition compels companies to constantly look for methods to improve their products and services. Without continuous innovation, manufacturing companies cannot remain competitive. Innovation represents the keyways the organisation responds to technical or market-related challenges. All manufacturers are currently trying to implement Multicriteria Decision-Making (MCDM) techniques such as Analytic Hierarchy Process, Piecewise Affine and fuzzy models, along with technology innovation initiatives (TIIs) for enhancing their production performance. In the current study, an attempt is made to assess the synergy fit of TIIs for MSMEs in India. The study considers metrics related to these initiatives, such as product performance and sales performance. In addition, these procedures use the MATLAB Fuzzy Logic Toolbox for the analysis of a Simulink block for designing and simulating the data set.

A quality learning environment: an assessment of spaciousness of architectural design studios of Iraqi Kurdistan region universities using fuzzy logic

PurposeSpaciousness is defined as “the feeling of openness or room to wander” that has been affected by various physical factors. The purpose of this paper is to assess the spaciousness of space to determine how spacious the space is. Furthermore, the study intends to propose a fuzzy-based model to assess the degree of spaciousness in terms of physical parameters such as area, proportion, the ratio of window area to floor area and color value.Design/methodology/approachFuzzy logic is the most appropriate mathematical model to assess uncertainty using nonhomogeneous variables. In contrast to conventional methods, fuzzy logic depends on partial truth theory. MATLAB Fuzzy Logic Toolbox was used as a computational model including a fuzzy inference system (FIS) using linguistic variables called membership functions to define parameters. As a result, fuzzy logic was used in this study to assess the spaciousness degree of design studios in universities in the Iraqi Kurdistan region.FindingsThe findings of the presented fuzzy model show the degree to which the input variables affect a space perceived as larger and more spacious. The relationship between parameters has been represented in three-dimensional surface diagrams. The positive relationship of spaciousness with the area, window-to-floor area ratio and color value has been determined. In contrast, the negative relationship between spaciousness and space proportion is described. Moreover, the three-dimensional surface diagram illustrates how the changes in the input values affect the spaciousness degree. Besides, the improvement in the spaciousness degree of the design studio increases the quality learning environment.Originality/valueThis study attempted to assess the degree of spaciousness in design studios. There has been no attempt carried out to combine educational space learning environments and computational methods. This study focused on the assessment of spaciousness using the MATLAB Fuzzy Logic toolbox that has not been integrated so far.

Fuzzy Logic Controller for Temperature Control

This paper describes the use of MATLAB in the design and implementation of a temperature control system for agricultural applications based on fuzzy logic. The system uses two inputs—the user-specified target temperature and the temperature sensed from the agricultural field—to produce two outputs for positive and negative pulse width modulation (P-PWM-C and N-PWM-C). With membership functions defined for the input and output ranges, the fuzzy logic controller is designed using the MATLAB Fuzzy Logic Designer. Ten guidelines are created to regulate the temperature control procedure. The relationship between the inputs and outputs is shown in the 3D surface viewer, which sheds light on the fuzzy logic control approach.

ПРИМЕНЕНИЕ НЕЧЕТКОЙ ЛОГИКИ ДЛЯ ПРИНЯТИЯ РЕШЕНИЙ ОБ ЭВАКУАЦИИ ПРИ НАВОДНЕНИИ

We are talking about natural disasters, such as flooding, which can be predicted a fewhours before they occur so that evacuation of the population can be organized. Evacuationmeans that people in disaster areas must leave these areas and reach shelters. The article pr esentsan analysis of the decision-making process on evacuation, the main criteria determiningthe decision and the main stages of using fuzzy logic to make a decision on evacuation based onqualitative and quantitative values of the decision-making criteria. These stages include selectionof criteria, determination of qualitative input and output variables, fuzzification of variables,definition of the base of fuzzy rules, construction of fuzzy inference, visualization of resultsand sensitivity analysis. When modeling, the following criteria were taken into account: thepredicted flood level, the level of danger, the vulnerability of the area of the expected flood andthe possibility of safe evacuation. The predicted flood level was based on the parameters of themaximum level and the rate of water rise. The hazard level reflected the physical characteristicsof the flood and its potential impact on the safety of people in the flood area. The vulnerabilityof the area of the expected flood was defined as the inability at the local level to prevent peoplefrom direct contact with flood waters during the event. The possibility of safe evacuation wasdefined as a set of limitations and potential negative aspects that could delay or hinder the successfulevacuation. The description of qualitative variable criteria for making a decision on theneed for evacuation, examples of determining the base of fuzzy rules are presented. The fuzzymodel is implemented using Matlab Fuzzy Logic Toolbox. The procedure of fuzzy inference andinterpretation of the solution and a model of several scenarios and flood situations are described.The method by which a fuzzy model of decision-making on evacuation can be applied incombination with a geoinformation system is considered. The actions related to the need forevacuation for various scenarios and circumstances are presented.

A KNOWLEDGE-BASED DECISION SUPPORT SYSTEM FOR SELECTION OF SUSTAINABLE STRUCTURALMATERIALS: USINGFUZZY EXPERT SYSTEM

One of the most critical elements in the construction industry is the materials used in the structure. The selection of appropriate materials can significantly impact cost, durability, beauty of the building, and many other aspects. Given the importance of sustainable development, it is necessary to carefully examine all the sustainability dimensions, including economic, social, environmental, and technical, which impact both the construction and operation phases of a building lifecycle. This study develops a Fuzzy Expert System (FES) as a knowledge-based decision support system (KBDSS) to rank structural materials according to sustainability criteria. A total of twelve sub-criteria are considered, three under each sustainability criterion. The FES is divided into five sub-systems to reduce the number of rules. A total of 243 rules are implemented in the model using MATLAB Fuzzy Logic Designer Toolbox. A case study was performed to evaluate four structural materials for sustainability criteria. These materials are: timber, concrete, steel, and blended cement. The results of the case study show that timber is the most sustainable material according to user input. However, the developed model can be easily calibrated to reflect changes in experts’ opinions, leading to a different ranking of structural materials.

A KNOWLEDGE-BASED DECISION SUPPORT SYSTEM FOR SELECTION OF SUSTAINABLE STRUCTURALMATERIALS: USINGFUZZY EXPERT SYSTEM

One of the most critical elements in the construction industry is the materials used in the structure. The selection of appropriate materials can significantly impact cost, durability, beauty of the building, and many other aspects. Given the importance of sustainable development, it is necessary to carefully examine all the sustainability dimensions, including economic, social, environmental, and technical, which impact both the construction and operation phases of a building lifecycle. This study develops a Fuzzy Expert System (FES) as a knowledge-based decision support system (KBDSS) to rank structural materials according to sustainability criteria. A total of twelve sub-criteria are considered, three under each sustainability criterion. The FES is divided into five sub-systems to reduce the number of rules. A total of 243 rules are implemented in the model using MATLAB Fuzzy Logic Designer Toolbox. A case study was performed to evaluate four structural materials for sustainability criteria. These materials are: timber, concrete, steel, and blended cement. The results of the case study show that timber is the most sustainable material according to user input. However, the developed model can be easily calibrated to reflect changes in experts’ opinions, leading to a different ranking of structural materials.

Design of a Fuzzy Logic Evaluation to Determine the Ergonomic Risk Level of Manual Material Handling Tasks.

In this work, we propose a fuzzy inference as a decision support system built in the MATLAB Fuzzy Logic Designer for evaluating manual material handling risk conditions. The input variables for the fuzzy decision were: (1) the total time duration of the manual material handling in one shift of 450 min, with 3 h considered the maximal exposition time; (2) 25 kg as a maximal mass reference which should never be exceeded; (3) the repetitiveness of the manual material handling task through the shift considering as the maximal frequency of four lifts per min. Results of 135 earlier direct ergonomic evaluations made using the method proposed by the ISO 11228-1 were used as validator results, and called “expected results”. The experimentation intended to simulate an ergonomic evaluation in different boundary conditions of work and verify if the fuzzy interface could correctly replicate the results of the ergonomic evaluations. As validation, the list with the 135 expected results was compared against the evaluation made by the fuzzy logic interface, called “Work_Conditions”. From the comparison, only three evaluations (0.02%) differed with respect to the expected results. Consequently, it is concluded that the fuzzy interface can be used as a tool for automating the determination of manual material handling ergonomic risk levels, with great precision.

Sustainability Management Model Based on Risk Analysis and Implementation of the Model

In modern business management, the effective management of organizational structures based on goals within the scope of modern management concepts, as well as the continuous improvement of processes for increasing competitiveness, are critical. The purpose of this study is to discuss the matter of risk identification and analysis, practices that are seen in many different fields within the scope of the notion of sustainable management. It aimed to add the dimensions of targets and risk analysis to the scope of process analysis and development, within this study. The stages, starting with the definition of the processes in the process model through the targets based on the risk analysis, are transformed into a quality assurance cycle and completed with the determination, monitoring, and evaluation of the sustainable process development activities. The performance indicators of the business processes in a textile business were determined, and the identification of a model structure with systematic traceability was provided, in practice. The opportunities and threats encountered in achieving the determined goals were identified. The defined factors were examined within the scope of the failure mode and effects analysis and risk analysis methods. The risk evaluations were performed using fuzzy numbers. The results obtained by fuzzy failure mode effects analysis were evaluated through the MATLAB Fuzzy Logic Design Toolbox model. Risks were ranked as a result of the evaluation, and process development activities were chosen.

Fuzzy logic as a decision-making support tool in planning transport development

Deliberations on transport development indicate that planning is its most significant aspect. One of the key issues in planning is selecting infrastructure projects for completion that will contribute to achieving the development objectives. The important functions of planning, as well as its complexity, indicate the need to use solutions in the decision-making support field. In Poland, in the area of strategic planning of infrastructure development, methods of supporting decision-making aimed at selecting infrastructure projects, taking into account their degree of compliance with strategic goals, are currently not applied comprehensively. The paper aims to address this gap with MCDA solution basing on review of literature combined with the authors’ experience in transport planning. Therefore, authors presented a proposed tool for supporting decision-making in planning transport development on a strategic level. The presented method allows for assessing infrastructure development projects in road and rail transport. Such assessments take into account a number of criteria corresponding to the main development directions, i.e. sustainable development and quality of life. Due to the method of formulating development objectives, it has been decided that it will be advantageous to apply fuzzy logic, which enables using natural language in decision-making support systems. To allow practical application of fuzzy logic, the Fuzzy Logic Toolbox package available in the MATLAB environment has been employed. The developed model contains a structure along with defined linguistic variables reflecting the decision-making criteria; also, it includes membership functions, inference rules as well as assessment results. The paper also defines the algorithm of decision-making support procedure. For verification purposes, the decision support model was applied in several real-life project evaluation cases, including a variety of projects in construction, development, and renovation of rail and road infrastructure. The deliberations described in this paper indicate the usefulness of fuzzy logic for supporting decision-making in planning transport development. It’s beneficial that the defined criteria can be applied in the case of projects in early preparation phase, enabling their practical application. Implementation of the solution in the MATLAB Fuzzy Logic Toolbox enables achieving fast results of the assessment of decision-maker preference level.

PENENTUAN JURUSAN PADA PROSES PENERIMAAN MAHASISWA DENGAN PENDEKATAN LOGIKA FUZZY

Choosing a major is not an easy matter. There are many factors that must be taken into account and carefully thought out so that in choosing a major, it will cause big losses. There are many ways to determine the selection of majors, one of which is by using fuzzy logic. Determination of majors is determined from the results of the selection test in the academic field with the subjects of Mathematics, English and Computer Knowledge. With the aim of recommending the selection of the right major according to academic abilities and improving quality. By using the fuzzy inference model Mamdani max-min method. The system simulation was tried using the MATLAB Fuzzy Toolbox software. The system design is carried out in several stages, namely: (1) formation of fuzzy sets, (2) formation of rules, (3) determination of the composition of rules, and (4) confirmation (defuzzification). Defuzzification is carried out using the Composite Moment method, with the types of membership functions used are mf-triangular, mf-trapezoid and mf-gaussian. From the results of the tests carried out, it shows that the mf-triangular and mf-trapezoid membership function types produce almost the same level of accuracy. While the membership function type mf-gaussian produces a high level of accuracy for mathematics by 87.50%, English 100% and computer knowledge 81.58%.

Evaluate of The Reproductive Efficiency of Cows With Fuzzy Logic

Fuzzy Logic (Fuzzy Logic) is a branch of science based on thinking like human beings and solving them with mathematical functions. Fuzzy logic theory is a mathematical theory. Based on fuzzy set theory, it also uses intermediate values. The fuzzy logic that emerged in 1965 is used in many fields. In the production of pacemakers, in the production of artificial organs, in many electronic devices, company efficiency estimation, etc. situations are used. Fuzzy logic, which is frequently used in the solution of problems that occur in uncertain situations such as quality assessment in recent years, is one of the artificial intelligence methods. With the help of machines, people-specific data and experiences are studied using the fuzzy logic approach. In this study, by using Matlab Fuzzy Toolbox, it was aimed to design a system that gives information about the breeding performances of cows. The expert system was designed based on the optimal values under the ideal conditions specified in the literature. The architecture of the system presented in this paper is designed as three input parameters and one output. The designed system was tested with 100 sample values. Afterwards, expert results were evaluated and system decisions were compared. The success of the decision support system was 94%. As a result, the reproductive efficiency of cows can be determined with this designed system. With this determination, the handling or disposal of cows can be determined.

Evaluation of Distribution System Reliability Indices Using Fuzzy Reasoning Approach

The most fundamental problems in the distribution system are the quality, the continuity, and the power supply. Political and economic changes were accompanied by changes in the structure of the electric load in the distribution network. Lack of investment and aging of the distribution company assets was accompanied by a decrease in the reliability of the distribution system. Identification and classification of assets from the point of view of their maintenance and replacement was one of the problems that were posed to the engineers. Fuzzy logic can be successfully used to evaluate distribution system reliability indices. In this paper fuzzy logic is used to evaluate the distribution system reliability indices of lines and transformers using six input variables. These variables considered the most important are: Age, Operation, Maintenance, Electrical current loading, Exposure and Weather conditions (Wind or Temperature). The fuzzy inferences knowledge-based IF-THEN rule is developed using Matlab Fuzzy software. The detailed analysis of the fuzzy system surfaces shows that the factors taken in consideration are dynamically and accurately connected to each other. The constructed rules based in engineering experience accurately represent the Reliability Indices.