Papers by Keyword: Fuzzy Logic

Abstract: Modern automated manufacturing environments are highly agile and are confronted with continuous change in market demands/customers’ requirements. Flexible Manufacturing Systems (FMSs) cater to the need of extensive flexibility and ability to manufacture different variety of batch quantity of components simultaneously in the highly dynamic environment. In FMSs, automated guided vehicle (AGV) systems are commonly used to control complex automated material handling systems. Path design as well as planning and control of AVGs are challenging problems for researchers. In this work, an attempt has been made to model AGVs in FMS using fuzzy logic technique as a modeling tool. A hypothetical FMS system with two AGVs, four processing stations, one buffer and an input/output station is considered. Parts routing, processing operations, allotted machines, processing time and part-mix variation are inputted. AGVs movement to be accomplished for movement of parts obtained is based on rule base consisting of ‘If – then’ statements. Movement of AGVs in FMS without any deadlock for moving the part in an optimized path so as to achieve maximum utilization of the system is aimed. The methodology is demonstrated with illustrative examples.

Abstract: Stainless steel SS304 is extensively used in dental applications for its high strength, hardness, and corrosion resistance. However, Conventional dental joining techniques such as soldering and fusion welding, reliant on elevated temperatures and toxic fluxes, present substantial oral health risks, leading to potential health deterioration due to toxic emissions. The study proposes the utilization of a microwave hybrid heating process (MHH) for joining stainless steel SS304 (15mm × 7.9mm × 0.2mm) and pure zinc metal powder (44 µm, 99% purity), citing its enhanced efficiency, speed, precision, and diminished environmental footprint as key characteristics without fume. It explores heat processing between 30°C to 60°C and cold temperature processing from 0°C to 10°C to analyze alterations in hardness properties and microstructures. The study identified a direct correlation between temperature and microhardness, observing an increase in microhardness with rising temperatures. Optimal microhardness of 208.6 HV was achieved at 60°C during a 3 min heat treatment. Cold temperatures induced slight deformation and grain transformation, while heat treatment enhanced grain density and hardness, particularly in the strongly bonded boundary layer, with experimental and predicted values using Fuzzy logic showing promising outcomes and errors below 10%. In conclusion, the study demonstrates that achieving a specific hardness value in stainless steel joints is highly desirable for dental applications, alongside the observation of favorable microstructures. These findings underscore the potential of MHH to propel dental technology forward and promote sustainable practices while addressing environmental concerns.

Abstract: Fatigue is a condition experienced by a person that causes a decrease in a person's vitality and productivity. Fatigue can be characterized by slowed reaction time and fatigue. People’s condition is a significant factor in driving safety. Based on this increase in the number of accidents according to the Central Statistics Agency (BPS), experts conducted research on detecting fatigue that often occurs. In this study, a system that can detect fatigue is developed using parameters obtained from physiological indicators such as heart signals by using the Low Frequency/High Frequency ratio parameter, muscle signals using the average frequency domain of the muscle signal and oxygen saturation. The detection tool in this study uses the ECG Click Module, EMG Click Module, and Oximeter Click which will be connected to the ARM microcontroller, namely STM32F407ZG. The parameters that have been obtained are processed using the Fuzzy Logic method to determine the level of fatigue. Based on the tests results carried out on three subjects, parameter values were obtained where in the subject the three parameters entered into fuzzy logic, it was found that the three subjects were detected in a fairly tired state. The aggregated output that found from subject A was 0.6303, the aggregated output of subject B was 0.77948, and the aggregated output of subject C was 0.79188. Furthermore for future research development, the signal processing can be done more complex, besides that signal processing and fuzzy logic processing can be embedded so the process runs in realtime.

Abstract: In this work, we are interested in the faults diagnosis and the faults prognosis in discrete event systems described by sequences of generated events. Through this work, we aim the maximization of the efficiency of diagnosis/prognosis operations by combining two concepts. The first one is the approach already developed in one of our works which consider the k-last generated events to perform the diagnosis/prognosis. The second concept is the reliability that takes into consideration the life cycle of each component of the discrete event systems to give the failure probability. This combination will be made using some notions of fuzzy logic.

Abstract: The reliability evaluation of an equipment is made through its functionality analysis in specific conditions. When these conditions are various, the accomplishment of functional requirements could be partial, not integral. In these cases, the reliability evaluation is realised through methods specific to systems with many stages, those based on the fuzzy logic being one of them. In this paperwork there are presented the most used algorithms for evaluation.

Abstract: Incremental forming is a promising manufacturing process which allow the user to obtain sheet metal parts, in a flexible manner, without the use of a die. However, the industry is still reluctant to apply the process on an industrial scale. Several drawbacks of the process which hinder its industrial implementation are reviewed in the paper. Among them, the low accuracy of the parts and the low productivity of the process are considered. The lack of dedicated technological equipment and specific CAM software tools are also seen as major drawbacks. Moreover, the lack of any analytical tools to predict the plastic behaviour of the processed part and to predict the moment when it loses its integrity influences the adoption of incremental forming on a large scale. Aside of summarizing these drawbacks, the paper tries to develop a decision-making system, based upon fuzzy logic, for assessing the degree of industrial implementation of the incremental forming process, if certain conditions are met.

Abstract: Economics is the first supply for the survival of a country, especially in the development, development and progress. The more developed a country is the better economic growth. Indonesia including the user databases on the economy, especially in the banking sector and the government. Government as the manager of the country's economy in order to make extra efforts of the people and citizens can get considerable economic assistance through various operations conducted by the government such as the division of poor rice and BPJS card. BPJS stands for Badan Penyelenggara Jaminan Sosial (Social Insurance Administration Organization). By doing classifying economic levels using Fuzzy Multiple Attribute Decision Making (FMADM) methods (Simple Additive Weighting) meant that applications created can be used as a tool to suppress errors and improve accuracy by minimizing the possibility of such a wrong target or targets. The application uses the input in the form of data that has a high level of security to be forged such as: proof of payment of electricity bills, vehicle tax, and property tax. Data from the family card to input the number of people staying. The results are sorted according emerged from the lowest to the highest. The calculations were already system and by calculation that has been designed is expected to work as expected.

Abstract: In this study, a novel fuzzy behavioral TOPSIS model was proposed. Sensitivity analysis is conducted according to the behavioral TOPSIS model parameter (λ) for the different case studies taken from the literature. The ranking results are slightly different according to different λ values. The results of the study can be used in material and manufacturing method selection problems.

Abstract: In petroleum industry, hydrodesulphurization (HDS) process is considered as one of the crucial catalytic units in which the sulfur is mostly eradicated. The modeling of HDS process is very important for the proper understanding of the process operation to be optimized. The studies conducted, in this area, focused on predicting parameters using analytical, empirical and numerical approaches. However, a typical desulfurization process is constantly faced with an uncertainty, which should be considered in a reasoning way. Therefore, this work aims to explore the use of fuzzy logic (FL) inference system in creating models of the HDS process for the prediction of sulfur reduction from oil. In order to validate the proposed model, we employed experimental data from the HDS setup. The simulated sulfur content results obtained from the proposed model correspond closely to the real experimental values. The outstanding performance of the developed FL-based model suggests its potential in predicting sulfur content for optimization of the HDS process. The model demonstrates promising results in terms of high correlation (R²=0.98) and minimal percentage of error (AARE=0.072).

Abstract: The authors approve a mathematical model for estimating the value of an object taking into account trends in the residential real estate market in the MATLAB software package with the assignment and correction of the fuzzy set membership functions. Fuzzy computations are performed using the Mamdani method, which requires defining the membership functions for the output variables. We consider schemes for constructing systems of fuzzy inference for variables (the real estate object state) and (the real estate market state). The results of calculations using the Fuzzy Logic Toolbox are given on the surfaces of fuzzy inference systems that show the dependence of the output variables on the individual input variables.