Analysis of maizena drying system using temperature control based fuzzy logic method

Arief, Ulfah Mediaty; Nugroho, Fajar Adi; Purbawanto, Sugeng; Suryono, Suryono

doi:10.1063/1.5028063

Cited by 4 publications

(3 citation statements)

References 7 publications

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“…Recently, modern methods and technologies have found application in the textile industry [15][16][17][18]. Expert systems are among the leading techniques [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Mikrodalga kurutucu için bulanık modelleme: Pamuklu dokuma kumaş kurutma işlemi

Akarslan

2023

Uluslararası Teknolojik Bilimler Dergisi

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Microwave drying stands out because it is faster than traditional drying methods, drying in the product is more uniform and energy efficiency. In this study, fuzzy modeling of a microwave dryer was developed. Microwave dryer is considered as a non-linear dryer. The proposed fuzzy model is used to estimate the drying rate for different electrical powers and different drying times. Different experimental measurements were used to evaluate the reliability of this model. Compared to other modeling techniques, thanks to simulation, the fuzzy model of the dryer provides an immediate estimation of the drying rate. This study will provide drying rates under demanded conditions and help determining machine parameters for a given product providing time and energy saving.The behavior predicted by the fuzzy model confirms the suitability of the defined model.

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“…Recently, modern methods and technologies have found application in the textile industry [15][16][17][18]. Expert systems are among the leading techniques [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Mikrodalga kurutucu için bulanık modelleme: Pamuklu dokuma kumaş kurutma işlemi

Akarslan

2023

Uluslararası Teknolojik Bilimler Dergisi

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“…enables such studies. Recently, modern methods have found application in the textile industry [6][7][8][9]. Expert systems are among the leading techniques [10].…”

Section: Introductionmentioning

confidence: 99%

Determining The Drying Rates of Fabrics with Different Knit Structures by Fuzzy Logic Method

Akarslan

KODALOĞLU

2023

International Journal of Computational and Experimental Science and Engineering

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Drying; It is a process applied to reduce the amount of water in a product or to reduce it to very low levels. The constantly changing conditions during the drying process make it difficult to determine the most suitable operating conditions to perform the drying process, such as drying time, energy consumption and product structural characteristics. In terms of a suitable drying, it is important to be able to control the factors affecting the drying depending on the characteristics of the product. Among these factors, the drying method and the pre-treatments that can be applied are also effective on drying. The high temperatures applied during drying and other conditions that are not chosen correctly can cause negative results in both the appearance of the product. The drying process in the textile industry is an expensive and laborious process that requires a lot of energy. The main purpose of the drying process is to provide maximum energy saving and energy efficiency at minimum time and cost without compromising the quality and structural properties of the material used. In this study, four fuzzy models were created depending on fabric fiber blend ratios and knitting structure in order to determine the effect on drying speed depending on time and temperature by using fuzzy logic method, which is one of the artificial intelligence methods.

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“…Another study conducted research using the fuzzy logic method as a temperature controller for the grain dryer. It showed that the fuzzy control system worked well because of the LPG gas with a stable temperature [13]. Other research has been conducted on the automatic control of lights and air conditioners in lecture rooms based on Arduino nano microcontrollers and managed to save electricity expenditure for a month with PIR sensors detecting the presence of people and LDR sensors which detect light intensity in the room [14,15].…”

Section: Introductionmentioning

confidence: 99%

Modeling and implementing a load management system for a solar home system based on Fuzzy Logic

Saini,

Djalal,

Azhar

et al. 2023

Sinergi

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Solar Home System is one of the technologies for utilizing solar power at home. To optimize the performance of PLTS, it is necessary to regulate the use of electrical energy. In this research, an effort is made to control the load using fuzzy logic to regulate the power consumption used by the load so that energy can be utilized effectively. The fuzzy logic method works based on the input given so that the desired results can be as expected. To test the effectiveness of the fuzzy logic method, this study was tested with two types of loads: lighting and fan loads. For lighting loads, it uses two light sensor inputs, and for air conditioning, it uses two temperature sensor inputs and a PIR sensor. The test results show that in the experiment of setting the light load using fuzzy logic, the average power usage at the load is 11.31 watts. In contrast, without fuzzy logic, the average power usage value for the load is 14.29 watts. In the fan load control experiment using fuzzy logic, the energy consumption setting was obtained according to the room temperature input and the number of people in the room. The test results received power usage without using fuzzy logic, where the average fan power usage value is 4.32 Watts, while without fuzzy logic, the average power usage value is 2.97 Watts. For one sensor input, the average power usage value of the average fan is 3.02 Watts; without fuzzy logic, the average power usage value is 2.93 Watts for two sensor inputs.

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Analysis of maizena drying system using temperature control based fuzzy logic method

Cited by 4 publications

References 7 publications

Mikrodalga kurutucu için bulanık modelleme: Pamuklu dokuma kumaş kurutma işlemi

Mikrodalga kurutucu için bulanık modelleme: Pamuklu dokuma kumaş kurutma işlemi

Determining The Drying Rates of Fabrics with Different Knit Structures by Fuzzy Logic Method

Modeling and implementing a load management system for a solar home system based on Fuzzy Logic

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