SIMULASI SISTEM PENCUCI BAHAN TEKSTIL BERBASIS LOGIKA FUZZY

Authors

  • Muhammad Fatih Azhari Asyauqi Mahasiswa Universitas Negeri Semarang

Abstract

Abstrak

Untuk memaksimalkan tingkah kebersihan dari proses pencucian dan meningkatkan efisiensi energy pada mesin pencuci dapat dilakukan control berbasis logika fuzzy. Dengan logika fuzzy, variable sekitar dapat dilakukan operasi untuk melakukan pengambilan keputusan dengan membuat rentang variable diantara 0 dan 1. Pada system pencuci nilai nilai pada bahan digunakan sebagai nilai input. Simulasi dilakukan dengan software matlab, variable berupa massa dan tingkat kekotoran dari bahan yang menghasilkan keluaran berupa kecepatan motor untuk mencuci bahan. Tingkat kekotoran dari bahan dimasukkan dalam persen dan massa dari bahan dalam kilogram (Kg). Tingkat kekotoran dan berat bahan mempengaruhi kecepatan motor, semakin kotor dan berat bahan maka kecepatan akan bertambah. Hasil yang didapatkan berupa nilai kecepatan motor dari kecepatan maksimalnya yang dipengaruhi oleh beberapa variable.

Kata Kunci- Logika Fuzzy, Mesin Pencuci, Simulasi, Matlab

 

Abstract

To maximize the cleanliness behavior of the washing process and increase the energy efficiency of the washing machine, fuzzy logic used as a control. With variable fuzzy logic, operations used to make decisions by making a variable range between zero and one. In the system, the value of the value of the material used is the input value. By using matlab software for simulation, the variables in the form of mass and level of dirtiness of the material which produce output in the form of motor speed for washing the material. The level of impurity of the ingredients is in percent and the mass of the material is in kilograms (Kg). The level of dirtiness and suggestions that affect the speed of the motor, the dirty and suggestion, the material will increase. The results obtained are in the form of motor speed values from the maximum built by several variables.

Keywords-Fuzzy Logic, Washing Machine, Simulation, Matlab

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Published

2021-04-30 — Updated on 2021-04-30

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