Rancang Bangun Pengiris Bawang Merah Otomatis Dengan Sensor Load Cell Berbasis IOT

Wirzal, Alwi and , Umar , S.T., M.T (2024) Rancang Bangun Pengiris Bawang Merah Otomatis Dengan Sensor Load Cell Berbasis IOT. Skripsi thesis, Universitas Muhammadiyah Surakarta.

	PDF (Naskah Publikasi) Naskah Publikasi_Alwi Wirzal_D400200066_Bismillahh_rev3.pdf Download (569kB)
	PDF (Surat Pernyataan Publikasi) UNGGAH alwi.pdf Restricted to Repository staff only Download (291kB) | Request a copy

Abstract

Shallots are a type of plant that is very important and popular in society, having a crucial role in various cooking recipes, especially in making fried onions with processed ingredients from shallots and the manufacturing process is done by slicing, then the slicing stage to make fried onions in Home and restaurant areas are still done manually. This is one of the causes of user weakness due to limited production quantities and low levels of efficiency. Overcoming this weakness, an automatically controlled onion slicer was designed which can slice quickly and practically. This automatic onion slicer uses IoT and a special program that can improve the slicing process in a relatively short time and will work if given the desired command. The automatic onion slicer has a working principle consisting of a load cell sensor connected to the ESP32, where the load cell sensor will read the weight of the sliced onions. The DC motor will receive a signal to move the slicing knife, then this tool can be controlled with a smartphone equipped with an IoT system via the blynk application. Based on the research, the results obtained for the thickness of the onion slices with several different parameters with the speed controlled by PWM, namely, when the PWM is 125, the speed is 1632 rpm with a slice thickness of 1.7 mm and when the PWM is increased slightly to 175, the PWM gets a speed of 2252 rpm with a thickness. becomes 1.2 mm slightly thinner then when the PWM 255 gets a speed of 2835 rpm the resulting slice becomes thinner, namely 0.8 mm.

Item Type:	Thesis (Skripsi)
Uncontrolled Keywords:	ESP32, IoT, DC Motor, Slicing Blade, Loadcell Sensor.
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Fakultas Teknik > Teknik Elektro
Depositing User:	ALWI WIRZAL
Date Deposited:	29 Jul 2024 02:01
Last Modified:	29 Jul 2024 02:01
URI:	http://eprints.ums.ac.id/id/eprint/125565

Actions (login required)

View Item