Perancangan Prototipe Sistem Kendali Otomatis Pada Pengering Pakaian Berbasis Air Heater

Pengering pakaian diharapkan dapat bekerja secara otomatis dan dapat menjaga kualitas pakaian yang dikeringkan. Terdapat parameter penting pada proses pengeringan pakaian yaitu temperatur dan kelembaban. Untuk menjaga kualitas pakaian, perlu diperhatikan nilai temperatur pengeringan agar tidak melebihi batas temperatur pengeringan yang ditentukan pada setiap jenis pakaian. Oleh karena itu, diperlukan pengaturan setpoint temperatur pengeringan pakaian pada alat pengering pakaian. Pada penelitian ini dirancang prototipe pengendali yang dapat bekerja secara otomatis pada sebuah sistem pengering berbasis air heater. Prototipe yang dirancang terdiri atas air heater, sensor temperatur, sensor kelembaban, Arduino, dan tampilan antarmuka menggunakan LabVIEW. Proses pengeringan dioperasikan oleh pengguna melalui antarmuka dimana pengguna memasukan dua input yaitu jenis pakaian yang akan dikeringkan dan jumlahnya. Input tersebut digunakan pada penentuan nilai temperatur operasi pada air heater. Selama proses pengeringan, nilai temperatur maupun nilai kelembaban pada bilik pengering diukur menggunakan sensor tipe DHT22. Kedua nilai lalu tersebut ditampilkan melalui antarmuka LabVIEW. Nilai temperatur tersebut dibandingkan dengan nilai temperatur setpoint yang ditentukan berdasarkan jenis dan jumlah pakaian yang akan dikeringkan. Berdasarkan nilai perbandingan tersebut, LabVIEW mengirimkan nilai kendali berupa nilai PWM secara serial ke Arduino, yang merupakan sinyal kendali ke air heater. Kemudian, air heater bekerja menjaga temperatur pada bilik pengeringan agar sesuai setpoint selama proses pengeringan berjalan atau kondisi timer on. Jika nilai kelembaban telah mencapai kriteria kondisi kering dan waktu pengeringan telah habis, maka air heater akan masuk pada mode off. Berdasarkan hasil pengujian, prototipe sistem kendali yang dirancang mampu bekerja secara otomatis dan hasil pengeringan dapat mempertahankan kualitas pakaian. Selain itu penghematan energi listrik juga dimungkinkan dengan penggunaan pengendali otomatis pada pengering pakaian tersebut.The clothes dryer is expected to work automatically and can maintain the quality of the clothes. Temperature and humidity are the two main parameters in the process of drying clothes. The drying temperature affects the clothes conditions because each type of clothing has a certain temperature limit to maintain its quality. Therefore, it is necessary to set the temperature setpoint for drying clothes operation. This study designed a controller prototype that can work automatically in an air heater-based clothes dryer. The designed prototype consists of an air heater, temperature sensor, humidity sensor, Arduino, and an interface using LabVIEW. The drying process is operated by the user through an interface where the user inputs the type of clothing and the amount of clothing to be dried. The input is used to determine the temperature setpoint on the air heater. During the drying process, the temperature and humidity values in the drying chamber are read by the DHT22 sensor and then displayed on the interface. This temperature value is compared with the setpoint temperature which is determined based on the type and amount of clothes to be dried. Based on the comparison value, LabVIEW sends control values in the form of PWM values serially to Arduino, which are control signals to the air heater. Then, the air heater works to maintain the temperature in the drying chamber to match the setpoint during the drying process or when the timer is on. The air heater will turn off when the humidity has reached dry conditions and the drying time has been over. Based on the testing results, the control system prototype is able to work automatically, and the drying process can maintain the quality of the clothes. In addition, saving electrical energy is also possible with the use of the automatic controller

A Modular and Mobile Product Design Approach for Feed Processor

This study aims to produce a modular feed processor design. Feed processing, flexibility, and mobility are taking into account in the design. The modular and integrated product design provides advantages such as (1) easy way of making and modifying the product, (2) feed processing can be done anywhere (3) equipment has mobility capabilities. The Modular Quality Function Deployment (QFD) method is applied to identify modules associated with the customer needs of the product. A survey about customer expectation and satisfaction was conducted in order to evaluate the gap of both. The highest value of the gap between customer expectation and satisfaction of products indicates that the customer needs are the focus of the problems. The most important customer needs are considered in the modification and improvement of design. These are (1) easy to use, (2) clean, (3) durable, (4) wide, (5) mobility capability, (6) safe, (7) strong, and (8) easy access

EM-IOT: IoT-Based Battery Monitoring System and Location Tracking on Electric Vehicles

As the community increasingly embraces electric vehicles over time, there is a growing necessity for electric vehicle users to determine the real-time status of their batteries and their locations. This enables them to estimate when and where their electric vehicle batteries will need to be recharged. The battery condition can be used to estimate the remaining distance that the electric vehicle can travel while monitoring and observing the location of the electric vehicle is required for security and can also be used as a suggestion for electric vehicle users to carry out charging by adding information on the location of the nearest charging station. The EM-IOT system is designed to be accessible via an Android smartphone with an easy-to-understand and attractive user interface. The wireless system is designed with the ES12E module and the Thingspeak platform. Testing is done to ensure the system can work properly. The test results of battery monitoring and location tracking on the EM-IOT application have been able to display data with an average error not exceeding 5%. The data on the application is updated every 15 seconds. The EM-IOT system can function properly to monitor battery voltage, battery percentage, remaining distance, and the current location of the system vehicle

Perancangan Line Maze Solving Robot dengan Algoritma Short Path Finder

Kemajuan teknologi membuat perkembangan di berbagai bidang. Kemajuan di bidang robotika adalah berkembangnya berbagai jenis robot. Salah satu jenis robot adalah line maze solving robot yang berfungsi untuk menemukan jalur terpendek labirin. Bagaimana menemukan jalur terpendek merupakan permasalahan dalam labirin. Permasalahan ini diselesaikan menggunakan Algoritma Short Path Finder. Algoritma ini terdiri atas tiga mode yaitu mode search, mode short path dan mode return and path. Mode search berfungsi menemukan finish, mode short path untuk menemukan lintasan terpendek dan mode return and path untuk kembali ke start dengan jalur terpendek. Sensor yang digunakan robot adalah sensor garis, yang berfungsi mendeteksi jalur yang dilalui robot. Sensor garis merupakan masukan untuk pengolah data. Pengolah data adalah Mikrokontroler ATmega32. Bagian keluaran dan penggerak robot adalah driver motor tipe H-bridge dan motor DC. Berdasarkan hasil percobaan, sensor garis mudah terpengaruh cahaya luar. Oleh karena itu, peredam cahaya perlu diberikan di bagian samping sensor garis untuk mengurangi cahaya luar. Robot mengalami kesalahan pembacaan saat kondisi lepas sensor garis depan karena robot tidak dapat meluruskan posisinya terhadap lintasan. Algoritma Short Path Finder dapat diterapkan pada jenis lintasan bertipe maju dan belum dapat diterapkan pada lintasan bertipe melingkar

Sistem kendali cerdas : Fuzzy Logic Controller (FLC), Jaringan syaraf Tiruan (JST), Algoritma Genetik (AG) dan Algoritma Particle Swarm Aptimization (PSO)

x, 214 hlm.; Ilus.; 23 cm

Sistem Kendali Cerdas

x + 214 hlm.; 1 jil. : 23 c

Sistem Kendali Cerdas: Fuzzy Logic (FLC), Jaringan Syaraf Tiruan (JST), Algoritma Genetik (AG), Algoritma Particle Swarm Aptitization (PSO)

x, 214 hlm.; 23 c

Sistem Kendali Cerdas

ix, 211 hlm.; 24 c

Sistem kendali cerdas : fuzzy logic controller (FLC), jaringan syaraf tiruan (JST), algoritma genetik (AG) dan algoritma particle swarm optimization (PSO)

ix, 211 p. ; 24 cm

Sistem Kendali Cerdas

23cm;214ha