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All Journal Proceeding of the Electrical Engineering Computer Science and Informatics JEEMECS (Journal of Electrical Engineering, Mechatronic and Computer Science) SENTIA 2016 Jurnal Intake : Jurnal Penelitian Ilmu Teknik dan Terapan Jurnal Tecnoscienza ALINIER: Journal of Artificial Intelligence & Applications SinarFe7 Journal FORTEI-JEERI Nucleus Journal
Rukslin
Universitas Darul ulum
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Other

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Optimasi Pemograman Sistem Pengendalian Mesin CNC Pengebor PCB Berdasar Metode Firefly Algorithm Hidayatul Nurohmah; Machrus Ali; Rukslin; Dwi Ajiatmo; M. Teguh Proyoga
ALINIER: Journal of Artificial Intelligence & Applications Vol. 3 No. 2 (2022): ALINIER Journal of Artificial Intelligence & Applications
Publisher : Program Studi Teknik Elektro S1 ITN Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/alinier.v3i2.5840

Abstract

Automatic circuits use several electronic components found on Printed Circuit boards ( PCB ), namely micro (small) sized boards. With more holes in the PCB, it is more time-consuming to drill them manually with human power. In addition, accuracy is required when the drill bit contacts the PCB board, which may cause drilling errors due to friction. This project aims to create an autonomous drill using a computer and BCNC software to move it live. DC stepper and spindle motors powered by a PID firefly-controlled motor drive this machine. Drilling is carried out using the BCNC program, the drilling process is carried out by entering codes in the form of codes that can later be read by the CNC. By changing the layout to what is known as a code, the coordinates of the holes that have been made in the layout can be found. PCB designing software is used for this procedure. With each of the ten experiments used to test the accuracy of the six axes, an error value of 1.2% was recorded. Kp = 54, Ki = 38, and Kd = 0.9 are constant values obtained from the PID implementation on DC stepper.
Optimasi Thermal Oil Heater Menggunakan ACO Sebagai Tunning PID Controller Machrus Ali; Mochamad Ali Fikri Haiqal; Rukslin; Dwi Ajiatmo
Nucleus Journal Vol. 2 No. 1 (2023): May
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/nucleus.v2i1.2101

Abstract

The furnace is a piece of equipment used to heat materials or change their shape. Process control has become increasingly important in industry, as a consequence of global competition. Year after year, furnaces have improved in both industrial processes and equipment. The tuning process plays a role in ensuring that the performance of a system meets operational objectives. Intelligent control based on Artificial Intelligence (AI) has been developed to improve conventional control so that the output voltage is always considered constant under changing loads. From the simulation results of this research, it was found that the PID-ACO controller model is the best model for using a PID control system. This design without control never reaches a steady state, with the undershot being quite small, the PID-ACO control system has the fastest settling time and steady-state response. Even though PID-ACO has a higher overshoot than PID-Auto, the undershoot is higher than PID-Auto. PID-ACO has lower overshoot and undershoots than PID-Auto
Co-Authors Agus Raikhani Agus Raikhani, Ahmad Fajar Rohmatullah Ardi Junianto Askan Askan Avi Maida W Budiman Budiman Cahyono, Iwan Cholil Hasyim Dhany Ristyanto Dwi Ajiatmo Dwi Hendra Kusuma Hidayatul Nurohmah Ira Kusumaningrum Kadaryono Kadaryono Kadaryono Kadaryono Kadaryono Luluk Masluchah M Agil Haikal M Ibrahim M. Teguh Proyoga Machrus Ali Mochamad Ali Fikri Haiqal Muhammad Fakhrurozi Muhlasin Muhlasin, Parwanti, Asnun Sunarti Sunarto Tri Siswanto