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All Journal JPTK: Jurnal Pendidikan Teknologi dan Kejuruan Jurnal ABDINUS : Jurnal Pengabdian Nusantara Technologic TECHNOLOGIC
Syahril Ardi
Program Studi Teknik Produksi & Proses Manufaktur, Politeknik Manufaktur Astra
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Industrial & Manufacturing Engineering Other

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DESIGN OF WIRELESS CONTROL SYSTEMS AND NAVIGATION SYSTEMS ON THE AUTONOMOUS VEHICLES AT HEAVY EQUIPMENT COMPANY Suprapto, Heru; Nur Fauzi, Iqbal; Ardi, Syahril; Ponco, Agus
Technologic Vol 13 No 2 (2022): Thirteenth Volume of the Technology Series
Publisher : LPPM Politeknik Astra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52453/t.v13i2.414

Abstract

In this paper, the research development of the Autonomous Vehicle Prototype project has been carried out. The research was carried out on a golf cart (buggy) by designing wireless control and navigation systems. Designing a wireless control system on a golf cart aims to control the drive systems, steer systems, and brake systems. Furthermore, this system can be controlled electrically wirelessly through a Joystick Radio Controller, so that the golf cart can move forward, reverse, turn right and turn left. The navigation system aims to enable golf carts to track from point A to point B by using several sensors, including the GPS (Global Positioning System) sensor. GPS is used for tracking position on the golf cart, IMU (Inertia Measurement Unit) as a measure of the golf cart heading degree, LIDAR (Light Distance and Ranging) is used to detect distance and avoid obstacles, and Hall Effect Sensor as a speed sensor. The integration of the sensor and actuator systems is carried out using an Arduino Mega 2560 type microcontroller. Next, the movement from point A to point B is carried out autonomously. The final result of this research is that the GPS sensor can detect a track distance of 68.8 m with a minimum accuracy of 3 m and a resolution of 1 m. The IMU sensor can detect headings of 90o with 2o accuracy and 1o resolution. The LIDAR sensor can detect obstacles at a distance of 0 m – 4 m, and the Hall Effect sensor can detect the RPM of the car at a speed of 5 km/h. Golf cart control can be done wirelessly and automatically on the navigation system from point A to point B by avoiding obstacles.
OPTIMISATION OF PRODUCT MARKING ACCURACY THROUGH THE IMPLEMENTATION OF A QR CODE SCANNER SYSTEM BASED ON RASPBERRY PI SBC IN THE AUTOMOTIVE MANUFACTURING INDUSTRY Ardi, Syahril; Suprapto, Heru; Fadhilah Irfan, Mochamad Nur; Hidayat, M
Technologic Vol 16 No 1 (2025): TECHNOLOGIC
Publisher : LPPM Politeknik Astra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52453/t.v16i1.473

Abstract

In automotive manufacturing, accurate product marking is essential for traceability and safety. One interior component requires laser marking of the label "AIR BAG" and the attachment of a QR code. However, production data revealed recurring defects due to missing QR code labels or skipped marking processes, which were caused by the lack of a verification system. This study aims to design and implement an automated QR code verification system using a Raspberry Pi 4, a single-board computer (SBC) of this type. The novelty of this approach lies in its cost-effective integration of hardware and image processing software (OpenCV) to detect QR codes in real time. The system is designed to scan for a QR code before the laser marking process begins. If a QR code is detected, a signal is sent to the laser machine to proceed with marking. It ensures that each product is verified correctly and marked. The method involved prototyping, software development, hardware integration, and implementation on a real production line. Results showed a significant reduction in marking-related defects and an improvement in process reliability. This solution minimizes operator error, enhances production efficiency, and supports quality assurance. Future work will focus on integrating the system with PLC-based controls and exploring machine learning techniques to enhance detection accuracy and facilitate predictive maintenance.
Co-Authors Afianto, Afianto Afitro Adam Nugraha Agung Wibowo Apit Hidayat, Apit Aulia, Ananda BAYU WIBOWO, BAYU Eka Samsul Maarif Fadhilah Irfan, Mochamad Nur Febriansyah, Mohamad Bintang Febrika Tasiawati Hendrik . Heru Suprapto Hidayat, Dimas Widyasmoro Indra Setiawan M Hidayat Marolanzano, Paolo Ma’arif, Eka Samsul Muhammad Hidayat Muhammad, Rayaldi Mushlihuddin, Afif Ningsih, Nur Dewi Nur Fauzi, Iqbal Nurmaningtyas, Cicilia Fania Ponco, Agus Putri, Dwita Khaendy Rahardjo, Nugroho Budi Rahmandanu, Titis Sondha Riestiawan, Rian Tutut Rika Kusuma, Rika Rosyidi, Edwar Sangun, Irfandaresa Setyowati . Siamdani, Cokro Sirin Fairus Subagio, Djoko Sukmaningrum, Sekar Utami, Desitia Wicaksono, Andreadie