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All Journal Jurnal Teknologi Kedirgantaraan (JTK) MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering
Purnama, Eko
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Aerospace Engineering Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Transportation

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Implementation of Finite State Automata for 6-Axis Robot in the Screwing Process Risfendra, Risfendra; Nursalam, Rapis; Purnama, Eko; Defri, Defri
MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering Vol 7 No 2 (2025): Motivection : Journal of Mechanical, Electrical and Industrial Engineering
Publisher : Indonesian Mechanical Electrical and Industrial Research Society (IMEIRS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46574/motivection.v7i2.445

Abstract

The screwing process is one of the important stages in the assembly of industrial products that requires high precision and time efficiency. This study implements Finite State Automata using Nondeterministic Finite Automata with the Mealy Machine model. The implementation of Finite State Automata on a 6-axis robot in the screwing process allows for better control, because each step in the process can be analyzed and programmed clearly. The system is controlled by a programmable logic controller that integrates a 6-axis robot, human machine interface, screwdriver, sensors, and pneumatic actuators. The screwing process is carried out using an automatic screwdriver, with the robot's movement following a logical sequence based on the Mealy Machine model state diagram. Each state represents the robot's operational steps, from taking tools, screws, to the screwing process. The study focuses on designing a system to move the robot according to the state diagram that activates the output based on the state transition to the input. The results show that the implementation of Finite State Automata is able to complete the screwing process consistently and repeatedly. This system also considers safe points to avoid collisions, thus supporting safety in the screwing process. The application of Finite State Automata on 6-axis robots is expected to provide convenience for users in understanding robot control in the screwing process and can be implemented according to industrial needs.
Enter metadata PENGEMBANGAN SKRIP BERBASIS AI UNTUK DJI TELLO EDU DRONE MENGGUNAKAN PLATFORM CHATGPT O1 DAN COPILOT Purnama, Eko; Edi Sofyan; Dwi Widyanto
Jurnal Teknologi Kedirgantaraan Vol 11 No 1 (2026): Jurnal Teknologi Kedirgantaraan (In Press)
Publisher : FTK UNSURYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35894/jtk.v11i1.263

Abstract

The rapid advancement of drone technology, particularly in its integration with artificial intelligence (AI), has had a significant impact on various sectors, one of which is the field of aircraft inspection and maintenance. This study aims to develop an AI-based script using the ChatGPT O1 and Microsoft Copilot platforms to control the DJI Tello EDU drone in automatically detecting cracks on aircraft bodies. The research was conducted through several stages, including collecting visual data via drone flights, processing and training the model using machine learning, developing the script with AI assistance, simulating on MATLAB Simulink, and finally implementing and testing directly on the physical drone. The results of the study indicate that ChatGPT O1 is capable of generating scripts that are more responsive, comprehensive, and easier to understand compared to Copilot, especially in interpreting natural language prompts. The generated scripts proved effective in both simulations and real-world flight tests, although there were limitations in the drone's sensors that affected the accuracy of altitude and distance measurements. The conclusion of this research is that AI plays a significant role in simplifying drone programming processes and enhancing work efficiency. This study contributes to the development of AI-based autonomous drone technology and opens up opportunities for broader and more efficient applications in other infrastructure inspection fields.
Co-Authors Ahmad Badawi Saluy Defri, Defri Dwi Widyanto Edi Sofyan Nursalam, Rapis Risfendra, Risfendra Sugiyono Sugiyono