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Process modelling of friction stir welding of AA1100 aluminum alloy using a hexagon-shaped tool to optimize the process parameters Indrawanto Indrawanto
Prosiding SNTTM Vol 23 No 1 (2025): SNTTM XXIII October 2025
Publisher : BKS-TM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71452/pkq5rh02

Abstract

This paper presents process modeling of Friction Stir Welding (FSW) to optimize mechanical properties on the friction stir welded material of 1100 aluminum alloy. The model variables are tool rotational speed, translational feed rate, and axial force. The model is developed using a statistical engineering method known as Response Surface Methodology (RSM). The analysis of variance techniques has been used to illustrate the adequacy of the model. The effect of the welding parameters on mechanical properties, macro-structure, and micro-structure of friction stir welded joints have been analyzed in detail and the predicted trends are discussed. The developed mathematical model can be effectively used to predict the tensile strength of friction stir welded AA1100 aluminum alloy joints at the 95% confidence level.
Design and manufacture of a self-balancing system for two-wheeled vehicle models using a reaction wheel Indrawanto Indrawanto; Yuzar Arigi; Vani Virdyawan
International Journal of Electrical and Computer Engineering (IJECE) Vol 16, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v16i4.pp1853-1866

Abstract

Motorbikes are a popular mode of transportation in Indonesia and are agile in maneuvering on roads with heavy traffic. The increasing use of motorbikes has triggered many accidents. This paper discusses the design, manufacture, and control of a self-balancing system for a two-wheeled vehicle model to improve driving safety. The self-balancing system designed uses a reaction wheel. The system architecture consists of a microcontroller board, a DC motor, a gyroscope, a reaction wheel, and a two-wheel vehicle model. The dimensions of the reaction wheel are optimized between the mass and the moment of inertia to make it possible to self-balance the model from a certain initial angle. The controller is designed based on the state space model with a feedback linear-quadratic regulator controller. The matrix weighting values are selected using Bryson’s rules method. Experimental results show that the self-balancing system can work well for the two-wheel vehicle model.