Engineering Journal of Research and Development

DEVELOPMENT OF A SMALL ROBOTIC ARM CONTROLLED BY EDGE AI TO RECOGNIZE THE PATH FROM THE OBJECT TRACKING CAMERA

somchai tiacharoen, Somporn Tiacharoen — Thu, 29 Jan 2026 00:00:00 +0700

This article presents real-time object detection on an Edge AI device using a camera as input. A machine learning model was developed using the OpenCV and TensorFlow libraries to detect objects in an image and control a robotic arm to follow the object's movement. While the camera is tracking the object, the Edge AI device simultaneously memorizes the movement path, saving it as a CSV data file. This allows the robotic arm to be trained to repeat the same path using the saved CSV file. The project developed a program using the machine learning model on a Raspberry Pi, which created a robotic arm with stepper motors and electronic motion drivers. A program was developed on an Arduino Uno board to control the robotic arm, receiving commands from the Raspberry Pi via the serial port. Experimental results indicate that the robotic arm successfully achieves real-time object tracking at an average speed of 6 centimeters per second. The robotic arm can memorize the movement path and repeat the movement with an average error of 0.5 centimeters. In the future, real-time image recognition technology can be applied to other applications such as smart agriculture and smart factories.

OPTIMIZATION OF REBAR CUTTING PLANS USING MULTIPLE STOCK LENGTHS AND INTEGER LINEAR PROGRAMMING: A CASE STUDY OF A WASTEWATER TREATMENT PLANT

Thu, 29 Jan 2026 00:00:00 +0700

This research aims to develop and evaluate the efficiency of rebar cutting plans for wastewater treatment plant construction, employing Integer Linear Programming (ILP) to minimize scrap waste and overall costs. The study compares cutting plans for rebar sizes DB12, DB16, and DB25 mm, utilizing standard stock lengths of 10 meters, 12 meters, and a combination of both. Rebar requirements were derived from the structural design specifications of a wastewater treatment plant case study. The findings demonstrate that combining 10 meter and 12 meter stock lengths yields the highest efficiency across all rebar sizes. Notably, for DB25 rebar, this approach reduced scrap waste from 17.09 %, when using only 12 meter stock, to a mere 1.95 %, while increasing material utilization to 98.05 % and remaining robust under moderate increases in rebar demand. Furthermore, it achieved material cost savings of up to 15.44 % and reduced greenhouse gas emissions by 15.45 % compared to using 12 meter stock alone. These results underscore that meticulous cutting plan optimization, incorporating multiple stock lengths and ILP, is a pivotal strategy for waste reduction, cost efficiency, and promoting sustainability in the construction industry.

ASSESSMENT OF ORGANIZATIONAL CARBON FOOTPRINT AND STRATEGIES FOR REDUCING GREENHOUSE GAS EMISSIONS: A CASE STUDY OF AN ELECTRICAL APPLIANCE FACTORY

Thu, 29 Jan 2026 00:00:00 +0700

This research aims to quantify the greenhouse gas emissions in accordance with the guidelines of the Thailand Greenhouse Gas Management Organization (Public Organization) and to assess the energy consumption from organizational activities in 2024. Furthermore, the study proposes greenhouse gas mitigation projects based on the methodology of the Thailand Voluntary Emission Reduction Program (T-VER). The case study is conducted in an electrical appliance manufacturing factory. The result revealed that the total greenhouse gas emission was 20,199.56 tonCO₂ eq./year or 0.0079 tonCO₂ eq/unit, while the total energy consumption was 26,502,490.69 MJ, or 10.41 MJ/unit. The largest sources of greenhouse gas emissions are: 1) Using plastic resin in category 1 from scope 3, 2) Plastic injection molding process in category 10 from scope 3 and 3) Electricity consumptions from scope 2 were discovered at 8,683.34, 5,036.64 and 2,499.48 tonCO₂ eq/year, respectively. Therefore, the researcher proposes four potential projects to reduce greenhouse gas emissions, namely: 1) Recovery and recycling of plastic from plastic solid waste, 2) Weight reduction of plastic components in products, 3) Use of renewable energy from solar rooftop and 4) Energy efficiency improvement for lightings. All four projects can reduce energy consumption 5,535,169.20 MJ, corresponding to 8.23 MJ/unit, and decrease greenhouse gas emissions 1,766.70 tonCO₂ eq/year, corresponding to 0.0072 tonCO₂ eq/unit.