Journal of Engineering and Innovation

Effects of electrodes configurated vertically on dewatering soft Bangkok clay using electrokinetic

Somjai Yubonchit, Avirut Chinkulkijniwat, Mantana Julvorawong — Sat, 21 Mar 2026 00:00:00 +0700

This research conducted a series of experiments to evaluate the effectiveness of electrokinetic techniques for water drainage and settlement in soft clay under two electrode configurations: (1) anode at the top and cathode at the bottom (1AT), and (2) anode at the bottom and cathode at the top (1AB). Results from this study show that the 1AB configuration produced greater settlement (27.08 mm, approximately 27% of soil thickness) than the 1AT configuration (21.28 mm, approximately 21%). This is attributed to the combined effects of electrophoresis and gravity, which accelerate settlement when the anode is placed at the bottom. In contrast, the 1AT configuration caused internal cracking due to upward particle movement induced by electrophoresis, opposing settlement. Stiffening of the upper soil layer further reduced the settlement rate. This study also confirms that soil dewatering is governed by electro-osmosis process rather than effect of temperature. Reduction of water content during the experiment affects the efficiency of electrokinetic technique, including electric current and electrical resistance. Therefore, electrokinetic techniques are more suitable for short-term applications, as they can rapidly enhance drainage and settlement during the initial stage, after which the process slows and stabilizes.

Development of an integrated material ordering model using time-series forecasting and EOQ: a case study of a construction company

Chalermchat Theeraviriya, Thananya Yokaew — Sat, 21 Mar 2026 00:00:00 +0700

The objective of this research was to develop an integrated material ordering model by combining time-series forecasting with the Economic Order Quantity (EOQ) model for a construction company. This study analyzed 40 construction materials selected based on the continuity of consumption records and value significance. The researchers applied an ABC-XYZ matrix to classify materials according to their value levels and demand volatility. Subsequently, three time-series forecasting techniques—Moving Average, Simple Exponential Smoothing, and Trend Analysis—were evaluated. The criteria for selecting the best-fit forecasting model were based on the minimum error metrics, including MAPE, MAD, and MSD. The results demonstrated that the developed integrated model significantly reduced total inventory costs compared to the previous experience-based policy. Furthermore, sensitivity analysis of holding costs, ranging from 10% to 40%, confirmed the robustness of the proposed model under fluctuating economic factors. This approach provides a practical framework for construction firms to enhance inventory management efficiency amidst demand uncertainty.

Compressive strength and thermal conductivity of concrete containing biochar and expanded clay aggregate

Sat, 21 Mar 2026 00:00:00 +0700

This paper investigates the compressive strength and thermal conductivity of concrete containing biochar and expanded clay aggregate. Hydraulic cement type GU was used as the main binder. Biochar produced from pyrolyzed rice husks was used to partially replace hydraulic cement at 1% and 3% by weight of total binder. Expanded clay aggregate was used to replace natural coarse aggregate at 25 and 50% by volume of coarse aggregate. The water-to-binder ratio of all concrete mixtures was kept at a constant value of 0.50. The experimental results found that biochar-based concrete had higher compressive strength than control concrete and concrete containing expanded clay aggregate. Concrete with 1% biochar by weight of total binder exhibited higher compressive strength than concrete with 3% biochar by weight of total binder. Meanwhile, the concrete using expanded clay aggregate demonstrated less thermal conductivity than the control concrete and the concrete incorporating biochar. The thermal conductivity decreased as the percentage of expanded clay aggregate increased. Furthermore, concrete containing biochar combined with expanded clay aggregate possessed a lower thermal conductivity than concrete having only expanded clay aggregate. This is because biochar and expanded clay aggregate were highly porous materials. As a result, it could reduce heat transfer inside the concrete.

Preventive maintenance planning: case study of air conditioner testing room

adisak nowneow, Banhan Lila, Jakrawarn Kunadilok — Sat, 21 Mar 2026 00:00:00 +0700

This research presents an approach to applying preventive maintenance principles to mitigate the issue of unexpected test interruptions in an air conditioning test chamber, primarily caused by steam system malfunctions. These malfunctions occurred with an average frequency of 0.67 times per month, resulting in a testing room downtime of 8 days per incident. The study began with identifying the root causes through maintenance history and in-depth analysis using Why-Why Analysis. It was determined that the steam system malfunctions were due to improper steam bypass operations of operators and the inappropriate replacement scheduling of critical components of the steam system. To fix these issues, the study implemented new procedures and standards for steam system bypass operations and established a preventive maintenance plan. This plan included replacing the Reduce Valve and Motor Valve after 920 days and 950 days of usage, respectively, based on survival function analysis using the Weibull distribution. Following the implementation of these corrective measures, there were no further unexpected test interruptions due to steam system failures over a monitoring period of reliability function with the Weibull distribution model. Consequently, this led to a 100% reduction in unexpected test interruptions in an air conditioning test chamber. This study concludes that the corrective actions, including the establishment of new operational standards and equipment replacement schedules, successfully achieved the objectives and can be applied to similar issues in other contexts.

Development of an artificial intelligence model for classifying short-duration machine stoppages: A case study of a beverage manufacturing plant

Kanyarat Worachatphaisan, Noppakun Sangkhiew — Sat, 21 Mar 2026 00:00:00 +0700

In the beverage packaging industry, even short-duration machine interruptions can significantly affect overall production performance (Overall Equipment Effectiveness: OEE). This study presents the development of an artificial intelligence model using a Multilayer Perceptron (MLP) Artificial Neural Network to classify short-duration machine stoppage (Minor Stoppage) events on a can-filling line. The model was evaluated using 5-fold walk-forward time-series cross-validation to ensure robust performance under sequential data conditions. The evaluation results indicate that the proposed ANN model achieved a high overall performance, with a mean macro-F1 score of 92.00% ( = 8.40%) and a mean Mi-F1 score of 84.48% ( = 15.97%). The model was also able to systematically categorize stoppage events, revealing that most cases were classified as short, non-repetitive interruptions (General-Minor Stoppage: GM), accounting for 62.83% of all events. Meanwhile, severe short stoppages (Major-Minor Stoppage: Mi) comprised only 6.67% but were identified as a major source of production efficiency losses. Traditional monitoring methods could not clearly distinguish between routine and severe short-duration stoppages. These findings demonstrate that the developed ANN model has strong potential to serve as an intelligent tool for automatic monitoring and analysis of machine stoppage events. It can detect early signs of abnormality and alert operators to take corrective action before serious failures occur. Consequently, the system enables proactive maintenance planning, reduces unplanned downtime, and enhances OEE in a tangible way, and ultimately improves the long-term efficiency and competitiveness of beverage manufacturing plants.

A A study of parameter affecting cookie model by using a 3D printing technology

Paphakorn Pitayachaval, Thanakharn Baothong, Nattamon Pilaiwong — Sat, 21 Mar 2026 00:00:00 +0700

The objective of this research was to study the parameters affecting the injection molding of cookies to the desired size. The initial variables in the study were the nozzle travel speed at 200 mm/min and 300 mm/min, the height between the nozzle and the workpiece base at a height of 5.5 mm and 6.5 mm., and the amount of butter, which was reduced by 40 g and increased by 40 g from the original recipe. The dependent variable was the width of the cookie line in 3 positions: head, middle and tail. The control variable was the size of the nozzle at 4 mm in diameter. From the experimental results, it was found that the factors that significantly influenced the width of the cookie dough were the speed of the nozzle movement, the amount of butter in the cookie recipe, and the co-influence between the amount of butter in the cookie recipe and the height between the nozzle and the base. When analyzing the consistency of the cookie patties, it was found that the amount of butter in the recipe was reduced by 40 g or 20% from the original recipe, the nozzle movement speed was at 300 mm/min., and the height between the nozzle and the workpiece base was 5.5 mm. This will make the width of the cookie line at the head, middle and tail positions to be the most similar.

Fire hazards of electric vehicles in semi-enclosed and enclosed environments: A review

Amonwan choodonwai, Nannapasorn Inyim — Sat, 21 Mar 2026 00:00:00 +0700

Electric vehicle (EV) adoption has been growing continuously; however, fire hazards remain a significant challenge, especially in semi-enclosed and fully enclosed environments such as underground parking lots and tunnels. The objective of this literature review is to understand EV fire behavior in semi-enclosed and enclosed environments. Eighteen studies published between 2015 and 2025 were reviewed to examine fire behavior, thermal runaway, heat release rate (HRR), smoke dispersion, and toxic gas emissions. The review also considers health hazards, fire suppression methods, and ventilation strategies. EV fire behavior differs significantly from internal combustion engine vehicles (ICEVs), with maximum HRR reaching 6–10 MW within minutes and up to 52 MW in electric buses. Hydrogen fluoride (HF) concentrations can reach up to 488 ppm, exceeding the acute exposure guideline AEGL-2 by a factor of 40, which drastically reduces tenability time by up to 47%, especially in areas with limited ventilation. Fire suppression for EVs requires significantly more resources-around 6,000 liters of water or chemical agents compared to ICEV fires and poses a risk of re-ignition. The findings of this literature review can serve as a guideline for further studies involving experiments or simulations of electric vehicle fires in semi-enclosed and enclosed spaces. It can also be used to support legislation and establish safety standards related to EV fire incidents in parking structures, to align with government policies promoting electric vehicle adoption and accommodate future growth in EV usage.