Thai Industrial Engineering Network Journal

The Study of Greenhouse Gas Emission from Transportation of Waste under Green Logistic Concept with The Study Case of Chulachomklao Royal Military Academy

2025-04-25T22:41:43+07:00

The study of Greenhouse gas emission from transportation of waste under green logistic concept with the study case of Chulachomklao Royal Military Academy aimed to observe the amount of Greenhouse gas emission from transportation of waste of Chulachomklao Royal Military Academy, and to compare Greenhouse gas emission from waste trucks that use general diesel engine and ones that are electric. According to the data collected during September 1st – November 30th , 2024, it was found that when using HINO diesel-engine trucks model FG8JJ1A-JJT, which is a compact garbage truck, as vehicles for transportation with 10 tons loading, running 4 routes that equals 12,174.24 km/year, 27,612 liters of diesel fuel was used created 74,516.50 kgCO₂eq/year of Greenhouse gas emission. Therefore, the author proposed the guidelines for reducing the emissions by using electric vehicles. It will help decrease 60 percent of greenhouse gas emissions which equals 44,709.9 kgCO₂eq/year. And when calculating marginal cost, it was found that net costs were reduced by 4.97 baht/ 1 kgCO₂eq. This indicates that the project can create benefits by reducing the emissions and enhance the significance of changes and improvements of using different types of vehicles that also environment-friendly and economic benefits. It can be used as a case study for improvement in other areas, for sustainability and environment in the future. And it is a response to the measures driving the reduction of greenhouse gas emissions under the Thailand 4.0 policy.

Assessing the Carbon Footprint of Product: A Case Study on the Plastic Bucket Production Process

2025-05-01T11:33:38+07:00

This study aims to evaluate the carbon footprint of Plastic Bucket production. The Life Cycle Assessment (LCA) method was applied using a Cradle-to-Gate framework in a Business-to-Business (B2B) system, encompassing processes from raw material acquisition to manufacturing. The findings revealed that the average greenhouse gas emissions per bucket amounted to 0.328 kgCO_₂e, with manufacturing identified as the major contributor at 54.17%, followed by raw material acquisition at 45.83%. These results provide actionable insights for reducing environmental impact through strategies such as increasing the use of recycled materials and improving energy efficiency in production processes.

Energy Consumption Forecasting Using Machine Learning and IoT System

2025-04-29T19:59:48+07:00

The objective of this research is to propose the development of a forecasting model for the electricity consumption of air conditioning systems in server rooms using machine learning and Internet of Things (IoT) systems. The study collects data on external temperature, humidity, and air conditioning power consumption through IoT technology. The methodology consists of three main parts: (1) data collection of temperature, humidity, and electricity consumption using IoT systems; (2) development of an electricity consumption forecasting model; and (3) performance evaluation of the forecasting methods. Four forecasting methods are selected for comparison: Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), Artificial Neural Network (ANN), and Autoregressive Integrated Moving Average (ARIMA). The performance is assessed based upon Mean Square Error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). The results indicate that the IoT system can collect data accurately and efficiently. Among the forecasting methods, LSTM demonstrated the highest accuracy in terms of the lowest MSE and RMSE values, while ARIMA exhibited the lowest MAPE. Machine Learning enhances the accuracy of electricity consumption forecasting by efficiently learning patterns from large datasets collected through IoT systems. These findings suggest that LSTM is the most appropriate model for forecasting electricity consumption. However, the choice of a forecasting model depends on the specific problem and practical requirements. This forecasting model enables users to estimate energy consumption in advance and manage energy more effectively.

Enhancing Cold Chain Logistics: Key Factors Influencing Temperature Retention in Portable Cold Storage Boxes

2025-04-25T12:30:43+07:00

Cold chain logistics play a crucial role in transporting temperature-sensitive goods such as vaccines, pharmaceuticals, and fresh food products. One of the key components in this process is portable cold storage boxes, which help maintain stable temperatures throughout transportation. This research aims to investigate the factors influencing temperature retention efficiency in portable cold storage boxes and develop a predictive model for temperature retention duration using Design of Experiments (DOE). The experiment was conducted using Factorial Design and Response Surface Methodology (RSM) to identify significant factors affecting temperature retention time. The results indicate that the type of cold storage box (B-Box), the quantity and type of Phase Change Materials (PCMs), and the structure of the top wall insulation are the most critical factors influencing cooling performance. Additionally, findings show that optimizing PCM placement and quantity can significantly extend temperature retention time. From this study, a predictive model was developed to forecast the duration of temperature retention in portable cold storage boxes. This model can be applied to improve cold chain logistics efficiency, minimize product losses, and reduce operational costs in temperature-controlled transportation.

Prediction of Optimal Ammonia Dosage for Fresh Latex Preservation in Skim Rubber Production Using Linear Regression

2025-04-23T15:23:22+07:00

The most critical process in skim rubber production is rubber coagulation, where sulfuric acid is currently used as a coagulant in manufacturing plants. The amount of sulfuric acid required is directly related to the ammonia content in fresh latex. Figuring out the right amount of ammonia is therefore a key part of increasing production efficiency and lowering costs. This study aims to develop a Linear Regression (LR) model to predict the appropriate amount of ammonia to be added to fresh latex before it enters the skim rubber production process. The input variables included storage duration of fresh latex (Days), initial ammonia content in fresh latex (NH3 Init), and initial volatile fatty acid content (VFA Init), all of which are key factors influencing the required ammonia dosage. Data analysis was conducted using the WEKA software. The model achieved a coefficient of determination (R2) of 0.980, Mean Absolute Error (MAE) of 5.170, and Root Mean Squared Error (RMSE) of 5.751, indicating a satisfactory level of accuracy for practical applications. Additionally, the developed model reduced ammonia usage by 9% compared to the factory's previous method. The findings can serve as a guideline for optimizing the skim rubber production process and reducing chemical costs.

Development of Surface Properties of Nickel-Based Alloy 617 through Aluminum-Pack Cementation

2025-04-23T09:16:51+07:00

This research explores the enhancement of nickel-based alloy 617 using aluminum pack cementation via direct diffusion. The coating powder, composed of aluminum, alumina, and ammonium chloride (22.5:120:7.5 grams by weight), was applied at 800°C for 1, 2.25, 4, and 6.25 hours, followed by homogenization at 1,150°C for 30 minutes. Oxidation resistance testing at 950°C for 64 hours, analyzed via X-Ray diffraction, scanning electron microscopy, and energy-dispersive spectroscopy, showed that coating duration directly affects thickness, with 6.25-hour coatings being the thickest. However, the 2.25-hour coating exhibited the best oxidation resistance, showing the lowest weight gain, while the 6.25-hour coating led to increased NiO formation and internal stress, reducing oxidation protection. Microstructural analysis confirmed NiAl as the main phase in the 2.25-hour coating, with Al₂O₃ providing better oxidation resistance compared to Cr₂O₃. Considering both performance and cost-effectiveness, the 2.25-hour coating is the most optimal, balancing oxidation resistance, feasibility, and production cost.

Predicting Compressive Strength of Hybrid Cement Concrete Using Multiple Linear Regression Sustainable Construction Application

2025-04-22T21:28:58+07:00

This study investigates the compressive strength of concrete using hybrid cement as a binding material, which offers the advantages of lower energy consumption and reduced carbon dioxide emissions during production. The study examines concrete mixtures using Portland and hybrid cement under varying curing times. The primary objective is to develop a predictive model for concrete compressive strength using multiple linear regression analysis and to identify factors influencing compressive strength by comparing the predicted results with laboratory test data. The findings reveal that concrete using hybrid cement shows compressive strength trends similar to Portland cement concrete. Hybrid cement concrete exhibits higher compressive strength with increased curing time than Portland cement concrete. Furthermore, statistical analysis indicates that the predictive model can accurately forecast compressive strength with 92.00% accuracy, with curing duration and water-to-cement ratio identified as the most significant factors. This study provides a valuable reference for developing sustainable concrete and has applications in building construction and infrastructure development.

Multimodal Transportation for Tourism in the Indochina Region

2025-04-25T18:40:13+07:00

This study aims to design suitable multimodal transport routes connecting three corridors: Thailand–Laos–Vietnam, Thailand–Laos–Cambodia, and Thailand–Cambodia–Vietnam, in the Indochina region. Ubon Ratchathani Province serves as the central hub, linking transportation routes between Thailand, Laos, Vietnam, and Cambodia. Currently, transportation in the region continues to face obstacles, including modal discontinuity, high costs, and a lack of efficiently connected infrastructure, which impact cross-border travel and trade. This research applies Data Envelopment Analysis (DEA) to analyze the efficiency of transport routes, considering factors such as distance, cost, availability of facilities, and user-based performance scores. The results indicate that integrating appropriate transport modes can significantly reduce logistics costs and improve the efficiency of the regional transport system.

Influence of Shoes Type and Heigh which Using with Removable Cast Walker

2025-04-25T23:51:00+07:00

Reducing Preform Material Loss through Process Improvement in Small-Sized Carbonated Beverage Bottling

2025-04-04T11:48:55+07:00

This research aimed to reduce preform material loss in a small-sized carbonated beverage bottling process. The study was conducted in five steps: (1) studying the production process, (2) collecting material loss data, (3) prioritizing potential causes, (4) identifying root causes, and (5) implementing process improvements. Three critical points with the highest material loss were identified: the blowing machine, the liquid level detection unit, and the preform dumping area. To analyze the root causes, the Why-Why analysis technique was applied together with a fishbone diagram to systematically categorize contributing factors. The improvement actions included applying the Centerline (CL) technique to standardize cap conveyor settings and the Cleaning, Inspection, and Lubrication (CIL) technique to ensure machine condition reliability. Standard operating procedures and inspection checklists were also developed.

The results showed that the material loss rate across the three points decreased from 8.26% to 1.16%, a reduction of 7.10%. This resulted in a cost reduction from approximately 6.46 million THB per year to 1.43 million THB per year, or 77.91%. Moreover, the proposed improvement approach can be extended to other production lines using similar machinery.

Design and Development the Drinking Water Filling Machine with Low-Cost Automation for Community Enterprises

2025-05-02T15:47:18+07:00

This research aims to design and develop a prototype low-cost automatic water filling machine for community enterprises. According to a survey of the needs of 37 community enterprises, it was found that community enterprises need an affordable automatic water production and filling system. Automation can be easy to use and community enterprises can maintain it manually. Therefore, the design of low-cost automation has the idea of choosing materials that can be purchased in Thailand and the materials meet the requirements of food and pharmaceutical organizations such as stainless steel 304, drinking water filling heads are machined from stainless steel pipe, motor and valves etc. Water Filling Machine uses stainless steel lathe pipe as total filling head, 3 heads connecting to the water suction pump system. The system controls the filling head to move up and down according to the rhythm of the moving belt and automatically turns on and off the pneumatic system according to the number of fillings in each cycle. The downward movement of the filling head to the position of the bottle mouth will automatically turn on the suction pump for filling and will turn off the pump when the time set in the system is set according to the size of the bottle. Then the pneumatic system will open the door and the belt starts to work to convey the bottles out and bottles in at the same time, so that it can be produced continuously and does not use workers in the water filling process. The results showed that the drinking water filling system with control system has 3 filling heads. It takes about 6 seconds / 3 bottles to fill the water into a 500 ml bottle. The drinking water filling system can adjust the filling speed in the range of 3 seconds to 7 seconds per bottle, the filling time will vary according to the size of the bottle and is equipped with a photo sensor that can detect transparent objects to count the number of bottles that have been filled and send data to the production record system. The result of the use of materials made in Thailand and various equipment according to the appropriateness of the selected technology level, the cost of packing machines and equipment is about 30% lower than the market price, increased production capacity and easy maintenance. Therefore, this research meets the needs of community enterprises and can help increase of the production capacity of community enterprises.

Improving Household Waste Management Efficiency with Automatic Waste Sorting Bin Systems

2025-05-26T14:18:58+07:00

This research aims to design and develop an automatic waste sorting bin system to help increase the efficiency of waste management, consisting of recycling and wet waste bins. The recycling bin is designed to automatically separate glass bottles, plastic bottles and cans using electronic sensors and a tilted surface. The wet bin has a blade system, powered by an electric motor, that introduces air into the bin, along with an automatic lid-opening mechanism to reduce contact and prevent disease transmission. The entire system is powered by solar energy, promoting energy sustainability. The performance testing involved 30 different recyclable items. The results showed that plastic bottles and aluminum cans were successfully sorted with 100% accuracy, while glass bottles were sorted with 66% accuracy. It was observed that the system could accurately separate glass bottles weighing more than 160 grams. The wet waste bin successfully converted food waste into organic matter suitable for composting within 7 days. The total initial investment for the prototype system was 14,180 THB. Based on an estimated monthly revenue of 141 THB from selling separated recyclables, the payback period is approximately 8.38 years. This does not include indirect benefits such as reducing manual labor for waste sorting and promoting the use of clean energy within households. The results indicate that the system significantly enhances waste sorting efficiency and has strong potential for further implementation at the community or organizational level to support more effective waste management in the future.

Application of ECRS Principles Combined with 5W1H Technique and Automatic Feeder System Design to Increase Production Rate of Profile F1 Sanding Machine

2025-12-15T14:12:15+07:00

This study aims to enhance production efficiency and eliminate bottlenecks in the Profile F1 sanding line production process. Preliminary analysis revealed that production rates were not meeting the targets due to the discontinuity of manual workpiece feeding, resulting in gaps between workpieces, machine idle time, and employee fatigue. A root cause analysis using Why-Why Analysis confirmed that reliance on manual labor for feeding without auxiliary equipment was the main cause of the problem To address this issue, industrial engineering methodologies were applied, specifically using the ECRS (Eliminate, Combine, Rearrange, Simplify) principles combined with the 5W1H technique to analyze and design an Automatic Feeder System to replace the manual handling process. The implementation of this system significantly improved the continuity of the process. Prior to the improvement, the average production rate was 1,084.0 pieces per hour; after the installation of the automatic feeder, the production rate increased to 1,605.8 pieces per hour, resulting in a 49% increase in production. This outcome successfully achieved the project objectives and sustainably eliminated the production line bottleneck.

Improving the Efficiency of Raw Material Inventory Management in the Cosmetic Industry Using EOQ and ROP Concepts: A Case Study of an OEM Manufacturing Company

2025-10-20T10:58:15+07:00

This research aims to present the application of the Economic Order Quantity (EOQ) and Reorder Point (ROP) concepts to improve the raw material inventory management of a cosmetic Original Equipment Manufacturer (OEM) company, using a case study from a sample firm. Initial findings revealed that the company faced challenges with the shortage of key production raw materials, which impacted operational efficiency. An analysis of raw material withdrawal data from July to September 2024 showed a stock-out rate as high as 26.85% of the total 242 withdrawal transactions. To address this problem, the EOQ and ROP methods were implemented to determine the optimal order quantity and the appropriate point for placing a new order. The operational results following the implementation, observed during the period from January to March 2025, demonstrated that the company was able to fully supply the production department with raw materials in 100% of the total 283 withdrawals, with zero instances of material insufficiency. This study underscores the significance and effectiveness of applying EOQ and ROP in enhancing inventory management efficiency, mitigating raw material shortages, and supporting business operations in the highly competitive cosmetic industry.

Optimization of Nickel with Molybdenum Disulfide Powder Co-electrodeposition on 3D-printed ABS Part for Wear Resistance

2025-08-07T14:25:24+07:00

This study investigated the optimal conditions for improving the wear resistance of 3D-printed ABS parts through nickel electroplating with molybdenum disulfide (MoS₂) as a solid lubricant. The key parameters examined were the concentration of MoS₂ powder in the plating bath and the applied current density during co-electrodeposition. A Ball-on-Disc test was conducted to evaluate wear performance. Based on the results from a 2^k factorial design, current density was identified as the statistically significant factor influencing wear loss, whereas the MoS₂ powder concentration showed no significant effect. High current density during electrodeposition promoted the formation of large nodules in the Ni–MoS₂ coating, thereby enhancing the wear resistance of the plated surface against an alumina ball. The optimal condition for minimizing wear loss, as determined from Pin-on-Disc testing, was achieved with a current density of 10 A/dm².

Increasing the Efficiency of Inventory Management for Mixing Storage Tanks: A Case Study of a Stainless Steel Manufacturing Company

2025-08-15T11:49:34+07:00

This study aims to enhance inventory management efficiency in a made-to-order stainless steel tank manufacturer by focusing on critical components that frequently experience stockouts, namely air vents and manholes of various sizes. An initial assessment revealed low fill rates, which led to production interruptions and delivery delays. Root causes were identified using a fishbone diagram, and controllable gaps were addressed by establishing safety stock, reorder points (ROP), and a max–min inventory control policy. An Excel VBA-based inventory control tool was developed to automate stock-level calculations and generate replenishment alerts, while demand forecasting was incorporated to support procurement planning. The implementation results showed that the fill rate improved to 100% across all targeted items and the average procurement cycle time decreased by 45%.

Improving Data Recording Processes Using a Barcode System: A Case Study of an Antenna Manufacturing Company

2025-11-27T10:04:54+07:00

This study was conducted with the objective of reducing paper consumption in record-keeping and minimizing the production time of the VH80 antenna model within the case study company. An initial analysis of the current process indicated significant paper usage during data recording. To address this issue, a barcode system and a VBA-based program—both considered appropriate for the company's operational environment—were introduced to replace manual, paper-based documentation. The findings indicate that paper usage in the data recording process was reduced from 6,348 sheets to 3,864 sheets, reflecting a 39.13% reduction. Furthermore, the production time of the VH80 antenna model decreased from 150 minutes and 34 seconds to 144 minutes and 42 seconds.