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Modeling Equivalent Circulating Density During Drilling Operations in the Gulf of Thailand
(2026-03-31)
Leerojanaprapa, Kanogkan
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Suttaloon, Sudarat
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Bhundarak, Komn
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Sirikasemsuk, Kittiwat
Equivalent Circulating Density (ECD) represents the total hydrostatic pressure generated by drilling fluid while in motion. This prevents the internal pressure within the well from exceeding the fracture resistance of the rock, which could lead to lost circulation and an inability to effectively control the wellbore pressure. This research aims to predict ECD in 6.125-inch production section in Gulf of Thailand field by using five machine learning algorithms were utilized, namely Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Networks (ANN), Gradient Boosting (GB), and Extreme Gradient Boosting (XGBoost). Various sensors from the Measure While Drilling (MWD), Logging While Drilling (LWD), and Pressure While Drilling (PWD) tools were used to collect raw data, totaling 38,863 records and 24 variables to predict the ECD value. The dataset was randomly split into 80% for training and validation and 20% for testing. The results indicate that the RF technique outperformed the other models in predicting ECD values, producing the lowest RMSE of 0.031. Therefore, the RF model is most suitable for further development and real-time application in predicting ECD values.
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Lactobacillus plantarum JCM 1149 Growth Enhancement by using Chlorella sp. KLSc61-pretreated Cells
(2025-06-01)
Khanrin, Lalita
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Boonyakorn, Phonwimon
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Wongsariya, Karn
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Kittiwongwattana, Chokchai
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Maneeruttanarungroj, Cherdsak
Dry microalgal biomass was previously tested as prebiotic to enhance the growth of probiotic bacteria. However, the drying process could be ineffective for scaling up probiotic production. This study aimed to investigate the use of fresh, pretreated microalgal biomass to promote the growth of Lactobacillus plantarum JCM 1149. Chlorella sp. KLSc61 cells were pretreated by three different methods: physical treatment with microwave radiation at power levels of 300, 500, and 700 W; chemical treatment with 0.1 M citric acid and 0.5 M sodium hydroxide; and biological treatment with cellulase enzyme. The 2.5% pretreated Chlorella cells were then added to L. plantarum JCM 1149 culture, and the growth was observed at 37 °C for 24 h of incubation. The results showed that, during the log phase (6-10 h), Chlorella cells pretreated with microwave radiation at 700 W were the most effective in promoting L. plantarum JCM 1149 growth, which was 1.4- and 1.5-fold of L. plantarum JCM 1149 without adding Chlorella and with untreated cells, respectively. Extension of the pretreatment time by microwave radiation at 700 W from up to 2 min increased the growth of L. plantarum JCM 1149 up to 1.8-fold of pretreatment time by microwave radiation at 700 W 1 min, compared to the control groups. Additionally, increasing the amount of Chlorella biomass up to 5% (w/v) extended the log phase of L. plantarum JCM 1149 and increased cell accumulation during the stationary phase. Unlike dry microalgal biomass, the simplicity of fresh, pretreated Chlorella biomass shown in this study may facilitate large-scale, commercial production of L. plantarum strains as probiotics.
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Analysis of Rear Differential Component Clustering in Transmission Systems Using Hierarchical Cluster Analysis with and without Procurement Strategy Matrix Variables
(2025-04-01)
Sombunsook, Saowalak
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Sirikasemsuk, Kittiwat
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Leerojanaprapa, Kanogkan
The automotive industry has faced significant challenges due to the large number of Tier 2 suppliers for Rear Differential components, with 17 suppliers providing 32 different parts. This situation has resulted in increased production costs and more complex supply chain management. This study aimed to analyze the clustering of Rear Differential components in transmission systems using Hierarchical Cluster Analysis, with the goal of supporting cost reduction in the automotive industry. Two clustering models were compared: Model 1, which excluded procurement strategy matrix variables (Special Requirements, Raw Material Grade, Raw Material Type, Manufacturing Process, Tier 2 Supplier Information, and Company Location), and Model 2, which incorporated an additional variable related to the Procurement Strategy Matrix. The decision criteria for determining the optimal number of clusters were based on four key factors: 1) Product design, 2) Characteristics, 3) Materials, and 4) Manufacturing. The clustering results for both models revealed the same optimal number of 13 clusters; however, the similarity matrix between the clusters differed. Furthermore, the number of members within each cluster varied. Based on the criteria for determining the optimal number of clusters, Model 2, which included the Procurement Strategy Matrix variable, demonstrated superior clustering efficiency compared to Model 1. Ultimately, this research identified 13 optimal clusters, reducing the number of Tier 2 suppliers from 17 to 13, representing a 23.53% reduction.
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Work posture risk comparison of RULA and REBA based on measures of assessment-score variability: A case study of the metal coating industry in Thailand
(2024-01-01)
Sirikasemsuk, Kittiwat
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Kittipanya-Ngam, Pichawadee
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Luanwiset, Darin
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Leerojanaprapa, Kanogkan
This study examines the work posture risk comparison of RULA and REBA based on measures of assessment-score variability. During the metal coating process, chemicals were frequently employed, necessitating a heightened level of caution among the employees. The Cornell Musculoskeletal Discomfort Questionnaires (CMDQ) revealed the manifestation of physical discomfort among employees. In this study, the rapid upper limb assessment (RULA) and the rapid entire body assessment (REBA) were used to identify ergonomic concerns related to the work of employees in the black oxide coating department of a metal coating firm. The sensitivity of risk assessment between the two methods was investigated, considering the mean and variability of the assessment scores. Consideration was given to the diverse and crucial work positions of employees at each station, focusing exclusively on the standing working posture. In the black oxide coating section, there were 12 steps that 20 workers had to complete. Under the same wo rking postures, the overall average RULA score was determined to be at a high-risk level, whereas the overall average REBA score was at a moderate-risk level. As a result, the RULA method had a greater capacity for risk warning than the REBA method. Levene's test was also applied to determine whether the variances of the risk scores computed using the two techniques were equal. The results of the analysis showed that the variances in the scores using the two methods were not significantly different.
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Navigating online learning challenges and educational infrastructure in times of crisis: Insights and solutions among Thai engineering students utilizing a mixed-methods analysis
(2024-01-01)
Sirikasemsuk, Kittiwat
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Leerojanaprapa, Kanogkan
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Khwanpruk, Kankanit
The rapid shift to online learning during COVID-19 posed challenges for students. This investigation explored these hurdles and suggested effective solutions using mixed methods. By combining a literature review, interviews, surveys, and the analytic hierarchy process (AHP), the study identified five key challenges: lack of practical experience, disruptions in learning environments, condensed assessments, technology and financial constraints, and health and mental well-being concerns. Notably, it found differences in priorities among students across academic years. Freshmen struggled with the absence of hands-on courses, sophomores with workload demands, and upperclassmen with mental health challenges. The research also discussed preferred strategies for resolution, emphasizing independent learning methods, managing distractions, and adjusting assessments. By providing tailored insights, this study aimed to enhance online learning. Governments and universities should support practical work, prioritize student well-being, improve digital infrastructure, adapt assessments, foster innovation, and ensure resilience.
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Solving the incomplete data problem in Greco-Latin square experimental design by exact-scheme analysis of variance without data imputation
(2024-01-01)
Sirikasemsuk, Kittiwat
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Wongsriya, Sirilak
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Leerojanaprapa, Kanogkan
This study introduced a novel exact-scheme analysis of variance to tackle the challenge of incomplete data within the Greco-Latin square experimental design (GLSED), specifically for scenarios with a single missing observation across any treatment and block level, thus eliminating the need for conventional data imputation methods. This approach innovatively addresses and mitigates the bias in the treatment sum of squares, a significant drawback of traditional missing plot techniques, by providing a precise, exact-scheme-based formula for calculating the treatment sum of squares in fixed-effect GLSED contexts with unrecorded values. Moreover, it offers a method for correcting biased treatment sum of squares values, presenting an adjustment mechanism for instances where the least squares method was previously employed to estimate missing values. This comprehensive strategy not only enhances the methodological accuracy and integrity of GLSED studies but also contributes significantly to the field by offering a solution to navigate the complexities of incomplete datasets without resorting to data imputation, thus improving the rigor and validity of experimental designs in the face of missing data challenges.
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Optimization of Process Conditions for Hard Disk Drive Assembly for Defect Reduction
(2023-11-01)
Sirikasemsuk, Kittiwat
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Leerojanaprapa, Kanogkan
A spoiler installed in a hard disk drive can reduce the airflow velocity that causes vibration at an actuator arm and its head. In the case study, a hard disk drive manufacturer identified the defect of a loosely tightened spoiler in the hard disk drive by the spoiler installation machine. This occurred as a result of incorrect screw spacing (also called ‘the screwdriver encoder’). There was no study that specifically specified or created a suitable relationship model between the screwdriver encoder and associated parameters for the installation of a spoiler. Factors affecting the screw spacing were determined using multiple regression analysis, and a mathematical model of the significant factors of the screwdriver encoder was built. Data were collected from the spoiler installation machine and its software. Four factors were identified with the potential to impact the screwdriver encoder as (1) vacuum level for picking up the screw, (2) time spent in tightening the screw, (3) bit angle, and (4) screw torque. The ANOVA results pointed out that the screw torque within the range of experimental values did not affect the screw spacing, and a quadratic regression model was the most appropriate under various statistical criteria. This research demonstrated that a sophisticated regression model, i.e., a cubic model, is not always a good choice for an agent. In addition, the optimal values for the spoiler installation machine were determined. The faults decreased by 0.0096% from 0.055% each month. For choosing the relationship model of additional workpiece screw tightening variables, this research phase can be utilized as a guideline.
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USING A MULTI-CRITERIA DECISION MAKING APPROACH IN CONJUNCTION WITH A DELPHI STUDY TO IDENTIFY FACTORS INFLUENCING POLLUTANT EMISSIONS
(2023-01-01)
Atthirawong, Walailak
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Leerojanaprapa, Kanogkan
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Somboonwiwat, Tuanjai
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Luangpaiboon, Pongchanan
Pollution is currently a major concern in Thailand and other countries around the world. The Thai government has made environmental degradation a priority, emphasizing the benefits of reducing pollution generated by heavy industries. To be successful, a variety of efforts and authority at all levels are required. This study adds to the existing literature on identifying factors that reduce pollution emissions in the plastic industry using a multi-criteria decision-making (MCDM) approach. Two-phase methodologies were used to identify and rank such factors from a practical standpoint. From the first phase, two rounds of the Delphi method yielded three main criteria and 12 sub-criteria. Regarding that, the Analytical Hierarchy Process (AHP) was used to rank those factors. The findings indicated that the top three sub-criteria for According to the findings, the top three sub-criteria for reducing pollution emissions were "determination of standard improvement of pollution discharge at source clearly" (19.55%), "improvement of production efficiency" (15.32%), and "set up action plans for emergency pollution accidents from industry" (11.04%), respectively. Among the main factors, "Source reduction" has the highest rank (40.4%). Finally, this study discussed recommendations for entrepreneurs and policymakers.
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Measuring the Efficiency of Thai Commercial Banks during the COVID-19 Pandemic by Data Envelopment Analysis
(2022-08-26)
Leerojanaprapa, Kanogkan
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Bhundarak, Komn
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Atthirawong, Walailak
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Sirikasemsuk, Kittiwat
This study intends to measure the comparative efficiency of Thai Commercial Banks. The performance data has been collected over the past 2 years, between 2020 and 2021 during the COVID-19 pandemic and then compared to performance during the normal period of 2017-2018. Data Envelopment Analysis (DEA) using Variable Return to Scale (VRS) is applied to measure banking performance. Through Intermediation Approach, specific input variables are considered: employee expenses, directors' remuneration expenses, premises and equipment expenses and deposits. The output variables, including loans to customers and investment, are also analyzed.The same time, through the Production Approach, these specific input variables are analyzed: employee expenses, directors' remuneration expenses, premises and equipment expenses, fees and service expenses, taxes and duties and interest expenses. The output variables, including interest income, fee and service income, deposit, and loans to customers, are used to analyze the efficiency. The results of analysis with the Intermediation Approach indicate 5 of 13 Thai Commercial Banks were considered relatively inefficient including BAY, BBL, KBANK, SCB and SCBT. In addition, CIMB is 1 of 13 Thai Commercial Banks is considered as relatively inefficient under the Production Approach.
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Inventory Management for Consumer Products: A Distribution Center in Thailand
(2022-01-01)
Leerojanaprapa, Kanogkan
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Bhundarak, Komn
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Atthirawong, Walailak
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Sirikasemsuk, Kittiwat
The objective of the study is to formulate an appropriate order quantity policy. A best-selling product, a cleaner fresher mouth, was selected to be a representative of this study. Monthly Sales data of the cleaner fresher product was collected from January 2013 to December 2021, for 9 years, to forecast the sales of each product. Two forecasting techniques i.e. Exponential Smoothing and Box-Jenkins methods were compared to select the appropriate forecasting method by using MSE criterion. It was found that the Triple Exponential Method was the suitable forecasting model to forecast demand for the cleaner fresher products. These forecast values were then applied in inventory planning to determine the order policy by using Economic Order Quantity (EOQ) method of inventory management. The results found that EOQ technique resulted in a reduction in total cost rather than the company's current technique by 27.80%•

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