Sirikasemsuk, Kittiwat

Preferred name

Alternative Name

Sirikasemsuk, K.

Main Affiliation

School of Engineering

kittiwat.si@kmitl.ac.th

Now showing 1 - 10 of 12

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Full-model regression sum of squares of randomized complete block design having one unrecorded observation
(2019-01-01)
Sirikasemsuk, Kittiwat
;
Leerojanaprapa, Kanogkan
;
Sirikasemsuk, Sirisak
In the classical design of experiment, a randomized complete block design (RCBD) is a helpful experimental design because this design uses a small number of experimental units. The randomized complete block design is comprised of two factors, i.e., a nuisance factor and a potential factor. In many real experiments, some data might be missing or unrecorded. The instant formulae were not provided for an analysis of variance in this case. This paper took into account the randomized complete block design (RCBD) with a treatments and b blocks. In this contribution, the RCBD with an unrecorded value was analyzed by means of the exact scheme with the model comparison approach. The advantages of the exact scheme are that the unrecorded value for the unfilled cell is not estimated and the treatment sum of squares is unbiased. It is important to note that there is no ready-made formula for RCBD in the past. Hence, this research paper provided the mathematical formulae for the fitted parameters and the overall regression sum of squares (ORSS) for the full model of experimental data. It is also noted that the ORSS is imperative for the analysis of the variance by means of the exact scheme.
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Modeling Equivalent Circulating Density During Drilling Operations in the Gulf of Thailand
(2026-03-31)
Leerojanaprapa, Kanogkan
;
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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Optimization of Process Conditions for Hard Disk Drive Assembly for Defect Reduction
(2023-11-01)
Sirikasemsuk, Kittiwat
;
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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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
;
Wongsriya, Sirilak
;
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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One missing value problem in Latin square design of any order: Exact analysis of variance
(2017-01-01)
Sirikasemsuk, Kittiwat
;
Leerojanaprapa, Kanogkan
This research proposes a simplified exact approach based on the general linear model for solving the K × K Latin square design (LSD) with one replicate and one missing value, given the lack of ready-made mathematical formulas for the sub-variance. Under the proposed scheme, the effects of the potential variable were determined by means of the regression sums of squares under the full and reduced treatment models. The mathematical expressions could be applied to the LSD with one missing value of any order. Moreover, the treatment, row and column sums of squares are unbiased.
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Measure of bullwhip effect in supply chains with first-order bivariate vector autoregression time-series demand model
(2017-02-01)
Sirikasemsuk, Kittiwat
;
Luong, Huynh Trung
With supply chains becoming increasingly global, the issue of bullwhip effect, a phenomenon attributable to demand fluctuation in the upstream section of the supply chains, has received greater attention from many researchers. However, most existing research studies on quantifying the bullwhip effect were conducted under the first-order autoregressive [AR(1)] incoming demand process or its variants as the fundamental demand process, thereby failing to account for the retailer demand dependency. This research work thus examined the bullwhip effect for the first-order bivariate vector autoregression [VAR(1)] demand process in a two-stage supply chain consisting of one supplier and two retailers. The impacts of the correlation parameters of the demand process, the correlation coefficient between the two error terms, and the variances of the error terms on the bullwhip effect were investigated. As such, the measure of the bullwhip effect was established using an analytical approach in which the minimum mean square error (MMSE) forecasting method and the base stock policy were applied to all members of the supply chain. Numerical experiments were then conducted to illustrate the behavior of the bullwhip effect with respect to various parameters of the demand processes to see in which situations the bullwhip effect would be absent. In addition, an evaluation of the inventory variance ratio was analyzed.
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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
;
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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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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Applying Lean Concept and Software Packages to Support Critical Issue Monitoring Process in Office
(2023-03-31)
Kittipanya-Ngam, Pichawadee
;
Chanthavutti, Anunya
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Sirikasemsuk, Kittiwat
The purpose of this research was to improve the performance monitoring process of critical issues in a case study company. The problem was that the process of tracking the performance of critical issues was ineffective. This research applied the lean concept. We started with the study and analysis of the work in order to find the root causes of the problem by means of the fishbone diagram. Subsequently, ECRS techniques were used to improve activities. The researcher used Microsoft Office 365 platforms, i.e., Microsoft Planner, to track the performance of the important tasks. After work process improvement, the activities 1 (the coordinator of the five departments collected the department forms) and 4 (the central coordinator summarized the forms of the five departments into the agency's form) could be reduced. Finally, the wasteful process time was reduced by more than 50 %. Also, the workload of coordinators was greatly reduced.
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Measure and analysis of the bullwhip effect in supply chain when demand correlation exists between two market groups under the first-order moving-average demand processes
(2018-01-01)
Sirikasemsuk, Kittiwat
;
Sirikasemsuk, Sarawut
With supply chains becoming increasingly global, the issue of bullwhip effect, a phenomenon attributable to demand fluctuation in the upstream section of the supply chains, has received greater attention from many researchers. The phenomenon in which the variation of upstream members' orders is amplified than the variation of downstream members' demands in the supply chain is called the bullwhip effect (BWEF). Most of existing research studies did not realize the demand dependency of market demands. Thus, this research focused on the study of the influence of the demand correlation coefficient between two market groups on the BWEF. The incoming demand processes are assumed the separate first-order moving-average, [MA(1)] demand patterns. The scope of the supply chain structure used in this research is composed of one manufacturer and two distribution centers. The general result reveals that the coefficient of correla-tion is one of several factors affecting the BWEF.

Sirikasemsuk, Kittiwat

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