Industrial Engineering Commons^™

Demand Forecasting And Inventory Management For An Automotive Tire Distributor In Northeast Thailand, Vasinee Chantaraponpun

Chulalongkorn University Theses and Dissertations (Chula ETD)

The objective of this research is to improve the inventory management for an automotive tire distributor company in Northeast Thailand to mainly reduce the excessive unnecessary stock. According to the initial investigations, the main causes of overstock are unstable customer demands and a lack of an inventory control system based on theory. In order to better address the issues and scope down the research area, three suitable products and sub-dealers with different demand patterns are selected to find the best-fit forecasting model for each of them and be customized the inventory policy based on the demand patterns. The methodology is …

Optimizing Energy Efficiency Projects In Bangkok Large Commercial Buildings, Angelica Arisa Morgan

Chulalongkorn University Theses and Dissertations (Chula ETD)

As a significant contributor to greenhouse gas emissions in the Asia Pacific region, Thailand has pledged to lower its GHG emissions by 555 million tCO2e by the year 2030. In Bangkok, energy efficiency projects in the large commercial buildings sector are an integral method by which to reduce emissions and to support a lower carbon future. Besides carbon dioxide emissions, energy efficiency projects also have the potential for other benefits including electricity and cost savings. This study develops a methodology to quantify the emissions reduction, electricity savings, and cost savings potential of various energy efficiency methods in this sector, and …

Analyzing Impact Of Economic Indicators On Vietnam Stock Market With Machine Learning Techniques, Nuttawan Sangsawai

Chulalongkorn University Theses and Dissertations (Chula ETD)

The study provides an analysis of the Vietnamese stock market using statistical and machine learning models. The dataset shows that all features have a positive linear relationship with the VN Index, but exhibit different scales and degrees of skewness. The Augmented Dickey-Fuller (ADF) unit root test was conducted to identify whether the variables were stationary or non-stationary, and most variables were transformed into stationary data through first differencing. The OLS method was used to construct a short run model, and the results indicated that only three variables, namely CPI, exchange rate, and S&P500 index, exhibited statistical significance. The ARDL Bound …

Multi-Objective Vehicle Loading And Routing Problem For Fresh Fruit And Vegetable Transportation, Supisara Krairiksh

Chulalongkorn University Theses and Dissertations (Chula ETD)

Multi-compartment refrigerated vehicles are recently utilized in the cold chain industry, due largely to their flexibility in storage capacities with different temperature settings. To better comprehend the costs and benefits of this vehicle type in fresh fruits and vegetable transportation, a multi-compartment vehicle routing and loading problem (MCVRLP) with three different objectives – namely (i) minimizing total transportation cost, (ii) minimizing CO2 emissions, and (iii) minimizing weight loss of fresh fruits and vegetable – is herein explored and solved by mathematical formulation and genetic-based evolutionary algorithm approaches. Based on our computational results, we find that large and complicated MCVRLP instances …

Bitcoin Candlestick Price Prediction With Recurrent Neural Network, Sutiwat Simtharakao

Chulalongkorn University Theses and Dissertations (Chula ETD)

Bitcoin is a high-risk asset with a potentially high return. Predicting Bitcoin candlestick, i.e., open, high, low, and close (OHLC) prices, can help investors make trading decisions. The objective of this study is to develop a neural network model to predict the candlestick prices of Bitcoin for the next period. Additionally, this study investigates methods to enhance the model's forecasting performance by feature transformations, specifically data normalization. This study employs two neural network algorithms, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), to forecast daily Bitcoin OHLC prices. To enhance the model's performance, we compare sliding window normalization with …

แนวทางการตัดสินใจการนำหุ่นยนต์มาใช้ทดแทนหรือปฏิบัติร่วมกับพนักงานในการทำงาน, ชนาธิป ทองดอนน้อย

Chulalongkorn University Theses and Dissertations (Chula ETD)

งานวิจัยนี้ให้ความสำคัญเกี่ยวกับกรอบการตัดสินใจสำหรับการนำหุ่นยนต์ร่วมปฏิบัติการหรือโคบอท เข้ามาใช้แทนที่แรงงานมนุษย์และ/หรือเพื่อทำงานร่วมกับคนงาน ในกรณีศึกษาของบริษัทที่ผลิตเลนส์แว่นตาผู้บริหารระดับสูงต้องการนำหุ่นยนต์ร่วมปฏิบัติการเข้ามาใช้ในกระบวนการคัดแยกชิ้นงาน เนื่องจากกระบวนการนี้เป็นกระบวนการทำงานแบบซ้ำ ๆ ซึ่งส่งผลกระทบให้พนักงานเกิดความเมื่อยล้าและความเจ็บป่วยทางการยศาตร์ ในการตัดสินใจสำหรับการนำหุ่นยนต์ร่วมปฏิบัติการทางโรงงานกรณีศึกษาได้ทำการพิจารณาเพียงด้านการเงินโดยไม่คำนึงถึงปัจจัยสำคัญอื่นๆ ดังนั้นบทความนี้จึงมุ่งเน้นสำรวจปัจจัยที่มีบทบาทสำคัญในการตัดสินใจใช้หุ่นยนต์ร่วมปฏิบัติการในสายการผลิต โดยการวิเคราะห์ปัจจัยเชิงสำรวจ (EFA) และการวิเคราะห์ปัจจัยเชิงยืนยัน (CFA) ซึ่งเป็นขั้นตอนทางสถิติหลายตัวแปร ถูกนำมาใช้ในการวิเคราะห์ปัจจัยที่เกี่ยวข้องกับตัวแปรแฝง นอกจากนี้ได้ทำการจำลองสถานการณ์ด้วยโปรแกรม ARENA เพื่อตรวจสอบประโยชน์ของการนำโคบอทไปใช้ในกรณีศึกษาอีกด้วย

Implementation Of Good Distribution Practice In A Pharmaceutical Manufacturer, Pana Chinajitphan

Chulalongkorn University Theses and Dissertations (Chula ETD)

Good Distribution Practice (GDP) has recently been adopted and practised by Thailand's pharmaceutical industry, which has complemented the supply chain perspective and radically changed the quality landscape of the industry. This study presents a case of a pharmaceutical manufacturer in Thailand that implemented GDP to ensure the quality of its products during storage and distribution processes, as well as to prevent the entry of falsified products into the Pharmaceutical Supply Chain (PSC). The GDP implementation combined Project Management and Quality Risk Management (QRM) to identify operational gaps, manage identified risks, and reduce GDP gaps. After analysing internal stakeholders, related teams …

Efficient Removal Of Lead Ions From Aqueous Media Using Sustainable Sources On Marine Algae, Hannah Namkoong, Erik Biehler, Gon Namkoong, Tarek M. Abdel-Fattah

Electrical & Computer Engineering Faculty Publications

The goal of this project is to explore a new method to efficiently remove Pb(II) ions from water by processing Undaria pinnatifida into immobilized beads using sodium alginate and calcium chloride. The resulting biosorbent was characterized by Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDS). Using immobilized U. pinnatifida, we investigated the effect of various factors on Pb(II) ion removal efficiency such as temperature, pH, ionic strength, time, and underlying biosorption mechanisms. For Pb(II) ion biosorption studies, Pb(II) ion biosorption data were obtained and analyzed using Langmuir and Freundlich adsorption models. It …

Simulated Annealing Heuristics For The Dynamic Generalized Quadratic Assignment Problem, Yugesh Dhungel

Graduate Theses, Dissertations, and Problem Reports (ETD)

The Dynamic Generalized Quadratic Assignment Problem (DGQAP) is the task of assigning a set of facilities to a set of locations in a multi-period planning horizon such that the sum of the transportation and assignment/reassignment costs is minimized. The facilities may have different space requirements, and the capacities of locations may vary during the multiple-period planning horizon. Also, multiple facilities may be assigned to each location without violating the space capacity of the location. This research presents a formulation and applications of DGQAP in various layout and assignment problems encountered in the literature. Two Simulated Annealing (SA) metaheuristics named SA …

Developing Artificial Intelligence Tools To Investigate The Phenotypes And Correlates Of Chronic Kidney Disease Patients In West Virginia, Marzieh Amiri Shahbazi

Graduate Theses, Dissertations, and Problem Reports (ETD)

ABSTRACT

Developing Artificial Intelligence tools to investigate the phenotypes and correlates of Chronic Kidney Disease patients in West Virginia

Marzieh Amiri Shahbazi

Chronic kidney disease (CKD) is responsible for disrupting the lives of 37 million people just in the USA, which is about 1 in 7 adults. CKD results in a gradual loss of kidney function over time. Sometimes CKD doesn’t produce any significant symptoms until it reaches an advanced stage. On the other hand, acute kidney injury (AKI) accounts for a sudden decline in the kidney’s function. As a result, the kidneys fail to filter waste materials from the …

Functionally Magnetic Gradient Copper-Nickel Material Fabricated Via Directed Energy Deposition, Vy Tran Phuong Nguyen

Graduate Theses, Dissertations, and Problem Reports (ETD)

Functionally gradient materials (FGMs) of CuSn10 and Inconel 718 were fabricated via a hybrid directed energy deposition (DED) system. The objective of the present thesis is to determine the feasibility of manufacturing CuSn10 and Inconel 718 FGMs via DED and investigate the physical and mechanical properties and the microstructures of the resulting FGMs. The physical tests comprised of conductivity and Seebeck coefficient measurements. The microstructure analysis and mechanical testing include microscopic imaging, scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and hardness test. In addition, compressive strength test was performed to analyze the interface bonding behaviors.

Energy Planning Model Design For Forecasting The Final Energy Consumption Using Artificial Neural Networks, Haidy Eissa

Theses and Dissertations

“Energy Trilemma” has recently received an increasing concern among policy makers. The trilemma conceptual framework is based on three main dimensions: environmental sustainability, energy equity, and energy security. Energy security reflects a nation’s capability to meet current and future energy demand. Rational energy planning is thus a fundamental aspect to articulate energy policies. The energy system is huge and complex, accordingly in order to guarantee the availability of energy supply, it is necessary to implement strategies on the consumption side. Energy modeling is a tool that helps policy makers and researchers understand the fluctuations in the energy system. Over the …

Virtual Analyzers For Increasing The Intelligence Of Industrial Process Control Systems, Umidjon Abdimajotovich Ruziev Phd, Marufjon Kobuljanovich Shodiev

Chemical Technology, Control and Management

It is shown that the development and implementation of virtual analyzers of the quality of the final industrial products is an effective tool for increasing the efficiency of industrial production. The methodology and stages of development of virtual analyzers for predicting the quality of products, monitoring non-measurable or difficult-to-measure parameters of continuous and periodic technological processes are considered, and issues of supporting and adapting a virtual analyzer during its operation without restructuring are also considered.

End Milling Process Modeling Using Artificial Neural Networks, Khaled Abdel-Hamid Elsayed

Archived Theses and Dissertations

No abstract provided.

Effects Of The Inclusion Of Rice Hull Derived Bio-Oil On Wood Pellet Production, Tyler E. Lowe

Theses and Dissertations

Wood pellet production has become an advancing industry for the sake of reducing greenhouse emissions into the atmosphere especially, in European Union countries. Researchers and industry executives seek new methods and materials to improve the pelletization process. Rice hulls or husks has the potential to aid in wood pelletization as they possess high calorific values. This study focuses on using rice hull derived bio-oil from pyrolysis, which will also decrease ash content, as an additive to aid in the wood pelletization process. Using two groups of rice hull derived bio-oil as an additive in wood pelletization: Group 1 uses heavy …

Deep Multi-Modal U-Net Fusion Methodology Of Infrared And Ultrasonic Images For Porosity Detection In Additive Manufacturing, Christian E. Zamiela

Theses and Dissertations

We developed a deep fusion methodology of non-destructive (NDT) in-situ infrared and ex- situ ultrasonic images for localization of porosity detection without compromising the integrity of printed components that aims to improve the Laser-based additive manufacturing (LBAM) process. A core challenge with LBAM is that lack of fusion between successive layers of printed metal can lead to porosity and abnormalities in the printed component. We developed a sensor fusion U-Net methodology that fills the gap in fusing in-situ thermal images with ex-situ ultrasonic images by employing a U-Net Convolutional Neural Network (CNN) for feature extraction and two-dimensional object localization. We …

A Dual Perspective Towards Building Resilience In Manufacturing Organizations, Steven A. Fazio

Theses and Dissertations

Modern manufacturing organizations exist in the most complex and competitive environment the world has ever known. This environment consists of demanding customers, enabling, but resource intensive Industry 4.0 technology, dynamic regulations, geopolitical perturbations, and innovative, ever-expanding global competition. Successful manufacturing organizations must excel in this environment while facing emergent disruptions generated as biproducts of complex man-made and natural systems. The research presented in this thesis provides a novel two-sided approach to the creation of resilience in the modern manufacturing organization. First, the systems engineering method is demonstrated as the qualitative framework for building literature-derived organizational resilience factors into organizational structures …

Leveraging Choice Modeling Technique For Enhancing The Cyber Resilience Of The Smart Grid, Kesava Karishma Devi Dadi

Theses and Dissertations

This research focuses on the cyber-attack of the smart grid and its retrieval to a normal state by estimating the smart grid's resilience. This study developed a theoretical model to estimate the resilience of the smart grid using choice modeling. A utility function is formulated based on various factors and sub-factors of resilience to estimate the resilience of the smart grid. Choice modeling is applied to estimate the model parameters in various fields such as marketing, energy, transportation, and health and to predict the outcome.

The Development Of Authentic Virtual Reality Scenarios To Measure Individuals’ Level Of Systems Thinking Skills And Learning Abilities, Vidanelage L. Dayarathna

Theses and Dissertations

This dissertation develops virtual reality modules to capture individuals’ learning abilities and systems thinking skills in dynamic environments. In the first chapter, an immersive queuing theory teaching module is developed using virtual reality technology. The objective of the study is to present systems engineering concepts in a more sophisticated environment and measure students learning abilities. Furthermore, the study explores the performance gaps between male and female students in manufacturing systems concepts. To investigate the gender biases toward the performance of developed VR module, three efficacy measures (simulation sickness questionnaire, systems usability scale, and presence questionnaire) and two effectiveness measures (NASA …

Using A Systemic Skills Model To Build An Effective 21st Century Workforce: Factors That Impact The Ability To Navigate Complex Systems, Morteza Nagahi

Theses and Dissertations

The growth of technology and the proliferation of information made modern complex systems more fragile and vulnerable. As a result, competitive advantage is no longer achieved exclusively through strategic planning but by developing an influential cadre of technical people who can efficiently manage and navigate modern complex systems. The dissertation aims to provide educators, practitioners, and organizations with a model that helps to measure individuals’ systems thinking skills, complex problem solving, personality traits, and the impacting demographic factors such as managerial and work experience, current occupation type, organizational ownership structure, and education level. The intent is to study how these …