Journal Description
Engineering Proceedings
Engineering Proceedings
is an open access journal dedicated to publishing findings resulting from conferences, workshops, and similar events, in all areas of engineering. The conference organizers and proceedings editors are responsible for managing the peer-review process and selecting papers for conference proceedings.
Latest Articles
Managing Deadstock in the Fashion and Apparel Industry: An Exploration of Causes, Solutions and Technological Interventions
Eng. Proc. 2024, 66(1), 9; https://doi.org/10.3390/engproc2024066009 (registering DOI) - 28 Jun 2024
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The fashion and apparel (FA) industry faces a critical challenge in the form of deadstock. There are various causes for deadstock, and some may be traced to supply chain and inventory management inefficiency. This research paper aims to understand the issue of deadstock,
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The fashion and apparel (FA) industry faces a critical challenge in the form of deadstock. There are various causes for deadstock, and some may be traced to supply chain and inventory management inefficiency. This research paper aims to understand the issue of deadstock, its root causes, its implications for business and strategies to mitigate it. This paper also aims to investigate the potential of adopting artificial intelligence (AI), machine learning (ML) and data analytics to reduce the issue of deadstock. This research paper uses a systematic bibliographic literature review of the relevant literature in this subject area. In conclusion, this research paper aims to comprehensively study deadstock in the FA industry. It highlights the potential of using AI, ML and data analytics in supply chain management (SCM) to increase efficiency and mitigate the deadstock issue. There is, however, a lack of sufficient research papers that focus on deadstock in the FA industry and strategies and technological interventions to overcome it. Therefore, this research paper aims to serve as an overview that can be beneficial for researchers, business stakeholders and process engineers in the FA industry to create deployable technology-based solutions to address the problem of deadstock.
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Open AccessProceeding Paper
Green House Gas Emission Analysis in the Food Processing Industry: A Case Study of MSME in South India
by
Gangavarapu Chenchu Chythanya Krishna, Chelakari Ravi Karthika, Chindukuru Sushwanth, Guggila Hema Gopi Chand, Firoz Nasirudeen and Vinay V. Panicker
Eng. Proc. 2024, 66(1), 8; https://doi.org/10.3390/engproc2024066008 - 28 Jun 2024
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Rising carbon emissions are worsening global climatic conditions, posing a grave threat to the environment. Analysing and reducing carbon footprints are vital for combating climate change. A carbon footprint analysis categorises emissions into three scopes, aiming to identify re- duction areas and promote
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Rising carbon emissions are worsening global climatic conditions, posing a grave threat to the environment. Analysing and reducing carbon footprints are vital for combating climate change. A carbon footprint analysis categorises emissions into three scopes, aiming to identify re- duction areas and promote sustainable practices, such as energy efficiency, renewable energy use, and eco-friendly choices in consumption. The current study’s purpose is to track and analyse the carbon emissions in the inbound and outbound logistics of a process industry belonging to Micro Small and Medium Enterprises using life cycle analysis. Ultimately, this study recommends mitigation strategies to bring down the carbon footprint.
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Open AccessProceeding Paper
A Review on Medical Image Analysis Using Deep Learning
by
Raju Egala and M. V. S. Sairam
Eng. Proc. 2024, 66(1), 7; https://doi.org/10.3390/engproc2024066007 - 28 Jun 2024
Abstract
The objective of the medical image analysis is to increase the effectiveness of the diagnosis options. The Coevolution Neural Network (CNN) is the predominant neural network architecture used in Deep Learning (DL) for medical image analysis. Recently, various innovative technics of DL such
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The objective of the medical image analysis is to increase the effectiveness of the diagnosis options. The Coevolution Neural Network (CNN) is the predominant neural network architecture used in Deep Learning (DL) for medical image analysis. Recently, various innovative technics of DL such as different activation functions, optimization technics, and loss functions have enhanced the performance of CNNs. The Deep Learning CNN (DL-CNN) assists as valuable tool to assist radiologist in diagnosis and improves efficiency and accuracy. Numerous DL-CNN methods have been published to analyze medical images. This paper compiles the performance metrics of DL-CNN, as presented by various authors. This paper reviews the image analysis of six different diseases, viz., lung cancer, colorectal cancer, liver cancer, stomach cancer, breast cancer, and brain tumors.
Full article
Open AccessProceeding Paper
An Investigation into the Design and Analysis of the Front Frame Bumper with Dynamic Load Impact
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B. Gowthama Rajan, S. Padmanabhan, Devendra Gautam, Feroja Khan, S. Baskar, A. Lalitha Saravanan and Abhishek Sharma
Eng. Proc. 2024, 66(1), 6; https://doi.org/10.3390/engproc2024066006 - 28 Jun 2024
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The present study is aimed at upgrading the passenger car’s front inner bumper. The dynamic explicit time-stepping method IMPACT was used to conduct the impact analysis. The programme was first evaluated against experimental findings for beams subjected to impacts at low loads. The
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The present study is aimed at upgrading the passenger car’s front inner bumper. The dynamic explicit time-stepping method IMPACT was used to conduct the impact analysis. The programme was first evaluated against experimental findings for beams subjected to impacts at low loads. The deviation between the simulated and experimental findings of the deflected beam ranged from 1.6% to 9.5%. The genuine bumper was subjected to two different kinds of impact simulations. The data were used as a standard against which to compare future bumper improvements. Internal energy absorption is much higher in all the conditions. All three designs are able to absorb more energy without changing their overall performance.
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Open AccessProceeding Paper
Optimizing Social Security Contributions for Spanish Self-Employed Workers: Combining Data Preprocessing and Ensemble Models for Accurate Revenue Estimation
by
Luis Palomero, Vicente García and José Salvador Sánchez
Eng. Proc. 2024, 68(1), 5; https://doi.org/10.3390/engproc2024068005 - 28 Jun 2024
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The Real Decreto-ley 13/2022 has amended the framework governing the calculation of Social Security contributions for Spanish self-employed workers. This framework obligates taxpayers to the annual revenue projection, under the possibility of lending money for free or paying unexpected taxes at the end
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The Real Decreto-ley 13/2022 has amended the framework governing the calculation of Social Security contributions for Spanish self-employed workers. This framework obligates taxpayers to the annual revenue projection, under the possibility of lending money for free or paying unexpected taxes at the end of the year in the case of deviations. To address this issue, the Declarando firm has developed an algorithm to recommend the optimal contributions that combines a Simple Moving Average forecasting method with an offset-adjustment technique. This paper examines how this strategy can be improved by cleaning the input data and combining different forecasts using an Ensemble-based approach. After testing experimentally various alternatives, a promising strategy involves employing a median-based Ensemble on preprocessed data. Although this Ensemble-based approach significantly reduces forecasting errors, the improvements are diluted when the predictions are combined with the offset-adjustment process.
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Open AccessProceeding Paper
Deep Learning for Crime Forecasting of Multiple Regions, Considering Spatial–Temporal Correlations between Regions
by
Martín Solís and Luis-Alexander Calvo-Valverde
Eng. Proc. 2024, 68(1), 4; https://doi.org/10.3390/engproc2024068004 - 28 Jun 2024
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Crime forecasting has gained popularity in recent years; however, the majority of studies have been conducted in the United States, which may result in a bias towards areas with a substantial population. In this study, we generated different models capable of forecasting the
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Crime forecasting has gained popularity in recent years; however, the majority of studies have been conducted in the United States, which may result in a bias towards areas with a substantial population. In this study, we generated different models capable of forecasting the number of crimes in 83 regions of Costa Rica. These models include the spatial–temporal correlation between regions. The findings indicate that the architecture based on an LSTM encoder–decoder achieved superior performance. The best model achieved the best performance in regions where crimes occurred more frequently; however, in more secure regions, the performance decayed.
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![](https://pub.mdpi-res.com/engproc/engproc-68-00004/article_deploy/html/images/engproc-68-00004-g001-550.jpg?1719556530)
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Open AccessProceeding Paper
Enhancing Strength and Surface Quality of 3D-Printed Metal-Infused Filaments in Fused Deposition Modelling
by
Rama Seshu K. V. Ganga, Ramu Inala, Chandra Sekhar Jowdula, Praveen Matti and Battina N. Malleswararao
Eng. Proc. 2024, 66(1), 5; https://doi.org/10.3390/engproc2024066005 - 27 Jun 2024
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Fused deposition modelling (FDM) is a widely used 3D printing technique known for its versatility across industries. However, achieving optimal strength, crucial for applications like the automotive and aerospace industries, remains a challenge. This study demonstrates the efficacy of metal-infused filaments in enhancing
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Fused deposition modelling (FDM) is a widely used 3D printing technique known for its versatility across industries. However, achieving optimal strength, crucial for applications like the automotive and aerospace industries, remains a challenge. This study demonstrates the efficacy of metal-infused filaments in enhancing FDM’s strength and quality. By incorporating metal particles into polymer matrices, their mechanical properties are notably improved. PLA and metal-infill PLA (copper, silver) are tested, with silver PLA showing notably higher tensile strength and hardness. Considerations such as infill density and pattern are discussed for optimizing object strength. This work underscores the potential of metal-infused FDM printing for advancing manufacturing capabilities, especially for intricate, high-strength metal components.
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Open AccessProceeding Paper
Internet of Things Enabled Adjustable Ramp System for Productivity Enhancement of Micro, Small and Medium Enterprises
by
Akhil Sharma, Balbir Singh and Prabir Sarkar
Eng. Proc. 2024, 66(1), 4; https://doi.org/10.3390/engproc2024066004 - 27 Jun 2024
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The industry usually faces a problem during the loading/unloading of finished products and raw materials from one place to another when both places are at different elevations. As trucks are of variable height and industry loading bays are at different elevations, it is
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The industry usually faces a problem during the loading/unloading of finished products and raw materials from one place to another when both places are at different elevations. As trucks are of variable height and industry loading bays are at different elevations, it is not possible to drive the pallets effectively into freight, which results in decreasing loading/unloading efficiency of small concerns. In this paper, an adjustable height ramp system for increasing production efficiency and improving the industrial working environment was developed using a linear actuator and automation system for the safe loading and unloading of pallets. This adjustable ramp will help to increase the productivity of micro, small and medium enterprises (MSMEs), and it will provide a safe working environment. Using an adjustable ramp will help create a bridge between industry loading bays and freight, and it will also resolve the issue of different heights of both by making a path between them. The Internet of things (IoT)-enabled lifting and downward movement of the ramp is attempted for oil/air filter MSMEs.
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Open AccessProceeding Paper
Forecasting Methods for Road Accidents in the Case of Bucharest City
by
Cristina Oprea, Eugen Rosca, Ionuț Preda, Anamaria Ilie, Mircea Rosca and Florin Rusca
Eng. Proc. 2024, 68(1), 3; https://doi.org/10.3390/engproc2024068003 - 27 Jun 2024
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This paper aims to emphasize the necessity for policy reform, improvements in vehicle design and enhanced public awareness through the projection of future trends in road accidents, injuries and fatalities. The statistical methods that are used in this study are the empirical laws
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This paper aims to emphasize the necessity for policy reform, improvements in vehicle design and enhanced public awareness through the projection of future trends in road accidents, injuries and fatalities. The statistical methods that are used in this study are the empirical laws of Smeed and Andreassen. The main gap that the researchers identify is the lack of a standardized methodology with the help of which the appropriate forecasting method can be chosen in the area of traffic accidents. In the present study, the authors propose such a methodology that can be generalized, being suitable for use for any urban agglomeration at the micro and macro level.
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Open AccessProceeding Paper
Magnetic Assisted Finishing of Internal Surfaces
by
Munish Kumar, Ajay Choudhary and Dilshad Ahmad Khan
Eng. Proc. 2024, 66(1), 3; https://doi.org/10.3390/engproc2024066003 - 27 Jun 2024
Abstract
Surface quality is one of the most important things to think about when using precision equipment. Inadequate surface quality in engineering products can result in a number of issues, such as excessive wear, failures, improper geometry, and more. Traditional finishing techniques are neither
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Surface quality is one of the most important things to think about when using precision equipment. Inadequate surface quality in engineering products can result in a number of issues, such as excessive wear, failures, improper geometry, and more. Traditional finishing techniques are neither flexible nor economical when it comes to finishing complex geometries. When it comes to finishing with low tolerances and no surface topography degradation, magnetic assisted finishing systems rank among the best. This chapter discusses the types of magnetic assisted finishing techniques, including BERMP, UAMAF, and MAF, and how they are used to finish internal surfaces.
Full article
Open AccessProceeding Paper
Explaining When Deep Learning Models Are Better for Time Series Forecasting
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Martín Solís and Luis-Alexander Calvo-Valverde
Eng. Proc. 2024, 68(1), 1; https://doi.org/10.3390/engproc2024068001 - 27 Jun 2024
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There is a gap of knowledge about the conditions that explain why a method has a better forecasting performance than another. Specifically, this research aims to find the factors that can influence deep learning models to work better with time series. We generated
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There is a gap of knowledge about the conditions that explain why a method has a better forecasting performance than another. Specifically, this research aims to find the factors that can influence deep learning models to work better with time series. We generated linear regression models to analyze if 11 time series characteristics influence the performance of deep learning models versus statistical models and other machine learning models. For the analyses, 2000 time series of M4 competition were selected. The results show findings that can help explain better why a pretrained deep learning model is better than another kind of model.
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Open AccessProceeding Paper
Exploring the Dynamics of Natural Sodium Bicarbonate (Nahcolite), Sodium Carbonate (Soda Ash), and Black Ash Waste in Spray Dry SO2 Capture
by
Robert Makomere, Lawrence Koech, Hilary Rutto and Alfayo Alugongo
Eng. Proc. 2024, 67(1), 1; https://doi.org/10.3390/engproc2024067001 - 26 Jun 2024
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The efficacy of spray dry systems compared to wet flue gas desulphurisation (FGD) units depends on applying a highly reactive scrubbing reagent. This study assessed sodium-based compounds derived from natural sources and waste by-products as potential agents for treating sulphur dioxide (SO2
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The efficacy of spray dry systems compared to wet flue gas desulphurisation (FGD) units depends on applying a highly reactive scrubbing reagent. This study assessed sodium-based compounds derived from natural sources and waste by-products as potential agents for treating sulphur dioxide (SO2). Sodium carbonate (Na2CO3) and sodium bicarbonate (NaHCO3) were acquired from mineral deposits, whereas the black ash waste (Na2CO3·NaHCO3) was obtained from the pulp and paper sector. The sorbents introduced in slurry form were subject to SO2 absorption conditions in a lab-scale spray dryer, including an inlet gas phase temperature of 120–180 °C, flue gas flow rate of 21–34 m3/h, and sodium to sulphur normalised stoichiometric ratio (Na:S) of 0.25–1. The comparative performance was evaluated using the metric of %SO2 ( ) removal efficiency. The results showed that NaHCO3 had the highest overall result, with a removal efficiency of 62% at saturation. Black ash was the second best-performing reagent, with a 56% removal efficiency, while Na2CO3 had the lowest efficiency (53%). The maximum degree of SO2 reduction achieved using NaHCO3 under specific operating parameters was at an NSR of 0.875 (69%), a reaction temperature of 120 °C (73%), and a gas inlet flow rate of 34 m3/h. In conclusion, the sodium reagents produced significant SO2 neutralisation, exceeding 50% in their unprocessed state, which is within acceptable limits in small- to medium-sized coal-fired power plants considering retrofitting pollution control systems.
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Open AccessProceeding Paper
Case Study: Using Healables® ElectroGear® Wearable E-Textile Sleeve with Embedded Microcurrent Electrodes and WelMetrix® Physiologic Motion Sensors to Enhance and Monitor the Sporting Performance of a Baseball Pitcher
by
Moshe Lebowitz, George H. Lowell, Michael April, Ziv Ritchie, Marco van der Putten Landau and Moshe Ehrenberg
Eng. Proc. 2023, 52(1), 34; https://doi.org/10.3390/engproc2023052034 - 18 Jun 2024
Abstract
We aimed to reduce the recovery time for baseball pitchers from the established recovery period of four days to only one day. We designed a wearable and flexible arm sleeve composed of knitted nylon and a polyether–polyurea copolymer that has embedded proprietary dry
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We aimed to reduce the recovery time for baseball pitchers from the established recovery period of four days to only one day. We designed a wearable and flexible arm sleeve composed of knitted nylon and a polyether–polyurea copolymer that has embedded proprietary dry electrodes that deliver a personalized microcurrent electron stream regimen as well as physiological motion sensors that provide real-time feedback for this electroceutical’s efficacy, positioning it as a revolutionary e-textile for enhancing and gauging sporting proficiency. Healables® (Jerusalem, Israel) developed a noninvasive wearable device that docks onto its adjustable e-textile for team training and on-the-go and home-based improvement in terms of sports readiness, recovery, and performance.
Full article
(This article belongs to the Proceedings of Eng. Proc., 2023, RAiSE-2023)
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Open AccessProceeding Paper
Design and Test of a Haptic-Stimulated Mindfulness Vest for Guided Breathing
by
Wei Wang, Pauline van Dongen and Daria Casciani
Eng. Proc. 2023, 52(1), 33; https://doi.org/10.3390/engproc2023052033 - 6 Jun 2024
Abstract
This research explores the potential of clothing as a medium for enhancing mindfulness experiences, focusing on the Mysa shirt, a product being developed by the newly founded start-up Touchwaves BV, which integrates haptic technology for breath guidance. Through a user-centered design (UCD) approach,
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This research explores the potential of clothing as a medium for enhancing mindfulness experiences, focusing on the Mysa shirt, a product being developed by the newly founded start-up Touchwaves BV, which integrates haptic technology for breath guidance. Through a user-centered design (UCD) approach, the study focused on the Mysa shirt’s redesign and its use during mindfulness practices. From the user testing with the redesigned Mysa, novice mindfulness users reported positive outcomes, including increased relaxation and reduced stress, while experienced practitioners recognized its teaching potential. The feedback demonstrates the Mysa shirt’s potential to enhance mindfulness for diverse users, highlighting the promise of haptic technology in clothing to enhance body awareness and overall well-being. The study bridges the gap between clothing and mindfulness, offering valuable insights for future design and well-being applications.
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(This article belongs to the Proceedings of Eng. Proc., 2023, RAiSE-2023)
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Open AccessEditorial
Preface: The 4th International Electronic Conference on Applied Sciences (ASEC 2023)
by
Nunzio Cennamo
Eng. Proc. 2023, 56(1), 339; https://doi.org/10.3390/engproc2023056339 - 31 May 2024
Abstract
The 4th International Electronic Conference on Applied Sciences (ASEC 2023), an online event held from 27 October to 10 November 2023, brought together scientists from different areas to discuss important recent developments in several fields [...]
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(This article belongs to the Proceedings of The 4th International Electronic Conference on Applied Sciences)
Open AccessProceeding Paper
Enhanced Driver Drowsiness Detection Model Using Multi-Level Features Fusion and a Long-Short-Term Recurrent Neural Network
by
Lawan Yusuf, Mohammed Hamada, Mohammed Hassan and Habeebah Kakudi
Eng. Proc. 2023, 56(1), 338; https://doi.org/10.3390/ASEC2023-15537 - 28 May 2024
Abstract
Drowsiness driving poses a significant risk to road safety, necessitating effective drowsiness detection models. Most of the prior research has primarily relied on composite facial-based features, mainly focusing on the mouth and/or eye states, to identify drowsiness status. However, these models tend to
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Drowsiness driving poses a significant risk to road safety, necessitating effective drowsiness detection models. Most of the prior research has primarily relied on composite facial-based features, mainly focusing on the mouth and/or eye states, to identify drowsiness status. However, these models tend to overlook crucial information from input signals, resulting in suboptimal detection accuracy. Moreover, the absence of suitable algorithms and techniques for extracting other essential facial features, such as the eyebrow and nostril, further impacts the accuracy of drowsiness detection. To address these limitations, this study introduces an innovative algorithm and a technique for extracting drowsiness-related information from the eyebrow and nostril regions. Additionally, we propose a method, leveraging four composite facial-based drowsiness features; eyebrow, nostril, eye, and mouth states as inputs to a Convolutional Neural Network (CNN). A novel multilevel feature fusion method is employed to effectively combine the deep representations of these drowsiness-related features. The final step involves employing a Long-short-term memory (LSTM) recurrent neural network to classify the drowsiness status of drivers. Our proposed model is rigorously evaluated using the National Tsing Hua University drowsy driver detection (NTHU-DDD) video dataset. The experimental results demonstrate an impressive accuracy in different scenarios, and the accuracy result reached 0.973, showcasing the effectiveness of our approach in enhancing drowsiness detection accuracy and promoting road safety.
Full article
(This article belongs to the Proceedings of The 4th International Electronic Conference on Applied Sciences)
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Open AccessProceeding Paper
Failure Analysis of API 5L Grade B Underground Crude Oil Transfer Pipe
by
Mujiono and Fahmi Mubarok
Eng. Proc. 2024, 63(1), 29; https://doi.org/10.3390/engproc2024063029 - 27 May 2024
Abstract
An underground transfer pipe was utilized to deliver crude oil from the BDA gathering station to the A main gathering station. The transfer pipe made of API 5L grade B has a diameter of 6 inches and a length of 18,000 m. The
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An underground transfer pipe was utilized to deliver crude oil from the BDA gathering station to the A main gathering station. The transfer pipe made of API 5L grade B has a diameter of 6 inches and a length of 18,000 m. The pipe has a design life of 20 years, but after being operated for five years, 41 points of leakage were found in the area of KM 14 to KM 16. Visual inspection of the leakages in the pipe indicates general corrosion as the main issue. Nevertheless, failure analysis is required to investigate the root cause of the problem in this area. Several characterization methods were performed, including ultrasonic testing, to measure the distribution of pipe thickness. SEM and EDS testing were conducted to understand the hole formations that led to leakage and study their elemental changes around the leakage point. XRD and FTIR characterization were carried out on the deposit found on the inner diameter of the pipe. The ultrasonic thickness measurement indicates gradual pipe thinning until a hole was formed. Deposit analysis revealed wax composition at the upper level of the pipe formed due to transferred crude oil, while the bottom deposit where leakage was identified consisted of corrosion products such as FeO2 (geothite), Fe2O3 (hematite) and Fe3O4 (magnetite). The leakage failure in KM 14 and KM 16 was discovered to be where the pipe was at its lowest elevation point of underground pipe installation. This situation causes the pipe to be submerged by produced water at the 3 o’clock to 9 o’clock position, which initiates the occurrence of oxygen-influenced corrosion and the formation of hydroxide ions (OH−). The formation of hydroxide ions (OH−) triggers the Under Deposit Corrosion (UDC) mechanism.
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(This article belongs to the Proceedings of The 7th Mechanical Engineering, Science and Technology International Conference)
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Open AccessEditorial
Preface: The 39th International Manufacturing Conference (IMC39) of the Irish Manufacturing Council
by
Shaun McFadden, Paddy McGowan and Emmett Kerr
Eng. Proc. 2024, 65(1), 16; https://doi.org/10.3390/engproc2024065016 - 27 May 2024
Abstract
Ulster University, on behalf of the Irish Manufacturing Council, hosted the 39th International Manufacturing Conference (IMC39) at the Derry~Londonderry campus on the 24th and 25th of August 2023 [...]
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(This article belongs to the Proceedings of The 39th International Manufacturing Conference)
Open AccessProceeding Paper
Engineering Skills to Respond to SDGs: A Survey of Employers, Academics, and Students
by
Rosalind Henry, Margaret Morgan, Una Beagon, Brian Bowe, Ruchita Jani and Janet McKennedy
Eng. Proc. 2024, 65(1), 15; https://doi.org/10.3390/engproc2024065015 - 24 May 2024
Abstract
Addressing challenges posed by the Sustainable Development Goals (SDGs) will require the next generation of engineers from all disciplines to be equipped with specific skills. Given this context, a professional skills survey was designed, drawing on previous European-level research. Its results provide valuable
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Addressing challenges posed by the Sustainable Development Goals (SDGs) will require the next generation of engineers from all disciplines to be equipped with specific skills. Given this context, a professional skills survey was designed, drawing on previous European-level research. Its results provide valuable localised insights for educators into the most important skills for the next generation of engineers (on the island of Ireland) to achieve the SDGs. They also reveal some variance in the views of employers, academics, and students.
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(This article belongs to the Proceedings of The 39th International Manufacturing Conference)
Open AccessEditorial
Preface of the 1st International Online Conference on Buildings (IOCBD 2023)
by
David Arditi
Eng. Proc. 2023, 53(1), 60; https://doi.org/10.3390/engproc2023053060 - 8 May 2024
Abstract
The first International Online Conference on Buildings with a focus on advances in building structures, materials, repair/renovation, energy, environment, systems, architecture, urban planning, and construction management was held on 24–26 October 2023 [...]
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(This article belongs to the Proceedings of The 1st International Online Conference on Buildings)
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