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6 pages, 355 KiB

Open AccessEditorial

Preface: III International Congress: Technology and Innovation in Engineering and Computing

by Luis Olivera-Montenegro

Eng. Proc. 2025, 83(1), 5; https://doi.org/10.3390/engproc2025083005 - 7 Jan 2025

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Abstract

The III International Congress: Technology and Innovation in Engineering and Computing, organized by Faculty of Engineering, St [...] Full article

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10 pages, 7549 KiB

Open AccessProceeding Paper

Effect of the Process Parameters on the Mechanical Properties of 3D-Printed Specimens Fabricated by Material Extrusion 3D Printing

by Andoni Molina and Julio Acosta-Sullcahuamán

Eng. Proc. 2025, 83(1), 1; https://doi.org/10.3390/engproc2025083001 - 6 Jan 2025

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Abstract

This work aims to study the influences of nozzle temperature, layer thickness and raster angles on the mechanical properties of acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) specimens fabricated by material extrusion 3D printing. Tensile tests were carried out in order to [...] Read more.

This work aims to study the influences of nozzle temperature, layer thickness and raster angles on the mechanical properties of acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) specimens fabricated by material extrusion 3D printing. Tensile tests were carried out in order to evaluate the mechanical properties of ABS and PLA specimens. The results showed that tensile strength decreased at a higher nozzle temperature for ABS, while an increase followed by a decrease in tensile strength occurred for PLA, with the maximum value obtained at 250 °C. Scanning electronic microscopy was used to analyze the surface fracture after tensile tests of specimens fabricated with different nozzle temperatures. Moreover, the highest tensile strength values for both ABS and PLA were achieved with a raster angle of [0°], the same direction as the applied tensile load. Additionally, a higher tensile strength was obtained for both ABS and PLA at a lower layer thickness. Based on these results, the process parameters used to manufacture a 3D object influence its mechanical properties. Full article

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9 pages, 3011 KiB

Open AccessProceeding Paper

Design, Manufacturing and Mechanical Evaluation of a 3D Printed Customized Wrist-Hand Orthosis for the Treatment of De Quervain Tenosynovitis

by Sofia Franco, Mauricio Ramos, Renzo Cordova, Emilio Ochoa, Gianella Ccama and Andoni Molina

Eng. Proc. 2025, 83(1), 2; https://doi.org/10.3390/engproc2025083002 - 6 Jan 2025

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Abstract

De Quervain’s tenosynovitis is a pathology that affects the tendons of the thumb and generates pain and inflammation, being common in people between 18 and 30 years old who perform repetitive movements. Despite the innovation of 3D printing in orthotics, customization is lacking. [...] Read more.

De Quervain’s tenosynovitis is a pathology that affects the tendons of the thumb and generates pain and inflammation, being common in people between 18 and 30 years old who perform repetitive movements. Despite the innovation of 3D printing in orthotics, customization is lacking. Therefore, this works aims to develop a 3D printed customized wrist-hand orthosis (WHO) for the treatment of De Quervain tenosynovitis. The WHO includes three main parts, which would be two faces that cover the front and back of the hand and the locks to ensure the coupling of both faces. Prior to 3D printing, feedstock filament characterization tests were carried out, and tensile strength, melt flow index, degradation, and melting temperature were obtained. 3D printing of the WHO was achieved in a short time and with an adequate fit. Subsequently, mechanical tests were carried out to evaluate the maximum force of the WHO in different positions. Full article

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Solution concept. Full article ">Figure 2
Area involved in immobilization [<a href="#B12-engproc-83-00002" class="html-bibr">12</a>]. A: Distal metacarpal area, B: Base of the thumb, C: Central Dorsal Area, D: Wrist Area, E: Distal palmar area. Full article ">Figure 3
Autodesk Fusion 360: Selection of side of application of force (blue arrow). Full article ">Figure 4
Manufacturing process of WHO. Full article ">Figure 5
Mechanical test of WHO. Full article ">Figure 6
Wrist movements, modified of [<a href="#B16-engproc-83-00002" class="html-bibr">16</a>]. (A) Flexion, (B) Extension, (C) Ulnar deviation and (D) Radial deviation. Full article ">Figure 7
FTIR results. Full article ">Figure 8
Manufacturing results: (a) Orthosis printed in 90° degrees. (b) Orthosis printed in 45° to the left. (c) Orthosis printed in 75° to the front. Full article ">

9 pages, 2119 KiB

Open AccessProceeding Paper

Additive Manufacturing of Reinforced Thermoplastic Nanoclay Particle Composites by Fused Filament Fabrication

by Andoni R. Molina and Julio Acosta-Sullcahuamán

Eng. Proc. 2025, 83(1), 3; https://doi.org/10.3390/engproc2025083003 - 7 Jan 2025

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Abstract

In this study, reinforced thermoplastic nanoclay particle composites were prepared and used as filaments for additive manufacturing of specimens by using fused filament fabrication (FFF). Acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) were used as thermoplastic polymer matrices. The particle reinforced composite [...] Read more.

In this study, reinforced thermoplastic nanoclay particle composites were prepared and used as filaments for additive manufacturing of specimens by using fused filament fabrication (FFF). Acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) were used as thermoplastic polymer matrices. The particle reinforced composite feedstock filaments were fabricated from ABS and PLA pellets with different contents of nanoclay particles in a twin-screw extruder. Tensile and impact tests were carried out to evaluate the mechanical properties of the composite specimens fabricated by FFF. The mechanical test results showed an increase in the tensile strength of ABS matrix composites, but a decrease in the impact strength. For the case of PLA matrix composites, the tensile strength decreased when introducing the nanoclay particles and only with 3% of nanoclay particles was an increase of impact strength observed. Successful additive manufacturing of the particle-reinforced composite was achieved. Full article

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9 pages, 2397 KiB

Open AccessProceeding Paper

The Evaluation of the Seismic Performance of Unsymmetric-Plan Tall Buildings Using Modal Spectral Time History and Multi-Mode Pushover Analysis

by Luis A. Flores and Rick M. Delgadillo

Eng. Proc. 2025, 83(1), 6; https://doi.org/10.3390/engproc2025083006 - 8 Jan 2025

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Abstract

In recent seismic events that occurred worldwide and in Peru, it has been observed that irregular structures in plan present greater structural damage compared to regular structures. Investigations carried out after seismic events indicate that irregular plan structures collapse due to erroneous structural [...] Read more.

In recent seismic events that occurred worldwide and in Peru, it has been observed that irregular structures in plan present greater structural damage compared to regular structures. Investigations carried out after seismic events indicate that irregular plan structures collapse due to erroneous structural conception and poor seismic analysis. Likewise, the Peruvian earthquake-resistant standard does not establish a permissible limit for the degree of irregularity under analysis, instead qualitatively assessing the structural irregularity. The objective of this article was to study the effect of plan irregularities using innovative methodologies on the structural response of tall 10-story reinforced concrete buildings. In this sense, seventeen (17) structural models are proposed that reflect different irregular configurations in plan: 06 structures Type L, 05 structures Type I, 05 structures Type I, and one regular building. These buildings are numerically modeled using ETABS software V.18.0 through modal analysis, Modal Spectral and Linear Time History (MSLTH), and Multi-Mode Pushover (MPA). For the MSLTH, seven (07) pairs of representative Peruvian earthquakes were analyzed. The results of the modal analysis evaluated in the first two vibration modes demonstrated that Type L irregular structures change their behavior from translational to torsional when the structures present an irregularity greater than 57%. Type I and O structures present translational behavior. Furthermore, the results of the Modal Spectral and MSLTH analysis demonstrate that Type L structures present greater displacements and drifts in both directions. The shear force and the overturning moment for Types L, I, and O decrease as the irregularity in plan increases. Finally, the results of the MPA for irregular Type L structures demonstrated that the lateral stiffness of the structures decreases as the irregularity in plan is critical, increasing the possibility of the formation of plastic mechanisms in the structural elements. Full article

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6 pages, 362 KiB

Open AccessProceeding Paper

A Survey of Process Mining for Customer Management

by Javier Dioses and Leyde Cordova

Eng. Proc. 2025, 83(1), 7; https://doi.org/10.3390/engproc2025083007 - 8 Jan 2025

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Abstract

Currently, organizations are experiencing rapid growth in the digitization of their processes, which generates a high availability of data and metadata in information systems generated by the activities of operations and support areas. This is important for business because it allows them to [...] Read more.

Currently, organizations are experiencing rapid growth in the digitization of their processes, which generates a high availability of data and metadata in information systems generated by the activities of operations and support areas. This is important for business because it allows them to analyze and understand the customer journey to provide a better experience to consumers and generate value in organizations. One way to analyze the customer journey is to use process discovery to obtain an optimal process model. There are several process discovery algorithms that allow for analyzing different business process models. In this paper, we focus on the customer experience because we have found that this is a trend in business that has rarely been addressed using process discovery by means of event logs. Thus, in this study, we conduct a literature review of primary articles about the use of process discovery algorithms using event logs from information systems to provide a better understanding on this topic. As a result, we have found that Heuristic Miner, Alpha Miner, and Inductive Miner are the most used algorithms for customer process discovery. Finally, we explain our findings about process discovery in the customer experience and why this is an emerging topic. Full article

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8 pages, 1424 KiB

Open AccessProceeding Paper

A Convolutional Neural Network for Early Supraventricular Arrhythmia Identification

by Emilio J. Ochoa and Luis C. Revilla

Eng. Proc. 2025, 83(1), 8; https://doi.org/10.3390/engproc2025083008 - 8 Jan 2025

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Abstract

Supraventricular arrhythmias (SVAs), including the often-asymptomatic supraventricular extrasystole (SVE), pose significant challenges in early detection and precise diagnosis. These challenges are of paramount importance, as recurrent SVEs may elevate the risk of developing severe SVAs, potentially resulting in cardiac weakening and subsequent heart [...] Read more.

Supraventricular arrhythmias (SVAs), including the often-asymptomatic supraventricular extrasystole (SVE), pose significant challenges in early detection and precise diagnosis. These challenges are of paramount importance, as recurrent SVEs may elevate the risk of developing severe SVAs, potentially resulting in cardiac weakening and subsequent heart failure. In the study conducted, an innovative approach was introduced that combined a convolutional neural network (CNN) architecture to enable the early identification and characterization of SVEs within electrocardiogram (ECG) signals. The analysis leveraged a dataset comprising 78 half-hour recordings from the highly regarded MIT-BIH Arrhythmia Database, which included annotation headers serving as labels for each recording. Signals were down-sampled by a factor of 2 and split into windows of 512 samples, with 12,288 observations for training. Following the methodology, classic signal preprocessing techniques (filtering and data normalization) were used. The proposed model was based on the UNET 1D model. A binary cross-entropy loss function, Adam optimizer, and a batch size of 128 were obtained after a hyperparameter tuning. As a training-validation methodology, a 50-fold cross-validation technique was used. The approach demonstrated a Dice coefficient of 79.01%, a precision of 80.96%, and a recall rate of 86.60% in detecting SVE events. These findings were corroborated through meticulous comparison with the annotations provided by the MIT-BIH database. The results underscore the immense potential of CNN and deep learning techniques in the early detection of supraventricular arrhythmias. This approach not only offers a valuable tool for healthcare professionals engaged in telemonitoring and early intervention strategies but also represents a significant contribution to the field of cardiac health monitoring. By facilitating efficient and precise identification of SVEs, our research sets the stage for improved patient outcomes and the prevention of severe SVAs, marking substantial advancements in this critical domain. Full article

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8 pages, 7391 KiB

Open AccessProceeding Paper

Comparative Analysis of LiDAR Inertial Odometry Algorithms in Blueberry Crops

by Ricardo Huaman, Clayder Gonzalez and Sixto Prado

Eng. Proc. 2025, 83(1), 9; https://doi.org/10.3390/engproc2025083009 - 9 Jan 2025

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Abstract

In recent years, LiDAR Odometry (LO) and LiDAR Inertial Odometry (LIO) algorithms for robot localization have considerably improved, with significant advancements demonstrated in various benchmarks. However, their performance in agricultural environments remains underexplored. This study addresses this gap by evaluating five state-of-the-art LO [...] Read more.

In recent years, LiDAR Odometry (LO) and LiDAR Inertial Odometry (LIO) algorithms for robot localization have considerably improved, with significant advancements demonstrated in various benchmarks. However, their performance in agricultural environments remains underexplored. This study addresses this gap by evaluating five state-of-the-art LO and LIO algorithms—LeGO-LOAM, DLO, DLIO, FAST-LIO2, and Point-LIO—in a blueberry farm setting. Using an Ouster OS1-32 LiDAR mounted on a four-wheeled mobile robot, the algorithms were evaluated using the translational error metric across four distinct sequences. DLIO showed the highest accuracy across all sequences, with a minimal error of 0.126 m over a 230 m path, while FAST-LIO2 achieved its lowest translational error of 0.606 m on a U-shaped path. LeGO-LOAM, however, struggled due to the environment’s lack of linear and planar features. The results underscore the effectiveness and potential limitations of these algorithms in agricultural environments, offering insights into future improvements and adaptations. Full article

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12 pages, 4916 KiB

Open AccessProceeding Paper

Ecological Protection: Cell Phone Stand with Cable Winding Made of Polypropylene

by Deysi Vanessa Canchis Paredes, Jerson Córdova Salas and Ruben Felipe Vidal Endara

Eng. Proc. 2025, 83(1), 10; https://doi.org/10.3390/engproc2025083010 - 13 Jan 2025

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Abstract

In an increasingly digitized environment, the deterioration of cell phone cables has led to a significant environmental impact due to the lack of adequate protection and care. This often results in cell phone charging cables being in poor condition. Cable damage can include [...] Read more.

In an increasingly digitized environment, the deterioration of cell phone cables has led to a significant environmental impact due to the lack of adequate protection and care. This often results in cell phone charging cables being in poor condition. Cable damage can include situations such as dirt accumulation or incorrect bending, leading to breakage. As a result, the objective was determined to design a prototype of a cell phone holder with internal biodegradable cable winding. Ulrich and Eppinger served as the methodological basis for the design, following phases including customer needs identification, setting objective values, product concept generation, concept selection, concept testing, and final specification filtering. A survey of 100 individuals provided valuable data for validating certain metrics. Additionally, two focus groups with 15 users were conducted, two experts were interviewed, and a 72 h usage test was carried out, all supported by the agile Scrum methodology and the Scamper technique, allowing for feedback and validation of the initial concept. The final prototype was modeled in 3D using the Lumion 11 program and physically constructed, ensuring functionality and adaptability of the cell phone and charger. In conclusion, a cell phone holder with a cable winder was designed, facilitating easy transport and prolonging the lifespan of any charger cable. Full article

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9 pages, 1825 KiB

Open AccessProceeding Paper

NevusCheck: A Dysplastic Nevi Detection Model Using Convolutional Neural Networks

by Andreluis Ingaroca-Torres, Lucía Heredia-Moscoso and Alvaro Aures-García

Eng. Proc. 2025, 83(1), 11; https://doi.org/10.3390/engproc2025083011 - 13 Jan 2025

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Abstract

Dysplastic nevi are skin lesions that have distinctive clinical features and are considered risk markers for the development of melanoma, the deadliest type of skin cancer. A specific deep learning technique to identify diseases is convolutional neural networks (CNNs) because of their great [...] Read more.

Dysplastic nevi are skin lesions that have distinctive clinical features and are considered risk markers for the development of melanoma, the deadliest type of skin cancer. A specific deep learning technique to identify diseases is convolutional neural networks (CNNs) because of their great capacity to extract features and classify objects. Therefore, the research aims to develop a model to diagnose dysplastic nevi using a deep learning network whose classification is based on the pre-trained architecture EfficientNet-B7, which was selected for its high classification accuracy and low computational complexity. As for the results obtained, an accuracy of 78.33% was achieved in the classification model. Also, the degree of similarity between the detection by a dermatology expert and the proposed model reached an accuracy of 79.69%. Full article

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8 pages, 6110 KiB

Open AccessProceeding Paper

Remote Control Device for the Detection and Correction of Errors in the FDM 3D Printing Process in Real Time

by Henry Requena, Kelvin Pozuelo, Carlos Díaz and Jean Coll

Eng. Proc. 2025, 83(1), 12; https://doi.org/10.3390/engproc2025083012 - 14 Jan 2025

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This project focuses on developing a remote control device for the real-time detection and correction of errors in fused deposition modeling (FDM) 3D printing. It utilizes a Raspberry Pi computer and a webcam to capture images while a neural network trained with a [...] Read more.

This project focuses on developing a remote control device for the real-time detection and correction of errors in fused deposition modeling (FDM) 3D printing. It utilizes a Raspberry Pi computer and a webcam to capture images while a neural network trained with a dataset generated by the research team identifies errors such as warping, stringing, and spaghetti. Information is efficiently transmitted via MQTT, with instant notifications through Telegram and a user interface. The methodology spans from training the neural network to integrated control strategies with the remote device. Evaluation highlights high precision using confusion matrices and IoU, promising substantial improvements in industrial and critical 3D printing environments. Full article

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