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Optimization of Textile SCs Design and Planning: A Bibliometric Analysis
(Springer Nature Switzerland, 2025)
Leandro L. Lorente-Leyva
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María del Mar Eva Alemany
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Diego H. Peluffo-Ordóñez
This study provides a comprehensive overview of the current state of research in the design and operations planning optimization of textile supply chains. This paper includes a bibliometric analysis of 42 selected papers that reveals a focus on tactical decision-making, with an emphasis on the manufacturing stage. The bibliometric analysis exposes the influence of prominent authors and journals in this field. A co-occurrence map graphically represents the keywords used in the papers. The literature review results suggest that models are primarily developed in a deterministic context, with a focus on cost minimization and limited use of artificial intelligence techniques. The solution context exhibits a preference for static approaches and periodic replanning.
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Automation of Filter Press Drive Control for Enhanced Palm Oil Extraction
(International Information and Engineering Technology Association, 2025-01-31)
CORDOVES GARCIA, ALEXIS
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Agustín Moreira Orellana
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Alexis Cordovés Rodríguez
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Ricardo Avila Rondon
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Leandro L. Lorente-Leyva
The study focuses on the automation of the drive system of a filter press in palm oil extraction plants, with the aim of optimizing operational efficiency, reducing manual intervention and improving process accuracy. The proposal replaces the manual drive with a motorized system controlled by a Programmable Logic Controller (PLC). A Siemens motor-reducer, model Z79-LE112MC4P-G040M-PN, was used, which guarantees a torque of 777.75 Nm and an output speed of 40 rpm, sufficient to efficiently tighten and release the filter press. The system control was implemented by a Siemens LOGO 230RC PLC, complemented by an AM2 analog expansion module to interpret strain gauge signals. These signals determine the exact moment to stop the motor-reducer once the programmed tightening force is reached. Programming was done in Ladder language using LOGOCONFORT software. The integration of these components improves system consistency and reliability, standardising processing times and reducing physical effort. The results highlight an increase in productivity and operational safety, aligning with modernisation trends in the palm oil industry. This advance represents a significant step towards greater sustainability and competitiveness of the sector.
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Data-enabled Bayesian inference for strategic maintenance decisions in industrial operations
(Elsevier BV, 2024-12)
Raúl Torres-Sainz
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Leandro L. Lorente-Leyva
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Yorley Arbella-Feliciano
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Carlos Alberto Trinchet-Varela
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Lidia María Pérez-Vallejo
Efficient management of industrial assets and equipment depends heavily on the selection of appropriate maintenance strategies. This research presents a dataset generated through Monte Carlo simulations to evaluate 12 key criteria relevant to maintenance strategy selection. The dataset covers a wide range of potential maintenance scenarios, providing comprehensive data for researchers to explore various strategies in industrial settings. The data were normalized and structured in a way that facilitates their use for further modeling or analysis. The dataset offers an opportunity for researchers to reproduce the data collection process, enabling comparisons with their own studies. By providing this dataset, we aim to support the development of new models for maintenance strategy selection and encourage further exploration of data-driven approaches in industrial maintenance. Additionally, the dataset can serve educational purposes, assisting in the teaching of decision-making in the context of maintenance operations.
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Control of Pollutant Emissions from a Boiler Through the Percentage of Oxygen
(International Information and Engineering Technology Association, 2021-06-25)
CORDOVES GARCIA, ALEXIS
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Carlos A. Pérez Alban
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Jorge R. Terán Benalcázar
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Alexis Cordovés Rodríguez
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Leandro L. Lorente-Leyva
<jats:p>The goal of this paper is to obtain an automated system for the control of the quality of the combustion gases of a boiler. The concentration of oxygen present in the combustion gases is detected by means of a lambda sensor, and a proportional PID controller automatically regulates, through an actuator, the air inlet to the boiler, thus ensuring the emission of CO2 and other polluting gases into the atmosphere within the parameters established by the current environmental regulations. The control system has an HMI display and a modular PLC. The results achieved also ensure the reduction of fuel consumption of the boiler.</jats:p>
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A Novel Linear-Model-Based Methodology for Predicting the Directional Movement of the Euro-Dollar Exchange Rate
(Institute of Electrical and Electronics Engineers (IEEE), 2023)
Mauricio Argotty-Erazo
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Antonio Blázquez-Zaballos
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Carlos A. Argoty-Eraso
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Leandro L. Lorente-Leyva
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Nadia N. Sánchez-Pozo
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Pineapple Drying Analysis in Packing Plants Through Computational Fluid Dynamics
(International Information and Engineering Technology Association, 2022-02-28)
CORDOVES GARCIA, ALEXIS
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Alexis Cordovés Rodríguez
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Karla Tatiana Núñez Buñay
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Arlys M. Lastre Aleaga
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Leandro L. Lorente-Leyva
The aim of this research is to determine the average fluid velocity values and the average total pressure at the outlet of the ventilation system conduit for the drying, by air impulsion, of pineapples in packing plants, in order to ensure the required humidity level of the crown for its proper packaging. The CAD model of the air conduction was obtained in Solidworks and Computational Fluid Dynamics (CFD) techniques were applied to simulate the performance of the ventilation system. Air was indicated as the type of fluid, and an internal analysis of the pipe with roughness Rz = 3.2 μm. As a computational domain, the pipeline was established, from the connection to the fan to the outlet diffuser. As boundary conditions were established; a W and Z Manufacturing regenerative fan at the inlet of the flow pipe 618,439 m3/h, and at the outlet of the pipe the value of atmospheric pressure. As a result of the simulation, an average velocity value at the diffuser outlet of 127.294 m/s was obtained, higher than the required 96.06 m/s. An average total pressure value of 111718.73 Pa was obtained in the conduit suitable for the proposed purposes. For the conveyor belt, it is recommended to use, in each row of pineapples, the simulated fan with a simple diffuser with a rectangular section of 1 x 20 cm, or a regenerative fan with a flow of 1248.77 m3/h and a diffuser with two-outlet bifurcation.</jats:p>
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Design and Implementation of an IoT Control and Monitoring System for the Optimization of Shrimp Pools using LoRa Technology
(The Science and Information Organization, 2023)
José M. Pereira Pontón
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Verónica Ojeda
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Víctor Asanza
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Leandro L. Lorente-Leyva
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Diego H. Peluffo-Ordóñez
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Myoelectric Prosthesis Using Sensor Fusion Between Electromyography and Pulse Oximetry Signals
(International Information and Engineering Technology Association, 2023-08-31)
Karen Torres
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Jhon Espinoza
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Víctor Asanza
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Leandro L. Lorente-Leyva
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Diego H. Peluffo-Ordóñez
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A 3D Printed, Bionic Hand Powered by EMG Signals and Controlled by an Online Neural Network
(MDPI AG, 2023-06-14)
Karla Avilés-Mendoza
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Neil George Gaibor-León
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Víctor Asanza
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Leandro L. Lorente-Leyva
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Diego H. Peluffo-Ordóñez
<jats:p>About 8% of the Ecuadorian population suffers some type of amputation of upper or lower limbs. Due to the high cost of a prosthesis and the fact that the salary of an average worker in the country reached 248 USD in August 2021, they experience a great labor disadvantage and only 17% of them are employed. Thanks to advances in 3D printing and the accessibility of bioelectric sensors, it is now possible to create economically accessible proposals. This work proposes the design of a hand prosthesis that uses electromyography (EMG) signals and neural networks for real-time control. The integrated system has a mechanical and electronic design, and the latter integrates artificial intelligence for control. To train the algorithm, an experimental methodology was developed to record muscle activity in upper extremities associated with specific tasks, using three EMG surface sensors. These data were used to train a five-layer neural network. the trained model was compressed and exported using TensorflowLite. The prosthesis consisted of a gripper and a pivot base, which were designed in Fusion 360 considering the movement restrictions and the maximum loads. It was actuated in real time thanks to the design of an electronic circuit that used an ESP32 development board, which was responsible for recording, processing and classifying the EMG signals associated with a motor intention, and to actuate the hand prosthesis. As a result of this work, a database with 60 electromyographic activity records from three tasks was released. The classification algorithm was able to detect the three muscle tasks with an accuracy of 78.67% and a response time of 80 ms. Finally, the 3D printed prosthesis was able to support a weight of 500 g with a safety factor equal to 15.</jats:p>
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Condition Monitoring of Wind Turbines: A Case Study of the Gibara II Wind Farm
(International Information and Engineering Technology Association, 2023-04-30)
Yorley Arbella-Feliciano
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Carlos A. Trinchet-Varela
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Leandro L. Lorente-Leyva
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Diego H. Peluffo-Ordóñez

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