Maestría en Matemática Aplicada

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Modelo matemático para determinar la calidad de servicio en el transporte público urbano en la ciudad de Ambato
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Toscano Ramos, Orlando Ruben; Benalcázar Palacios, Freddy Geovanny
This research is quantitative, descriptive and correlational. The objective was to build a mathematical model that allows determining the quality of the urban public transport service in the city of Ambato in the period 2020 - 2021. The data were obtained through the survey technique with its instrument the questionnaire, the same as applied to 400 users who use public transport in the city of Ambato. To achieve the objectives proposed in the research, the binary logistic regression model was applied, which helps to classify and predict the quality of the urban public transport service in the city of Ambato The variables involved in this research were: as a dependent variable the quality of the service and as predictive or independent variables: the waiting time, the treatment of the user, the current state of the units and the way of driving of the carrier. For the processing and analysis of the data, the Microsoft Excel 2016 program and the free software RStudio version 4.0.1 were used. It is concluded that the constructed logistic regression model correctly adjusts to the predictor variables, the decision frontier yielded by the model was 0.6142 or 61.42%, which is used to determine the quality of the safe and unsafe service. The model correctly classifies 308 observations, of which 205 observations are classified as safe, representing 51.25% of the total data, while 103 observations were classified as unsafe, which is equivalent to 25.75%. With the analysis carried out, it was determined that the urban public transport of the city of Ambato is moderately safe, for which the pertinent authorities should place emphasis on improving the quality of the service.
Modelo matemático basado en las técnicas de detección de bordes y propagación de texturas para restaurar imágenes fotográficas documentales RGB
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Jordán Bolaños, Carlos Rodrigo; Gordón Gallegos, Carlos Diego
EXECUTIVE SUMMARY The restoration of RGB documentary photographic images, using a mathematical model based on two fundamental techniques texture propagation and edge detection seek to give balanced priority to the two techniques, that is, neither should prevail over the other, using the notation for image restoration: I = Image, ɸ = source region. It is the known region of the image, Ω = target region. It is the region to restore and 𝛿Ω = border. RGB (color) documentary photographic images focus on people and social groups, to show aspects of their daily lives and are born with the intention of capturing reality in a still image. Edge detection is a technique that facilitates the identification of image objects and therefore their recognition. If the purpose of edge detection algorithms is to obtain as a result an image where the pixels of those points of the original image where sudden changes in intensity are presented are highlighted. In this respect it is worth highlighting, among others, the techniques related to zero crossing (“Zero crossing”) and level set (“level set”). On the other hand, texture propagation is a technique that consists of building from a small sample image, a large image that preserves the structure of the sample. An important part of the model that is proposed in this work, consists in filling the image by pixels, first of all, you must count on the area to be restored is well defined so that the neighboring textures maintain balance and harmony in the final result. The proposed mathematical model is designed to obtain from the original image, first the gradient of the image followed by the extraction map which is nothing more than the silhouette of the object to be extracted; then the energy map of the image is created to proceed with the removal of seams. Seam after seam will be removed until you create a resulting image similar in size and characteristics to the original. Finally the restoration will be done considering the edges and textures of the original image, with this it will be evaluated if the restored documentary photographic image is visually satisfactory. The similarity criterion to make the comparison between the original and resulting image has to be of mathematical type, that is, an algorithm will compare pixel by pixel the two images showing on screen how efficient the algorithm is. Under the above context it is said that the restoration of images through mathematical modelling seeks to refine the amendment in an intelligent way, that is to say, that at the end of the restore process, the image is visually pleasing to the observer, where the subtraction of elements or the size modification does not harm the harmony of colors, shapes and textures.
Modelo estadístico para la planificación de la producción en una ensambladora de vehículos, mediante la metodología Lean Manufacturing
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Gavidia García, José Luis; Meneses Freire, Manuel Antonio
EXECUTIVE SUMMARY The main objective of this study was to design a statistical model for production planning in a vehicle assembly plant, using the Lean Manufacturing methodology, which covers topics related to the calculation of Takt-Time, focused on the analysis of times and movements, with in order to eliminate downtime, thereby generating an adequate balancing of production lines that are coupled with production planning in the assembly of the HAVAL M4 AC 1.5 5P 4X2 Model vehicle produced by the company Ciauto Cía. Ltda. Initially, the identification of the different assembly processes that are executed in the ten workstations was carried out, in order to carry out the taking of times through the use of a stopwatch, managing to determine the bottleneck within the assembly process of the Model M4, condescending of this condition to manage alternative solutions for a production of eleven units per day. In the analysis of the Installed Capacity (CI) a value of 12 vehicles / day was obtained, this means that the assembler based on its resources, equipment and infrastructure is capable of assembling 6 M4 Models daily, this value confirms that in addition to the Compliance with the production plan set by the assembly coordinator, each batch of M4 corresponding to 30 cars can be assembled in approximately one week and one day, systematically satisfying the demand of the national market. The data from the investigative work highlight the need to provide a statistical tool that guides efficiently and sustainably in the short, medium and long term the planning of production in the assembly area of the company Ciato Cía. Ltda., In order to generate efficient management of resources in a vehicle assembly company.
Modelo matemático de optimización para planeación de redes FTTH a través de programación estocástica multietapa
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Cunalata Landa, Myriam Paola; Salazar Escobar, Fabián Rodrigo
EXECUTIVE SUMMARY In this research project a mathematical optimization model is used for planning FTTH networks through multistage stochastic programming, the method of reduction and construction of scene trees is studied in order to choose the appropriate modeling approach, in addition to define an optimization model for the projection of FTTH telecommunications networks, finally the effectiveness of the new data model obtained from the company FASTER ISP is evaluated. With the mixed methodology used in this project, quantitative and qualitative data are collected, analyzed and combined that allow to achieve the proposed objectives, to reach these objectives the different concepts of FTTH networks, mathematical models, K-means optimization algorithms are studied, Setcover, Dijkstra, Brownian Movement. The use of these algorithms allows to process the information of the clients, reduce the scenarios to find the optimal one, carry out the stochastic projection of the potential clients and find the input and output variables that are used to define the mathematical model that serves as parameters of the objective function, to optimize various resources such as splitters and the number of fiber optic meters. The algorithms used allow identifying the resources and parameters necessary for optimization, on the other hand, it is evident that the inappropriate location of an equipment splitter in the deployment of FTTH networks leads to oversizing or wasting resources. To define the optimization model, variables and restrictions discovered in the information processing were used, it should be added that the model minimizes the cost of investment in resources. The use of the optimization model reduces the cost of planning in a FTTH network by 39%, on the other hand, future lines of research may be the application of the mathematical model in a WIFI network.
Modelo matemático de inventarios en la cadena de suministros y su impacto en la comercialización de productos de fibra acrílica, método Multicriterio ABC
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Toscano Guerrero, Francisco Eduardo; Jurado Lozada, Marco Antonio
ABSTRACT Companies worldwide today compete within the framework of technology and the resources they have, so that the market is always satisfied according to their needs and preferences, it is for this reason that at the national level and punctually at the level Local strategies are established which allow companies to develop in a better way, incorporating in their policies new elements that lead to a better development in the field of product marketing. The problems that affect companies daily make them look for alternative solutions, specifically speaking of inventories as an important capital investment found in assets which entail expenses of materials, administrative personnel, and storage warehouse, which consequently need of practical solutions that allow a balance with the customer and product rotation. The main objective of this study leads to the solution of this problem by incorporating a mathematical model incorporated with a computational application that allows finding solutions to the problem of ordering the products that are in greatest demand in the local and national market, optimizing resources and obtaining a balanced inventory with respect to the rotation of products and managing to raise its level of marketing based on sales. The computational application is a very versatile and practical tool, managing to analyze many elements of various criteria, accelerating the process of selecting the best products based on each of the characteristics that the market prefers, thus maximizing the impact of the marketing of acrylic fiber products from the company "Lanas Elsy". Vilfredo Pareto's ABC classification technique is used in many analyzes at all levels, becoming one of the best alternatives for developing inventories worldwide, combined with the multi-criteria mathematical model and the neglected computational application in C # and Matlab, are part of a very important input for the development of the company.
Simulación de tráfico vehicular en un tramo de la Av. Manuelita Sáenz comprendido entre las calles Pío de Baroja y Antonio Clavijo sector Paseo Shopping Ambato
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Moyolema Chaglla, Ángel Gustavo; Salazar Escobar, Fabián Rodrigo
ABSTRACT The objective of the research is to carry out a simulation of vehicular traffic through the use of free software and a macroscopic model, to optimize the vehicular flow in the section of Avenida Manuelita Sáenz between Pío de Baroja and Antonio Clavijo streets, Paseo Shopping Ambato. The study began with a field phase aimed at collecting data on traffic densities, average traffic speeds and traffic flows in each of the four sub-sections that comprise the road system of interest, on different days and times. Subsequently, a data processing and analysis phase was developed, which aims to present descriptive statistics for the identification of minimum, average and maximum values of each parameter. The third phase consisted in the application of the macroscopic traffic model Lighthill-Whitham-Richards (LWR), solved by means of a numerical solution technique, with the boundary conditions and the incorporation of linear functions that express the speed relationship and the density of traffic, the latter was obtained using regression models. Among the results of the study, it stands out that the highest flows are presented at 6:30 p.m. throughout the section. The highest traffic flow of those registered was 1140 vehicles per hour, for vehicles entering from Av. Manuelita Sáenz, north-south direction towards intersection A. Traffic densities were similar for the four sub-sections, the maximum peak reached being 16 cars per sub-section. Although the section that presents the greatest fluctuation in speed and traffic density is the BA, which denotes that it is the most conflictive, since it restricts the free flow of cars on a more recurrent basis. N simulations were carried out in a period of one hour, taking into account the traffic light times, each simulation represents an event and in the end the cars that would circulate in that time were counted.
Modelado matemático predictivo para la sostenibilidad de los emprendimientos productivos
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Luzuriaga Jaramillo, Héctor Alberto; Ponsot Balaguer, Ernesto Antonio
Executive Summary Models that explain and predict failure and success are very valuable to entrepreneurs in the production sector. The implementation of an explanatory and predictive mathematical - statistical model is presented for the study of the sustainability of productive enterprises in the Cevallos, Quero, Mocha, Patate and Tisaleo cantons of the province of Tungurahua, Ecuador. A logistic regression model is proposed and adjusted on a sample of 1546 entrepreneurs. The variable selection method is stepwise which, following the parsimonious principle, incorporates only the variables that are significant. The deviance goodness-of-fit test suggests that such a model fits the data appropriately. Several hypotheses are checked and discussed, the most important result being the demonstration that there are factors that can be used to explain the success of productive entrepreneurs. These are: Instruction, time of the undertaking, staff, canton and if it has been suspended.
Simulación de pronósticos de ventas en la empresa IMPACTEX mediante redes neuronales
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Llumitasig Galarza, Mayra Cristina; Salazar Escobar, Fabián Rodrigo
In the present research work, the simulation of the sales forecast was carried out in the IMPACTEX company using Artiﬁcial Neural Networks. For which the free Python software was used with the help of the Tensorﬂow and Keras libraries, the data used was historical data obtained from the IMPACTEX company for the years 2008-2019, from which a sales record was obtained by product code. (127 products in total), to carry out the forecast an ABC analysis was carried out that allowed determining the products with the highest demand, obtaining as a result the product BH1060 followed by the product BH7010 located in group A, while in group B the product C585 and group C was made up of product 1112.6. The structure for each neural network was obtained after varying the epoch parameters, the number of layers of the neural network and the number of neurons, the number of hidden layers coinciding in three for the four products used, the number of neurons per layer and epoch. varies depending on the error response obtained in the simulation. The selected parameters generated an error of 2.60 % for product type A (BH1060), for product type A (BH1070) 3.64 %, for product type B (C585) 3.02 % and a 3.27 % error for product C (1112.6)
Implementación de un sistema inteligente para la identificación vehicular
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Cáceres Mayorga, Paúl Alejandro; Reinoso Astudillo, Cristina Isabel
The main objective of this research work was to implement an intelligent system capable of classifying vehicle and automotive license plates, as well as self-correcting recognition errors, for which it was based on the design of an algorithm capable of detecting and classifying vehicles, implementing artificial intelligence. Once the process to be followed was identified, a source code was implemented for the detection of the types of license plates using the convolutional neural network WPOD in which the data of the edge, width and height of the plate were specified so that it only provides the photo of license plate. For the binarization process used in the research, the Otsu algorithm was used, which converts the images into the gray, blur, binary and dilation scales, applying filters that can obtain the location segments of the letters and numbers. Finally, an effective system was obtained, with acceptable detection capacity, since design parameters of the architecture of each type of red were established, which achieved a satisfactory solution to the problem of identification, classification and validation of the characters of Ecuadorian license plates.
Modelo matemático prospectivo para la generación de desechos hospitalarios en el cantón Ambato
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Bastidas Sarabia, Liliana Rocío; Benalcázar Palacios, Freddy Geovanny
This research is descriptive, longitudinal and projective, in order to develop a prospective mathematical model for the generation of hospital waste in the canton of Ambato, through the database of the SIPECA system of the Municipal Public Company for the Integral Management of Solid Waste from Ambato comprised in the period January 2014 to March 2020. In this research, the time series was applied, especially the SARIMA models that are built under the Box-Jenkins methodology. For the analysis and processing of the database, the free software RStudio version 4.0.1 was used and the computer code was also built. It was possible to build a mathematical model that allows to satisfactorily analyze, explain, describe and predict the production of solid hospital waste collected monthly in the Ambato canton. It is concluded that the model that meets the tests of adequacy and randomness is the SARIMA (1, 1, 1) (1, 0, 1) [12] whose forecasting equation is: ΔŶt = -0.326 Yt − 1 + 0.992 Yt − 12 + 0.7882 Ɛt − 1 + 0.8934 Ɛt − 12 + Ɛt, with this model the projections for the period April 2021 to March 2022 were generated. Based on the projections made, it was identified that the security cells for the final disposal of hospital waste occupy an excessive volume in the sanitary landfill, for which it is proposed to use technological equipment such as the autoclave, the same one that helps to treat the waste. solid hospital waste, managing to convert waste into inert waste and reducing its volume by 80%.
Implementación de un sistema predictivo con redes neuronales para el control del comportamiento de la planta Festo MPS-PA
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Soria Mejía, Daysi Maribel; Benalcázar Palacios, Freddy Geovanny
In the present research work, the implementation of a Dynamic Matrix Predictive Controller (DMC) with Neural Networks was carried out for the level control process (liquid) of a Festo Compact Workstation plant of the hydraulics and pneumatics laboratory of the Technical University of Ambato. The dynamics of the plant was found through the training of a feedforward neural network, the training and testing data used were obtained by conducting an experiment that consists of applying different step inputs to the plant and the response of the system to said input. The algorithm implemented was that of a dynamic matrix predictive controller, for which it is necessary to know the mathematical model of the level process represented as a transfer function, said mathematical model was built using the exponential regression method by least squares.
Optimización de los indicadores de productividad de los procesos de manufactura de una empresa láctea mediante la simulación con Flexsim integrando la filosofía Lean Manufacturing
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Flores Cadena, Cristian Andrés; Benalcázar Palacios, Marco Enrique
The objective of this research is to simulate the manufacturing processes of the dairy company Soprab with the integration of the Lean Manufacturing Philosophy. One of the important advantages of simulation is to generate changes in the process without the need to make investments in companies. For the simulation, the data of the manufacturing processes of the yogurt and mozzarella cheese production lines were collected, through an on-site visit of the production plant. During this visit, data was collected on: number of operators, process times, equipment and machinery of the production lines and production batches. The simulation was carried out in the yogurt and mozzarella cheese production lines due to their high demand compared to the other products of the company. For the simulation, the Flexsim program was used, where the data collected in the plant was loaded. The simulation process was validated, with which it is concluded that the simulation carried out reflects the operation of the real process, where the initial productivity indicators were: cycle time equal to 687 min and productivity of 0.88 units / min in the line for making yogurt; while in the mozzarella cheese production line the initial values were: cycle time equal to 2339 min and productivity of 0.427 units / min. Then simulations of the improvement scenarios were carried out, incorporating Lean Manufacturing in the production lines such as: TPM, Poka Yoke, 5 S, elimination of mudas, kaizen and SMED. It was determined that the incorporation of the Lean Manufacturing philosophy did have significant statistical differences in the productivity indicators between the simulated model and the simulated improvement scenarios of the yogurt and mozzarella cheese line. Of the improvement scenarios proposed in the yogurt production line, the incorporation of 5 S is the best scenario because it reduces the cycle time to 620.3 min and productivity of 0.966 units / min. While in the mozzarella cheese production line, the scenario with the standardization of processes was the best with a reduction of the cycle time to 2185 min and a productivity of 0.450 units / min. In the yogurt production line, cycle time was reduced by 9.68% and productivity increased by 10.27%. While in the cheese making line, the cycle time was reduced by 6.58% and productivity increased by 6.79%. In the yogurt production line, the company obtains a daily income of $ 2700 from the sale of 2L yogurt, while with the improvement proposal it could increase production and generate sales of $ 2992, increasing income by 10 , 81%. While in the mozzarella cheese production line, daily income of around $ 375 is obtained from the sale of 250 g mozzarella cheese, and with the improvement proposal it could increase the income to $ 478, increasing the income around 27, 47%.
Diseño de un modelo matemático para estimar la deserción estudiantil mediante técnicas de análisis multivariado en una institución de educación superior tecnológica
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Vinueza López, Cristina Nataly; Loza Aguirre, Edison Fernando
EXECUTIVE SUMMARY In this research, a logistic regression model was used to estimate student dropout from the IST Luis A. Martínez Agronómico. The data of 849 students registered in the institute between 2018 and 2020 was used to build the model. The independent variables considered for the model were: gender, marital status, age, career, repetition, occupation and economic status. We used the KDD methodology to estimate the mathematical model, which allows generating information from a database with the records to be studied. In the evaluated period, 82.45 percent of the students did not dropout but 17.55 percent did it. In the study, four logistic regression models were established, the first one includes all the independent variables but only the ‘career’ variable was significant. The ‘age’ and ‘gender’ variables were eliminated (higher p-value) for generating a second logistic regression model, where the ‘repetition’ and ‘career’ variables were considered significant. Subsequently, the highest p-value variables, ‘marital status’ and ‘economic status’ were eliminated for obtaining a third logistic regression model wherein the ‘repetition’ and ‘career’ variables were the only significant ones. Finally, it was chosen the logistic regression model 4, which only includes the career and repetition variables as the only significant ones. The null hypothesis was rejected because the coefficients Beta 1 and Beta 2 of the variables ‘career’ and ‘repetition’ aren´t zero. The logistic regression model 4 correctly classified 83 percent of the training data and 79 percent of the test data. Additionally, we build a prediction model based on decision trees, which established ‘career’ as a unique explanatory variable. The F1_Score value of the logistic regression model 4 was higher than the F1_Score value of the decision tree model.
Modelo matemático de la producción de la empresa Salinerito en la Provincia Bolívar
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Sánchez Verdezoto, Carlos Alfredo; Benalcázar Palacios, Freddy Geovanny
EXECUTIVE SUMMARY The present research work is descriptive, predictive and longitudinal with a trend. The objective was to develop a mathematical model for the production of the company Confites El Salinerito in the Bolívar province, from the production values in the period from January 2017 to July 2020, the data were obtained directly from the company. To achieve the research objectives, the methodology proposed by Box-Jenkins was applied, which describes the characteristics of the time series in terms of trend, seasonality and stationarity; The free software RStudio version 4.0.1 was applied for the estimation of the parameters, the processing and the analysis of the data. It was concluded that the mathematical model that most accurately adjusts to the production values of the company was SARIMA (1, 1, 1) (1, 1, 1) 12, the same one that allowed making the monthly production forecasts for the period from August 2020 to January 2021. The results obtained by the developed model and the methodology used by the company to establish its monthly production were also compared.
Modelo estadístico para valorar las líneas de transporte público de pasajeros en la ciudad de Riobamba
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Londo Yachambáy, Fabián Patricio; Meneses Freire, Manuel Antonio
EXECUTIVE ABSTRACT Public passenger transport is considered an inefficient service in Ecuador and therefore in the city of Riobamba, although there have been attempts on several occasions to achieve high levels of safety, comfort and quality, there is almost nothing that could be improved. Faced with this problem, it is about applying a statistical model that allows me to assess public passenger transport, for which an analysis was carried out in three axes that involve this means of transport, such as Infrastructure, ascent and descent of passengers and quality of service applying the survey technique and use of a questionnaire to obtain information, with which variables were obtained that helped to build my Multinomial Logit model.
Modelo de predicción de riesgos psicosociales en el transporte urbano de pasajeros usando técnicas de Inteligencia Artificial
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Lara Satán, Amado Antonio; Loza Aguirre, Edison Fernando
EXECUTIVE SUMMARY The city bus driver job ranks among the highest risk and most stressful modern occupations. Modern technologies provides greater autonomy and work flexibility, however they also expose drivers to psychosocial risks, which leads to work stress. Consequently, the early prediction of stress and their associated risk, would contribute to make preventive decisions. The objective of this study is to develop a model that allows predicting psychosocial risks in urban passenger transport in the city of Ambato, applying supervised machine learning techniques. For this purpose, we used data set of occupational psychosocial risk of urban bus drivers obtained with the Fpsico 4.0 questionnaire. The study applies the methodology for the identification, analysis, and evaluation of psychosocial risks of the INSHT of Spain and the Cross Industry Standard Process for Data Mining (CRISP-DM) framework. The classification is performed with the three non-parametric supervised algorithms: k-nearest neighbors, decision trees and support vector machine. The evaluation metrics of the algorithms used are the Jaccard index and F1-score. The experimental results show that the support vector machine model shows better performance with an F1 score of 93 percent and the Jaccard score of 87 percent.
Diseño de un modelo matemático para optimizar las rutas de recorrido del proceso de recolección de desechos sólidos para el Cantón Valencia
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Escudero Andino, Flavio Fernando; Ponsot Balaguer, Ernesto Antonio
Executive Summary The optimal urban waste collection route for the canton of Valencia in the province of Los Ríos, Ecuador is presented. A version of the integer linear programming model is selected, known as the “traveling salesman problem”, in which the start and return points do not necessarily coincide. A prior quantitative and graphic analysis of the available data is carried out using the program for geographic information systems QGis and the Pandas library for data management in Python. A strategy is discussed in which the sector under study is divided into five collection groups, made up according to the algorithm known as “k-Means ”. The proposed solution shows to be adjusted to reality and, although it does not imply a substantive decrease in intra-urban routes, since the scale of the problem is very small, it does produce a decrease in operating costs of the order of 18.15 percent, compared with the current situation.
Modelación matemática para un control robusto de la planta Festo MPS-PA Compact Workstation mediante la normativa IEC-61499
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Bustos Pulluquitin, Sergio Patricio; García Sánchez, Marcelo Vladimir
In the present research work, the implementation of a GPC control with restrictions was carried out in a FESTO MPS-PA CompactWorkstation level plant through the modeling of function blocks, thus obtaining an industrial control application with decentralized logic which is one of the objectives of the IEC 61499 standard. The IDE used compatible with IEC 61499 was the 4DIAC IDE and the runtime environment (runtime) 4DIAC FORTE, in addition the BBB card was used for reading and writing data from sensors and actuators respectively. The mathematical model of the level plant represented as a transfer function was found by two methods: the first using linear differential equations and the second using experimental data of the response to the step of a first order system. Three types of restrictions were implemented: in the control increment ( Delta u(t)) to avoid unnecessary efforts in the actuator and the output restrictions (y(t)) and control (u(t)) that will prevent damage to the plant, the GQPA algorithm was used to optimize the objective function.
Estudio de los modelos de regresión paramétricos polinomiales y modelos de regresión no paramétricos B-Splines. Aplicaciones en ingeniería
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Toalombo Rojas, Byron Miguel; Meneses Freire, Manuel Antonio
The study of polynomial parametric regression models and non-parametric B-Splines regression models is carried out based on particular applications in engineering. The cases considered are a car against the bus bodywork crash simulation as part of the structural design and the relationship of the climatological variables in the weather station of San Antonio de Pichincha. A non-experimental cross-sectional methodological design is made, being a correlational type of research. The appropriate regression models for each relationship are established with the use of R software and taking into account the criteria: rejection of the nullity of the coefficients of the models by Student's t-hypothesis test, the validity of the models by Snedecor's F test of the ANOVA table, the goodness of fit, 95% confidence intervals, and compliance with the assumptions of normal distribution, no autocorrelation, and homoscedasticity of the residuals for the polynomial regression (Shapiro-Wilk, Kolmogorov-Smirnov corrected by Lilliefors, Durbin-Watson and Breusch-Pagan tests, respectively). The Wilcoxon nonparametric test was used to select the most suitable regression model based on the lengths of the confidence intervals. Based on the results obtained, the polynomial parametric regression models fit well when the curves have a parabolic shape or follow a pattern without abrupt changes in curvature. It means the model can define better to the relationships of the vehicle impact simulation that have the speed of the impacting vehicle as an explanatory variable. In contrast, the nonparametric Bsplines regression models provide a better fit when the curves are bell-shaped with more abrupt curvature changes.This model can adapt better to the conditions of the climatological variables as a function of the time of day
Modelo Matemático para la programación de la producción de Eva Foamy en el área de acabados de la Empresa Plasticaucho
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021-06) Castro Mayorga, Maritza Elizabeth; Reinoso Astudillo, Cristina Isabel
EXECUTIVE SUMMARY Given the internationalization of the world economy and the growing need for organizations to compete in global markets, it is necessary for production scheduling to be supported by mathematical models that allow for more objective when deciding what, how and when to produce. Manufacturing companies have traditionally focused their management on quality, efficiency and productivity; currently it is necessary that the manufacturing processes also offer differentiation in the product and service perceived by the client: reliability and flexibility in delivery times and batch sizes; however, the purpose of any business, which is to generate profitability, should not be lost sight of. Globalization fosters greater dynamism and competitiveness in the markets, this leads industries to generate strategic plans in all their areas, especially in manufacturing to optimize resources; The management of resources are directly related to the planning and programming department since they are the link between the sales department and the production plant, therefore it is essential that planning is involved in the projects that production raises to optimize the resources. In the finishing process that is carried out in the Plasticaucho Industrial Plant of Various Industries, the production scheduling is carried out according to the order entry without considering the costs and benefits, for this reason the study was carried out and the inclusion of a mathematical model in production scheduling. The first step consisted of identifying the products that are manufactured in the finishing area, subsequently the production costs, costs of maintaining inventories, profit per product, standards, inventories of finished products were documented, then the restrictions of non-negativity and process to finally develop the mathematical model that will allow to program production based on costs to obtain the highest profitability in the production line.