Pub Date : 2021-11-02DOI: 10.11144/javeriana.iyu26.ortp
Eduard Gañan-Cardenas, Jorge Isaac Pemberthy-Ruiz, Juan Carlos Rivera-Agudelo, Maria Clara Mendoza- Arango
Objective: The objective of this work is to build a prediction model for Operating Room Time (ORT) to be used in an intelligent scheduling system. This prediction is a complex exercise due to its high variability and multiple influential variables. Materials and methods: We assessed a new strategy using Latent Class Analysis (LCA) and clustering methods to identify subgroups of procedures and surgeries that are combined with prediction models to improve ORT estimates. Three tree-based models are assessed, Classification and Regression Trees (CART), Conditional Random Forest (CFOREST) and Gradient Boosting Machine (GBM), under two scenarios: (i) basic dataset of predictors and (ii) complete dataset with binary procedures. To evaluate the model, we use a test dataset and a training dataset to tune parameters. Results and discussion: The best results are obtained with GBM model using the complete dataset and the grouping variables, with an operational accuracy of 57.3% in the test set. Conclusion: The results indicate the GBM model outperforms other models and it improves with the inclusion of the procedures as binary variables and the addition of the grouping variables obtained with LCA and hierarchical clustering that perform the identification of homogeneous groups of procedures and surgeries.
{"title":"Operating Room Time Prediction: An Application of Latent Class Analysis and Machine Learning","authors":"Eduard Gañan-Cardenas, Jorge Isaac Pemberthy-Ruiz, Juan Carlos Rivera-Agudelo, Maria Clara Mendoza- Arango","doi":"10.11144/javeriana.iyu26.ortp","DOIUrl":"https://doi.org/10.11144/javeriana.iyu26.ortp","url":null,"abstract":"Objective: The objective of this work is to build a prediction model for Operating Room Time (ORT) to be used in an intelligent scheduling system. This prediction is a complex exercise due to its high variability and multiple influential variables. Materials and methods: We assessed a new strategy using Latent Class Analysis (LCA) and clustering methods to identify subgroups of procedures and surgeries that are combined with prediction models to improve ORT estimates. Three tree-based models are assessed, Classification and Regression Trees (CART), Conditional Random Forest (CFOREST) and Gradient Boosting Machine (GBM), under two scenarios: (i) basic dataset of predictors and (ii) complete dataset with binary procedures. To evaluate the model, we use a test dataset and a training dataset to tune parameters. Results and discussion: The best results are obtained with GBM model using the complete dataset and the grouping variables, with an operational accuracy of 57.3% in the test set. Conclusion: The results indicate the GBM model outperforms other models and it improves with the inclusion of the procedures as binary variables and the addition of the grouping variables obtained with LCA and hierarchical clustering that perform the identification of homogeneous groups of procedures and surgeries.","PeriodicalId":39036,"journal":{"name":"Ingenieria y Universidad","volume":"98 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81090589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-02DOI: 10.11144/javeriana.iyu26.islc
Diego Mendez-Chaves, Manuel Perez, Alejandro Farfan, E. Gerlein
In order to properly monitor the health status of the hydrological resources of a region, in terms of water contamination, a scalable and low-cost system is necessary to map the water quality at different locations and allow the prioritization of more sophisticated and expensive monitoring campaigns on those areas where a suspicious behavior seems to be occurring. This paper presents the design and implementation process of such an IoT-based solution for low-cost and scalable water quality monitoring applications. To achieve that end, we propose the utilization of a low-cost inter-digital capacitance (IDC) sensor to characterize the conductivity of the water, a very telling parameter about the level of pollution in the water. Additionally, an embedded method to measure such sensor was designed and implemented, which considers the requirements of a portable platform: low computational capabilities, small memory and low power consumption. Our results show that an IDC sensor is capable of detecting the changes of the capacitance of the sample, and therefore mapping the changes in the conductivity of the water. Additionally, integrating an embedded measuring method is a valid option for in-situ characterization of water samples and the complete solution enables a new paradigm for water quality monitoring in large scale scenarios.
{"title":"IDC Sensor for Low-Cost Water Quality Monitoring Applications","authors":"Diego Mendez-Chaves, Manuel Perez, Alejandro Farfan, E. Gerlein","doi":"10.11144/javeriana.iyu26.islc","DOIUrl":"https://doi.org/10.11144/javeriana.iyu26.islc","url":null,"abstract":"In order to properly monitor the health status of the hydrological resources of a region, in terms of water contamination, a scalable and low-cost system is necessary to map the water quality at different locations and allow the prioritization of more sophisticated and expensive monitoring campaigns on those areas where a suspicious behavior seems to be occurring. This paper presents the design and implementation process of such an IoT-based solution for low-cost and scalable water quality monitoring applications. To achieve that end, we propose the utilization of a low-cost inter-digital capacitance (IDC) sensor to characterize the conductivity of the water, a very telling parameter about the level of pollution in the water. Additionally, an embedded method to measure such sensor was designed and implemented, which considers the requirements of a portable platform: low computational capabilities, small memory and low power consumption. Our results show that an IDC sensor is capable of detecting the changes of the capacitance of the sample, and therefore mapping the changes in the conductivity of the water. Additionally, integrating an embedded measuring method is a valid option for in-situ characterization of water samples and the complete solution enables a new paradigm for water quality monitoring in large scale scenarios.","PeriodicalId":39036,"journal":{"name":"Ingenieria y Universidad","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77990335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.11144/javeriana.iued26.ompp
Sepideh Abolghasem, Nicolás Mancilla-Cubides
Modern production process is accompanied with new challenges in reducing the environmental impacts related to machining processes. The turning process is a manufacturing process widely used with numerous applications for creating engineering components. Accordingly, many studies have been conducted in order to optimize the machining parameters and facilitate the decision-making process. This work aims to optimize the quality of the machined products (surface finish) and the productivity rate of the turning manufacturing process. To do so, we use Aluminum as the material test to perform the turning process with cutting speed, feed rate, depth of cut, and nose radius of the cutting tool as our design factors. Product quality is quantified using surface roughness (R_a) and the productivity rate based on material removal rate (MRR). We develop a predictive and optimization model by coupling Artificial Neural Networks (ANN) and the Particle Swarm Optimization (PSO) multi-function optimization technique, as an alternative to predict the model response (R_a) first and then search for the optimal value of turning parameters to minimize the surface roughness (R_a) and maximize the material removal rate (MRR). The results obtained by the proposed models indicate good match between the predicted and experimental values proving that the proposed ANN model is capable to predict the surface roughness accurately. The optimization model PSO has provided a Pareto Front for the optimal solution determining the best machining parameters for minimum R_a and maximum MRR. The results from this study offer application in the real industry where the selection of optimal machining parameters helps to manage two conflicting objectives, which eventually facilitate the decision-making process of machined products.
{"title":"Optimization of Machining Parameters for Product Quality and Productivity in Turning Process of Aluminum","authors":"Sepideh Abolghasem, Nicolás Mancilla-Cubides","doi":"10.11144/javeriana.iued26.ompp","DOIUrl":"https://doi.org/10.11144/javeriana.iued26.ompp","url":null,"abstract":"Modern production process is accompanied with new challenges in reducing the environmental impacts related to machining processes. The turning process is a manufacturing process widely used with numerous applications for creating engineering components. Accordingly, many studies have been conducted in order to optimize the machining parameters and facilitate the decision-making process. This work aims to optimize the quality of the machined products (surface finish) and the productivity rate of the turning manufacturing process. To do so, we use Aluminum as the material test to perform the turning process with cutting speed, feed rate, depth of cut, and nose radius of the cutting tool as our design factors. Product quality is quantified using surface roughness (R_a) and the productivity rate based on material removal rate (MRR). We develop a predictive and optimization model by coupling Artificial Neural Networks (ANN) and the Particle Swarm Optimization (PSO) multi-function optimization technique, as an alternative to predict the model response (R_a) first and then search for the optimal value of turning parameters to minimize the surface roughness (R_a) and maximize the material removal rate (MRR). The results obtained by the proposed models indicate good match between the predicted and experimental values proving that the proposed ANN model is capable to predict the surface roughness accurately. The optimization model PSO has provided a Pareto Front for the optimal solution determining the best machining parameters for minimum R_a and maximum MRR. The results from this study offer application in the real industry where the selection of optimal machining parameters helps to manage two conflicting objectives, which eventually facilitate the decision-making process of machined products.","PeriodicalId":39036,"journal":{"name":"Ingenieria y Universidad","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88693182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-12DOI: 10.11144/javeriana.iued25.bpaw
H. Sánchez, Wilmer Ponce, B. Brito, W. Viera, R. Baquerizo, M. Riera
Objective: To obtain biofilms from starch and cellulose present in the avocado (Persea americana) peel and seed. Materials and methods: The starch characterization included humidity, gelatinization temperature, paste clarity, absorption index, solubility index, swelling power, amylose, amylopectin, amount, and starch yield. Five mixtures were made with 3 g of starch, 5 mL of 30 % NaOH (w/v), 3 g of cellulose, and different proportions for glycerin: 2 g; 2.5 g; 3 g; 3.5 g; 4 g, and PVA: 2 g, 3 g, 4 g, 5 g, and 6 g. Films were formed on acrylic plates, using the casting method. The bioplastic was characterized in terms of moisture, solubility in water, density, thickness, biodegradability, stress, deformation, and modulus of elasticity. Results and discusión: The addition of cellulose to the mixture does not contribute to film formation, unlike PVA which did. The film had the best physical appearance with a mixture of 2 g of glycerin and 6 g of PVA. The bioplastic characterization was 23.43 % humidity, 39.39 % for water solubility, 1.52 g/cm3 density, 0.58 mm thickness, 21.03 % weight loss for the biodegradability test, 1.53 MPa for tension, 21.25 % deformation, and 10,04 MPa for the modulus of elasticity. Conclusions: The bioplastic obtained did not show the resistance of traditional plastic. However, the results obtained serve as a starting point for the realization of other formulations, aimed at producing a bioplastic capable of competing with its synthetic relatives.
{"title":"Biofilms Production from Avocado Waste","authors":"H. Sánchez, Wilmer Ponce, B. Brito, W. Viera, R. Baquerizo, M. Riera","doi":"10.11144/javeriana.iued25.bpaw","DOIUrl":"https://doi.org/10.11144/javeriana.iued25.bpaw","url":null,"abstract":"Objective: To obtain biofilms from starch and cellulose present in the avocado (Persea americana) peel and seed. Materials and methods: The starch characterization included humidity, gelatinization temperature, paste clarity, absorption index, solubility index, swelling power, amylose, amylopectin, amount, and starch yield. Five mixtures were made with 3 g of starch, 5 mL of 30 % NaOH (w/v), 3 g of cellulose, and different proportions for glycerin: 2 g; 2.5 g; 3 g; 3.5 g; 4 g, and PVA: 2 g, 3 g, 4 g, 5 g, and 6 g. Films were formed on acrylic plates, using the casting method. The bioplastic was characterized in terms of moisture, solubility in water, density, thickness, biodegradability, stress, deformation, and modulus of elasticity. Results and discusión: The addition of cellulose to the mixture does not contribute to film formation, unlike PVA which did. The film had the best physical appearance with a mixture of 2 g of glycerin and 6 g of PVA. The bioplastic characterization was 23.43 % humidity, 39.39 % for water solubility, 1.52 g/cm3 density, 0.58 mm thickness, 21.03 % weight loss for the biodegradability test, 1.53 MPa for tension, 21.25 % deformation, and 10,04 MPa for the modulus of elasticity. Conclusions: The bioplastic obtained did not show the resistance of traditional plastic. However, the results obtained serve as a starting point for the realization of other formulations, aimed at producing a bioplastic capable of competing with its synthetic relatives.","PeriodicalId":39036,"journal":{"name":"Ingenieria y Universidad","volume":"118 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77384994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-12DOI: 10.11144/javeriana.iued25.rcsc
Luis Felipe Ariza-Vesga, Johan Sebastian Eslava-Garzon
The objective of this paper is to extend into the OpenAirInterface platform the Coordinated Scheduling (CS) technique to allocate resource blocks among User Equipment (UE) in a wisely way and to control the energy efficiency, the throughput, and the inter-cell interference for Cloud Radio Access Networks (C-RANs). It is achieved by modifying the OpenAirInterface scheduler code, increasing the Remote Radio Unit (RRU) scalability, and employing some component carriers of the Radio Cloud Center (RCC), each one them with one or more UEs. The hardware utilized is composed of general-purpose processors and fast Ethernet transport ports, and the software is recent frequency-domain methodologies in a software-only environment where the use of radio units are not required. However, the USRP B200 mini-i radio unit and the UE (Samsung Galaxy S8) were considered only for validation purposes. The emulations using frequency-domain methodologies, compatible with fourth and fifth-generation cellular systems, allowed real-time emulations and reduced 10-fold the multipath channel’s signal processing complexity compared to time-domain methodologies. The results show we can emulate a real-time static coordinated scheduling proof-of-concept for one C-RAN composed of one RCC, three RRUs, and three UEs. In the end, it is evaluated the reproducibility and the scalability of synthetic networks composed of one RRU and at least one UE, without using software-defined radio units, reducing prototyping uncertainties of the physical hardware and the total price of the experiment.
{"title":"Real-time Coordinated Scheduling for Cloud Radio Access Networks in a Software-only Environment using the OpenAirInterface Platform","authors":"Luis Felipe Ariza-Vesga, Johan Sebastian Eslava-Garzon","doi":"10.11144/javeriana.iued25.rcsc","DOIUrl":"https://doi.org/10.11144/javeriana.iued25.rcsc","url":null,"abstract":"The objective of this paper is to extend into the OpenAirInterface platform the Coordinated Scheduling (CS) technique to allocate resource blocks among User Equipment (UE) in a wisely way and to control the energy efficiency, the throughput, and the inter-cell interference for Cloud Radio Access Networks (C-RANs). It is achieved by modifying the OpenAirInterface scheduler code, increasing the Remote Radio Unit (RRU) scalability, and employing some component carriers of the Radio Cloud Center (RCC), each one them with one or more UEs. The hardware utilized is composed of general-purpose processors and fast Ethernet transport ports, and the software is recent frequency-domain methodologies in a software-only environment where the use of radio units are not required. However, the USRP B200 mini-i radio unit and the UE (Samsung Galaxy S8) were considered only for validation purposes. The emulations using frequency-domain methodologies, compatible with fourth and fifth-generation cellular systems, allowed real-time emulations and reduced 10-fold the multipath channel’s signal processing complexity compared to time-domain methodologies. The results show we can emulate a real-time static coordinated scheduling proof-of-concept for one C-RAN composed of one RCC, three RRUs, and three UEs. In the end, it is evaluated the reproducibility and the scalability of synthetic networks composed of one RRU and at least one UE, without using software-defined radio units, reducing prototyping uncertainties of the physical hardware and the total price of the experiment.","PeriodicalId":39036,"journal":{"name":"Ingenieria y Universidad","volume":"157 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74152764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-22DOI: 10.11144/javeriana.iued25.rlld
Carol Brigitte Hernández Rodríguez, A. Gutierrez-Malaxechebarria, Carlos Alfonso Zafra Mejía
Objective: The aim of this paper is to present a review of specific cases that reported lead concentrations in blood, objects, food, soil, bioindicators, air, and water in specific places in Colombia and evaluate the reported concentrations against target values. Materials and Methods: A systematic qualitative literature review of publications between 1995 and 2019 was done; using Boolean operators 1571 papers were identified, to which 3 inclusion and 4 exclusion criteria were applied. A total of 57 studies met the defined criteria. The reports in these studies were geo-localized and compared with acceptable values. Results and Discussion: Results suggest that lead is present in all environmental matrices, widely distributed in the Colombian territory, and that 72 % of the cases exceeded regulation limits. The percentage of noncompliance per environmental matrix was 89 % for blood samples, 71 % in food, 63 %, in soil, 89 % for bioindicators, 60 % for air, and 55 % for water. Conclusion: These results show that lead pollution is a large-scale problem in the country, more systematic studies are needed, and control measures, policy-making and regulatory updating should be pursued.
{"title":"Reported Lead Levels in Different Environmental Matrices in Colombia","authors":"Carol Brigitte Hernández Rodríguez, A. Gutierrez-Malaxechebarria, Carlos Alfonso Zafra Mejía","doi":"10.11144/javeriana.iued25.rlld","DOIUrl":"https://doi.org/10.11144/javeriana.iued25.rlld","url":null,"abstract":"Objective: The aim of this paper is to present a review of specific cases that reported lead concentrations in blood, objects, food, soil, bioindicators, air, and water in specific places in Colombia and evaluate the reported concentrations against target values. Materials and Methods: A systematic qualitative literature review of publications between 1995 and 2019 was done; using Boolean operators 1571 papers were identified, to which 3 inclusion and 4 exclusion criteria were applied. A total of 57 studies met the defined criteria. The reports in these studies were geo-localized and compared with acceptable values. Results and Discussion: Results suggest that lead is present in all environmental matrices, widely distributed in the Colombian territory, and that 72 % of the cases exceeded regulation limits. The percentage of noncompliance per environmental matrix was 89 % for blood samples, 71 % in food, 63 %, in soil, 89 % for bioindicators, 60 % for air, and 55 % for water. Conclusion: These results show that lead pollution is a large-scale problem in the country, more systematic studies are needed, and control measures, policy-making and regulatory updating should be pursued.","PeriodicalId":39036,"journal":{"name":"Ingenieria y Universidad","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86568959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-17DOI: 10.11144/javeriana.iued25.rasp
M. Becerra-Fernández, Milton M. Herrera, C. Trejos, O. R. Romero
Objective: Calculate the required personnel and resources needed to fulfill the service promise agreed with the customer. Methods and materials: This paper presents a discrete event simulation (DES) model developed to select and implement a Point of Sale (POS) for a company providing financial products. First, the paper shows the characterization of the system components and times per process. Then, hypothesis testing and goodness-of-fit statistics are estimated. Subsequently, the simulation scenarios assess the times between arrivals and the number of commercial advisers. Results and discussion: This model allows us to assess the allocation of resources to fulfill the service promise, which is that 80 % of customers must be served within one hour or less. This paper provided the service isoquants allowing us to observe the behavior of the performance metrics (service promise fulfillment) among different scenarios. Conclusions: The use of DES techniques allows for the evaluation of the assignment of personnel to achieve the fulfillment of the service promise, including facilities, equipment, and the evaluation of related processes. These methods can be extended to the analysis of resource allocation in the development of other processes, observing the relationship between service quality and operating costs.
{"title":"Resources Allocation in Service Planning Using Discrete-Event Simulation","authors":"M. Becerra-Fernández, Milton M. Herrera, C. Trejos, O. R. Romero","doi":"10.11144/javeriana.iued25.rasp","DOIUrl":"https://doi.org/10.11144/javeriana.iued25.rasp","url":null,"abstract":"Objective: Calculate the required personnel and resources needed to fulfill the service promise agreed with the customer. Methods and materials: This paper presents a discrete event simulation (DES) model developed to select and implement a Point of Sale (POS) for a company providing financial products. First, the paper shows the characterization of the system components and times per process. Then, hypothesis testing and goodness-of-fit statistics are estimated. Subsequently, the simulation scenarios assess the times between arrivals and the number of commercial advisers. Results and discussion: This model allows us to assess the allocation of resources to fulfill the service promise, which is that 80 % of customers must be served within one hour or less. This paper provided the service isoquants allowing us to observe the behavior of the performance metrics (service promise fulfillment) among different scenarios. Conclusions: The use of DES techniques allows for the evaluation of the assignment of personnel to achieve the fulfillment of the service promise, including facilities, equipment, and the evaluation of related processes. These methods can be extended to the analysis of resource allocation in the development of other processes, observing the relationship between service quality and operating costs.","PeriodicalId":39036,"journal":{"name":"Ingenieria y Universidad","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81366137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-17DOI: 10.11144/javeriana.iued25.dcli
Francisco Andrés Chuchoque-Urbina, Martha Patricia Caro-Gutiérrez, Carlos Eduardor Montoya-Casas
Objective: Designing a CPFR (collaborative planning forecasting and replenishment) model for the delivery of diabetes and arterial hypertension medicines from a health insurance company (EPS) to a healthcare provider (IPS) and comparing the performance of this collaborative chain to that of the traditional one through their corresponding supply chain costs. Methodology: A series of collaboration agreements involved in joint planning were established according to the designed CPFR model. This allowed (i) raising the levels of interaction between the health insurance company, the healthcare provider, the supplying pharmaceutical laboratories, and the patients; (ii) determining demand forecasts; (iii) locating distribution centers; and (iv) defining medicine distribution strategies oriented to the minimization of costs along the chain. Subsequently, the main differences between the current operation and CPFR models at the level of structure and decisions were characterized and then evaluated in terms of supply chain costs. Results: The significant impact of the proposed model is demonstrated. The total monthly cost of operating the chain is reduced by 11.2 % on average. Within the proposed innovation, an outstanding place is held by the savings reached in the purchase and distribution of medicines from the laboratory to the distribution centers, and by the customer satisfaction differences, which increased 15.3 % on average during the studied six-month period.
{"title":"Design of a CPFR, Location, Inventory and Routing Approach to Diabetes and High Blood Pressure Medicine Supply Network Planning","authors":"Francisco Andrés Chuchoque-Urbina, Martha Patricia Caro-Gutiérrez, Carlos Eduardor Montoya-Casas","doi":"10.11144/javeriana.iued25.dcli","DOIUrl":"https://doi.org/10.11144/javeriana.iued25.dcli","url":null,"abstract":"Objective: Designing a CPFR (collaborative planning forecasting and replenishment) model for the delivery of diabetes and arterial hypertension medicines from a health insurance company (EPS) to a healthcare provider (IPS) and comparing the performance of this collaborative chain to that of the traditional one through their corresponding supply chain costs. Methodology: A series of collaboration agreements involved in joint planning were established according to the designed CPFR model. This allowed (i) raising the levels of interaction between the health insurance company, the healthcare provider, the supplying pharmaceutical laboratories, and the patients; (ii) determining demand forecasts; (iii) locating distribution centers; and (iv) defining medicine distribution strategies oriented to the minimization of costs along the chain. Subsequently, the main differences between the current operation and CPFR models at the level of structure and decisions were characterized and then evaluated in terms of supply chain costs. Results: The significant impact of the proposed model is demonstrated. The total monthly cost of operating the chain is reduced by 11.2 % on average. Within the proposed innovation, an outstanding place is held by the savings reached in the purchase and distribution of medicines from the laboratory to the distribution centers, and by the customer satisfaction differences, which increased 15.3 % on average during the studied six-month period.","PeriodicalId":39036,"journal":{"name":"Ingenieria y Universidad","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86439944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-17DOI: 10.11144/javeriana.iued25.svmu
Nathalie Hernández, N. Caradot, H. Sonnenberg, P. Rouault, A. Torres
Objective: this paper focused on: (i) developing a deterioration model based on support vector machines (SVM) from its regression approach to separate the prediction of the structural condition of sewer pipes from a classification by grades and predict the scores obtained by failures found in CCTV inspections; and (ii) comparing the prediction results of the proposed model with the ones obtained by a deterioration model based on SVM classification tasks to explore the advantages and disadvantages of their predictions from different perspectives. Materials and methods: The sewer network of Bogota was the case study for this work in which a dataset consisting of the characteristics of 5031 pipes inspected by CCTV (obtained by GIS) was considered, as well as information on external variables (e.g., age, sewerage, and road type). Probability density functions (PDF) were used to convert the scores given by failures found in CCTV into structural grades. In addition, three techniques were used to evaluate the predictions from different perspectives: positive likelihood rate (PLR), performance curve and deviation analysis. Results: it was found that: (i) SVM-based deterioration model used from its regression approach is suitable to predict critical structural conditions of uninspected sewer pipes because this model showed a PLR value around 6.8 (the highest value among the predictions of all structural conditions for both models) and 74 % of successful predictions for the first 100 pipes with the highest probability of being in critical conditions; and (ii) SVM-based deterioration model used from its classification approach is suitable to predict other structural conditions because this model showed homogeneous PLR values for the prediction of all structural conditions (PLR values between 1.67 and 3.88) and deviation analysis results for all structural conditions are lower than the ones for the SVM-based model from its regression approach.
{"title":"Support Vector Machines Used for the Prediction of the Structural Conditions of Pipes in Bogota’s Sewer System","authors":"Nathalie Hernández, N. Caradot, H. Sonnenberg, P. Rouault, A. Torres","doi":"10.11144/javeriana.iued25.svmu","DOIUrl":"https://doi.org/10.11144/javeriana.iued25.svmu","url":null,"abstract":"Objective: this paper focused on: (i) developing a deterioration model based on support vector machines (SVM) from its regression approach to separate the prediction of the structural condition of sewer pipes from a classification by grades and predict the scores obtained by failures found in CCTV inspections; and (ii) comparing the prediction results of the proposed model with the ones obtained by a deterioration model based on SVM classification tasks to explore the advantages and disadvantages of their predictions from different perspectives. Materials and methods: The sewer network of Bogota was the case study for this work in which a dataset consisting of the characteristics of 5031 pipes inspected by CCTV (obtained by GIS) was considered, as well as information on external variables (e.g., age, sewerage, and road type). Probability density functions (PDF) were used to convert the scores given by failures found in CCTV into structural grades. In addition, three techniques were used to evaluate the predictions from different perspectives: positive likelihood rate (PLR), performance curve and deviation analysis. Results: it was found that: (i) SVM-based deterioration model used from its regression approach is suitable to predict critical structural conditions of uninspected sewer pipes because this model showed a PLR value around 6.8 (the highest value among the predictions of all structural conditions for both models) and 74 % of successful predictions for the first 100 pipes with the highest probability of being in critical conditions; and (ii) SVM-based deterioration model used from its classification approach is suitable to predict other structural conditions because this model showed homogeneous PLR values for the prediction of all structural conditions (PLR values between 1.67 and 3.88) and deviation analysis results for all structural conditions are lower than the ones for the SVM-based model from its regression approach.","PeriodicalId":39036,"journal":{"name":"Ingenieria y Universidad","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72776327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.11144/javeriana.iued25.fchp
H. Bolaños, F. Botero
Objective: Identify and characterize subsynchronous hydrodynamics phenomena in a low specific speed centrifugal pump based on its four-quadrant characteristic curve. Materials: A 1.5 HP ITT Goulds pump instrumented with pressure transductors, an accelerometer, a torque sensor and a tachometer. Flow rate measurement was done with an ultrasonic transit time clamp-on flow meter. Methods: Time and frequency domain analysis with phase analysis were used to identify spectral components linked to hydrodynamic phenomena such as rotating stall and surge. Results and discussion: This work approaches an alternative method to calculate the phase angle using pressure signals without filtering. Related with hydrodynamic phenomena, the evidence collected suggests the presence of rotating stall in some operation points of the four-quadrant characteristic curve. Furthermore, in the third quadrant, rotating stall coexist with surge. Conclusions: The instrumentation and methods regarded in this work allow to collect evidence to identify in-phase and out of phase subsynchronous hydrodynamic phenomena. The classic cross-correlation-based method was improved to ease the diagnosis of subsynchronous phenomena by visual inspection. A new quantitative approach was introduced to detect subsynchronous phenomena, based on the Fourier analysis; it was validated with a case study for which the classical method was not suitable.
{"title":"Four-quadrant Characterization of Hydrodynamic Phenomena in a Low Specific Speed Centrifugal Pump","authors":"H. Bolaños, F. Botero","doi":"10.11144/javeriana.iued25.fchp","DOIUrl":"https://doi.org/10.11144/javeriana.iued25.fchp","url":null,"abstract":"Objective: Identify and characterize subsynchronous hydrodynamics phenomena in a low specific speed centrifugal pump based on its four-quadrant characteristic curve. Materials: A 1.5 HP ITT Goulds pump instrumented with pressure transductors, an accelerometer, a torque sensor and a tachometer. Flow rate measurement was done with an ultrasonic transit time clamp-on flow meter. Methods: Time and frequency domain analysis with phase analysis were used to identify spectral components linked to hydrodynamic phenomena such as rotating stall and surge. Results and discussion: This work approaches an alternative method to calculate the phase angle using pressure signals without filtering. Related with hydrodynamic phenomena, the evidence collected suggests the presence of rotating stall in some operation points of the four-quadrant characteristic curve. Furthermore, in the third quadrant, rotating stall coexist with surge. Conclusions: The instrumentation and methods regarded in this work allow to collect evidence to identify in-phase and out of phase subsynchronous hydrodynamic phenomena. The classic cross-correlation-based method was improved to ease the diagnosis of subsynchronous phenomena by visual inspection. A new quantitative approach was introduced to detect subsynchronous phenomena, based on the Fourier analysis; it was validated with a case study for which the classical method was not suitable.","PeriodicalId":39036,"journal":{"name":"Ingenieria y Universidad","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83460072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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