Maria Alejandra Coronado Racines, Juan Carlos Osorio Gómez, Dayhanna Stephania Vargas Mesa
The cultivation of sugar cane generates impacts on ecosystems, two of the four most relevant impacts are environmental, on the one hand, the generation of greater water stress due to irrigation needs, in addition to the impact on biodiversity and endemic species due to land use, highlighting the need for the development of policies for sugarcane production trying to mitigate these impacts [1]. This is how a dynamic simulation is proposed that addresses elements of sugarcane cultivation considering a case of traditional plantation and another organic one to estimate the environmental effects produced by irrigation, which generates depletion of the water resource, and the control of pests and weeds that cause contamination in the soil through the application of chemicals. The proposed model was applied using the Vensim PLE software considering interrelationships between these elements. In this way, it was possible to conclude that the depletion of the water resource and the contamination of the soil is lower in organic cultivation, consuming 10.5% less water, in addition they are not considered pollutants in the soil, but in the traditional cultivation reaches 1674 l/ha. It is important to note that for the model to be able to correctly support decision-making, additional aspects that affect the yield of each type of crop, as well as its profit margin and volatility, must be considered.
{"title":"System Dynamics Application as a Tool to Estimate Environmental Effects of Irrigation, Pest and Weed Control Considering a Traditional Sugarcane Crop and an Organic Sugarcane Crop","authors":"Maria Alejandra Coronado Racines, Juan Carlos Osorio Gómez, Dayhanna Stephania Vargas Mesa","doi":"10.1145/3523132.3523138","DOIUrl":"https://doi.org/10.1145/3523132.3523138","url":null,"abstract":"The cultivation of sugar cane generates impacts on ecosystems, two of the four most relevant impacts are environmental, on the one hand, the generation of greater water stress due to irrigation needs, in addition to the impact on biodiversity and endemic species due to land use, highlighting the need for the development of policies for sugarcane production trying to mitigate these impacts [1]. This is how a dynamic simulation is proposed that addresses elements of sugarcane cultivation considering a case of traditional plantation and another organic one to estimate the environmental effects produced by irrigation, which generates depletion of the water resource, and the control of pests and weeds that cause contamination in the soil through the application of chemicals. The proposed model was applied using the Vensim PLE software considering interrelationships between these elements. In this way, it was possible to conclude that the depletion of the water resource and the contamination of the soil is lower in organic cultivation, consuming 10.5% less water, in addition they are not considered pollutants in the soil, but in the traditional cultivation reaches 1674 l/ha. It is important to note that for the model to be able to correctly support decision-making, additional aspects that affect the yield of each type of crop, as well as its profit margin and volatility, must be considered.","PeriodicalId":109028,"journal":{"name":"Proceedings of the 2022 9th International Conference on Industrial Engineering and Applications (Europe)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121916310","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}
Industry practitioners are being pushed to have a fresh look at the negative impact their supply chain activities have on environment. There are various carbon policies that have been forced by government globally, aiming to limit carbon emission. In this work, , an optimization models based on carbon cap policy for a two-echelon supply chain is presented. The proposed model aims to optimize the cost as well as the amount of carbon emitted along the supply chain. Results show that zero additional cost along with 100% demand satisfaction can be granted if defined cap is greater than total carbon emission of supply chain network. Moreover, a strict cap can still offer 100% demand satisfaction at an extra cost. Government should realize the impact of cap on supply chain network on demand and total cost increase percentage.
{"title":"The Impact of Carbon Cap Policy on Supply Chain Network","authors":"Sanabel Alnourani, S. Mejjaouli","doi":"10.1145/3523132.3523135","DOIUrl":"https://doi.org/10.1145/3523132.3523135","url":null,"abstract":"Industry practitioners are being pushed to have a fresh look at the negative impact their supply chain activities have on environment. There are various carbon policies that have been forced by government globally, aiming to limit carbon emission. In this work, , an optimization models based on carbon cap policy for a two-echelon supply chain is presented. The proposed model aims to optimize the cost as well as the amount of carbon emitted along the supply chain. Results show that zero additional cost along with 100% demand satisfaction can be granted if defined cap is greater than total carbon emission of supply chain network. Moreover, a strict cap can still offer 100% demand satisfaction at an extra cost. Government should realize the impact of cap on supply chain network on demand and total cost increase percentage.","PeriodicalId":109028,"journal":{"name":"Proceedings of the 2022 9th International Conference on Industrial Engineering and Applications (Europe)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127624306","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}
M. J. Gumasing, Frankern Luis S. Malabuyoc, Madeline Anne Patrice C. Sy, M. Sobrevilla, Maryam G. Irenea
This study empirically determines the risk level of food sector employees for the virus COVID-19 infection, specifically those who are under the food sector in the Philippines. This paper utilizes the RIKA Risk Assessment Tool to assess health, behavioral, exposure, and social factors that may contribute to the overall risk score of individuals. The researchers used data from a sample of 55 respondents obtained from a digital survey containing the RIKA Risk Assessment Tool, which was then analyzed using descriptive statistics and correlation analysis. The results of the statistical analysis used presented low to moderate risk levels of being infected with COVID-19 based on the personal assessment of their surroundings and health practices of the food sector employees. Researchers found that workers in the Philippines' food sector are exposed to a variety of risk factors: health, behavioral, exposure, and social policy. The majority have a moderate impact upon the said results; however, adhering to proper hygiene, community standards, and lockdown policies can significantly influence outcomes.
{"title":"COVID-19 Risk Level Assessment: A Case of Food Sector Employees","authors":"M. J. Gumasing, Frankern Luis S. Malabuyoc, Madeline Anne Patrice C. Sy, M. Sobrevilla, Maryam G. Irenea","doi":"10.1145/3523132.3523142","DOIUrl":"https://doi.org/10.1145/3523132.3523142","url":null,"abstract":"This study empirically determines the risk level of food sector employees for the virus COVID-19 infection, specifically those who are under the food sector in the Philippines. This paper utilizes the RIKA Risk Assessment Tool to assess health, behavioral, exposure, and social factors that may contribute to the overall risk score of individuals. The researchers used data from a sample of 55 respondents obtained from a digital survey containing the RIKA Risk Assessment Tool, which was then analyzed using descriptive statistics and correlation analysis. The results of the statistical analysis used presented low to moderate risk levels of being infected with COVID-19 based on the personal assessment of their surroundings and health practices of the food sector employees. Researchers found that workers in the Philippines' food sector are exposed to a variety of risk factors: health, behavioral, exposure, and social policy. The majority have a moderate impact upon the said results; however, adhering to proper hygiene, community standards, and lockdown policies can significantly influence outcomes.","PeriodicalId":109028,"journal":{"name":"Proceedings of the 2022 9th International Conference on Industrial Engineering and Applications (Europe)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130829380","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}
The development of industrial automation is closely related to the evolution of mobile robot positioning and navigation mode. In this paper, we introduce ASL-SLAM, the first line-based SLAM system operating directly on robots using the event sensor only. This approach maximizes the advantages of the event information generated by a bio-inspired sensor. We estimate the local Surface of Active Events (SAE) to get the planes for each incoming event in the event stream. Then the edges and their motion are recovered by our line extraction algorithm. We show how the inclusion of event-based line tracking significantly improves performance compared to state-of-the-art frame-based SLAM systems. The approach is evaluated on publicly available datasets. The results show that our approach is particularly effective with poorly textured frames when the robot faces simple or low texture environments. We also experimented with challenging illumination situations to order to be suitable for various industrial environments, including low-light and high motion blur scenarios. We show that our approach with the event-based camera has natural advantages and provides up to 85% reduction in error when performing SLAM under these conditions compared to the traditional approach.
{"title":"ASL-SLAM: An Asynchronous Formulation of Lines for SLAM with Event Sensors","authors":"Xiaoqi Nong, Simon Hadfield","doi":"10.1145/3523132.3523146","DOIUrl":"https://doi.org/10.1145/3523132.3523146","url":null,"abstract":"The development of industrial automation is closely related to the evolution of mobile robot positioning and navigation mode. In this paper, we introduce ASL-SLAM, the first line-based SLAM system operating directly on robots using the event sensor only. This approach maximizes the advantages of the event information generated by a bio-inspired sensor. We estimate the local Surface of Active Events (SAE) to get the planes for each incoming event in the event stream. Then the edges and their motion are recovered by our line extraction algorithm. We show how the inclusion of event-based line tracking significantly improves performance compared to state-of-the-art frame-based SLAM systems. The approach is evaluated on publicly available datasets. The results show that our approach is particularly effective with poorly textured frames when the robot faces simple or low texture environments. We also experimented with challenging illumination situations to order to be suitable for various industrial environments, including low-light and high motion blur scenarios. We show that our approach with the event-based camera has natural advantages and provides up to 85% reduction in error when performing SLAM under these conditions compared to the traditional approach.","PeriodicalId":109028,"journal":{"name":"Proceedings of the 2022 9th International Conference on Industrial Engineering and Applications (Europe)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114250335","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}
Jose Coronel-Vasquez, Dhara Huamani-Lara, A. Flores-Perez, Martin Collao-Diaz, J. Quiroz-Flores
The textile sector has a large share in the Peruvian manufacturing industry, dominated by SMEs. However, the segment has been facing a slowdown in growth, intensified by the partial inoperability of commercial enterprises. Under this scenario, there is a need to improve its competitiveness by optimizing the material supply process, as this is the stage that generates a large number of non-conforming orders and delays in the entry of production. Therefore, an optimize model using Just-In-Time and Lean Warehouse has been proposed to reduce backorders, shorten delivery times and minimize the input of defective materials. Along with 5S methodology to organize the warehouse and supplier assessment, ensured a long lasting solution. After the simulation made by the software Arena with the proposed model, it was possible to reduce the number of non-optimal orders by 55% and increase process efficiency by 5.97% by reducing procurement lead time. Furthermore, it represents a reduction in the purchasing cost of 40.55%.
{"title":"Logistics Management Model to reduce non-conforming orders through Lean Warehouse and JIT: A case of study in textile SMEs in Peru","authors":"Jose Coronel-Vasquez, Dhara Huamani-Lara, A. Flores-Perez, Martin Collao-Diaz, J. Quiroz-Flores","doi":"10.1145/3523132.3523136","DOIUrl":"https://doi.org/10.1145/3523132.3523136","url":null,"abstract":"The textile sector has a large share in the Peruvian manufacturing industry, dominated by SMEs. However, the segment has been facing a slowdown in growth, intensified by the partial inoperability of commercial enterprises. Under this scenario, there is a need to improve its competitiveness by optimizing the material supply process, as this is the stage that generates a large number of non-conforming orders and delays in the entry of production. Therefore, an optimize model using Just-In-Time and Lean Warehouse has been proposed to reduce backorders, shorten delivery times and minimize the input of defective materials. Along with 5S methodology to organize the warehouse and supplier assessment, ensured a long lasting solution. After the simulation made by the software Arena with the proposed model, it was possible to reduce the number of non-optimal orders by 55% and increase process efficiency by 5.97% by reducing procurement lead time. Furthermore, it represents a reduction in the purchasing cost of 40.55%.","PeriodicalId":109028,"journal":{"name":"Proceedings of the 2022 9th International Conference on Industrial Engineering and Applications (Europe)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122760102","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}
D. Acosta-Ramirez, Alvaro Herrera-Noel, A. Flores-Perez, J. Quiroz-Flores, Martin Collao-Diaz
The growing importance of continuous improvement in companies, focusing on the customer and greater competitiveness, the present research aims to propose a model based on Lean Manufacturing through the application of DMAIC Cycle to improve customer satisfaction and thereby increase the Net Promoter Score (NPS) of a real estate company, for this purpose applied a mixed research, descriptive-purposeful level, taking as analysis methodology Lean Manufacturing with the use of TQM, VSM and 5S tools, which in turn made use of the Ishikawa Diagram, Pareto and Customer Journey Map. As a result, an integrated model was obtained that allows identifying and eliminating activities that do not add value, analyzing and correcting failures in the customer experience that cause dissatisfaction, to increase the NPS from 28.83 current to 50 (sector average), proposing a continuous improvement plan through TQM, from the diagnosis obtained indicators were drawn and a simulation of the proposed model was carried out, concluding that it is effective in achieving the goals set and that within the first semester, according to the ARENA simulation, the NPS would increase to 35.53%.
{"title":"Application of Lean Manufacturing tools under DMAIC approach to increase the NPS in a real estate company: A Research in Peru","authors":"D. Acosta-Ramirez, Alvaro Herrera-Noel, A. Flores-Perez, J. Quiroz-Flores, Martin Collao-Diaz","doi":"10.1145/3523132.3523144","DOIUrl":"https://doi.org/10.1145/3523132.3523144","url":null,"abstract":"The growing importance of continuous improvement in companies, focusing on the customer and greater competitiveness, the present research aims to propose a model based on Lean Manufacturing through the application of DMAIC Cycle to improve customer satisfaction and thereby increase the Net Promoter Score (NPS) of a real estate company, for this purpose applied a mixed research, descriptive-purposeful level, taking as analysis methodology Lean Manufacturing with the use of TQM, VSM and 5S tools, which in turn made use of the Ishikawa Diagram, Pareto and Customer Journey Map. As a result, an integrated model was obtained that allows identifying and eliminating activities that do not add value, analyzing and correcting failures in the customer experience that cause dissatisfaction, to increase the NPS from 28.83 current to 50 (sector average), proposing a continuous improvement plan through TQM, from the diagnosis obtained indicators were drawn and a simulation of the proposed model was carried out, concluding that it is effective in achieving the goals set and that within the first semester, according to the ARENA simulation, the NPS would increase to 35.53%.","PeriodicalId":109028,"journal":{"name":"Proceedings of the 2022 9th International Conference on Industrial Engineering and Applications (Europe)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125083540","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}
In recent years, with the rapid growth of airport passenger flow, airport services such as security inspection, emergency response, check-in, baggage tracking are facing tremendous pressure. Being able to make relatively accurate predictions of short-time passenger flow in airport terminals is an important basic guarantee for improving service quality, enhancing operational efficiency, and rationalizing resource allocation. In this paper, we establish a multi-gate short-time passenger flow prediction model ST- LSTM based on deep spatial-temporal learning, which integrates convolutional neural network (CNN) and long short-term memory (LSTM) to improve short-time passenger flow prediction accuracy. Based on the actual passenger flow data of 2 million departing passengers at Guangzhou BAIYUN International Airport, according to the number of passengers connected to Wi-Fi AP (Access Point), flight schedules, gates area, Wi-Fi access point location characteristics, etc. Through comparison with the HA, ARIMA, GBDT, LSTM, it is proved that the ST-LSTM model can more effectively predict the short-term passenger flow of the airport, which provides crucial decisions for the dynamic allocation and optimization of resources in the boarding gates, gives guiding significance to actuality.
近年来，随着机场客流量的快速增长，安检、应急响应、值机、行李跟踪等机场服务面临着巨大的压力。能够对机场航站楼短期客流进行较为准确的预测，是提高服务质量、提高运营效率、合理配置资源的重要基础保障。本文建立了基于深度时空学习的多门短时客流预测模型ST- LSTM，将卷积神经网络(CNN)和长短期记忆(LSTM)相结合，提高短时客流预测精度。基于广州白云国际机场200万出境旅客的实际客流数据，根据连接Wi-Fi AP (Access Point)的旅客数量、航班时刻表、登机口面积、Wi-Fi接入点位置特征等。通过与HA、ARIMA、GBDT、LSTM模型的比较，证明ST-LSTM模型能更有效地预测机场短期客流，为登机口资源的动态配置和优化提供关键决策，对现实具有指导意义。
{"title":"Short-term Passenger Flow Forecasting of the Airport Based on Deep Learning Spatial-temporal Network","authors":"Wenjia Xu, L. Miao, Jinjiang Xing","doi":"10.1145/3523132.3523145","DOIUrl":"https://doi.org/10.1145/3523132.3523145","url":null,"abstract":"In recent years, with the rapid growth of airport passenger flow, airport services such as security inspection, emergency response, check-in, baggage tracking are facing tremendous pressure. Being able to make relatively accurate predictions of short-time passenger flow in airport terminals is an important basic guarantee for improving service quality, enhancing operational efficiency, and rationalizing resource allocation. In this paper, we establish a multi-gate short-time passenger flow prediction model ST- LSTM based on deep spatial-temporal learning, which integrates convolutional neural network (CNN) and long short-term memory (LSTM) to improve short-time passenger flow prediction accuracy. Based on the actual passenger flow data of 2 million departing passengers at Guangzhou BAIYUN International Airport, according to the number of passengers connected to Wi-Fi AP (Access Point), flight schedules, gates area, Wi-Fi access point location characteristics, etc. Through comparison with the HA, ARIMA, GBDT, LSTM, it is proved that the ST-LSTM model can more effectively predict the short-term passenger flow of the airport, which provides crucial decisions for the dynamic allocation and optimization of resources in the boarding gates, gives guiding significance to actuality.","PeriodicalId":109028,"journal":{"name":"Proceedings of the 2022 9th International Conference on Industrial Engineering and Applications (Europe)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134562510","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}
{"title":"Proceedings of the 2022 9th International Conference on Industrial Engineering and Applications (Europe)","authors":"","doi":"10.1145/3523132","DOIUrl":"https://doi.org/10.1145/3523132","url":null,"abstract":"","PeriodicalId":109028,"journal":{"name":"Proceedings of the 2022 9th International Conference on Industrial Engineering and Applications (Europe)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128220978","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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