Pub Date : 2020-04-01DOI: 10.1109/iciea49774.2020.9101923
Neng Jin, Xiangning Lin, Zhengtian Li, Zirui Rong, Peifu Zhang
{"title":"Notice of Removal: A Novel Station-Wide Area Information Interaction Intelligent System","authors":"Neng Jin, Xiangning Lin, Zhengtian Li, Zirui Rong, Peifu Zhang","doi":"10.1109/iciea49774.2020.9101923","DOIUrl":"https://doi.org/10.1109/iciea49774.2020.9101923","url":null,"abstract":"","PeriodicalId":306461,"journal":{"name":"2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA)","volume":" 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141217777","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 : 2020-04-01DOI: 10.1109/ICIEA49774.2020.9102096
Y. Prasetyo
Gross manual dexterity is an important part of human factors and ergonomics. The purpose of the current study was to investigate factors affecting gross manual dexterity. Gender, palm length, grip strength, hand skin temperature, room temperature, and room humidity were analyzed simultaneously to predict gross manual dexterity by utilizing Structural Equation Modeling (SEM) approach. SEM showed that hand skin temperature was the most important factor for predicting gross manual dexterity, followed by several other factors such as grip strength, gender, and room temperature. In addition, room humidity, age, and hand size were also had significant indirect effects on gross manual dexterity. The SEM derived in this study could be a very valuable theoretical foundation which could be very beneficial for human factors engineer, physical therapist, and even medical doctors.
{"title":"Factors Affecting Gross Manual Dexterity: A Structural Equation Modeling Approach","authors":"Y. Prasetyo","doi":"10.1109/ICIEA49774.2020.9102096","DOIUrl":"https://doi.org/10.1109/ICIEA49774.2020.9102096","url":null,"abstract":"Gross manual dexterity is an important part of human factors and ergonomics. The purpose of the current study was to investigate factors affecting gross manual dexterity. Gender, palm length, grip strength, hand skin temperature, room temperature, and room humidity were analyzed simultaneously to predict gross manual dexterity by utilizing Structural Equation Modeling (SEM) approach. SEM showed that hand skin temperature was the most important factor for predicting gross manual dexterity, followed by several other factors such as grip strength, gender, and room temperature. In addition, room humidity, age, and hand size were also had significant indirect effects on gross manual dexterity. The SEM derived in this study could be a very valuable theoretical foundation which could be very beneficial for human factors engineer, physical therapist, and even medical doctors.","PeriodicalId":306461,"journal":{"name":"2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123869354","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 : 2020-04-01DOI: 10.1109/ICIEA49774.2020.9102060
Jean Vidal, M. Lauras, J. Lamothe, Romain Miclo
The Demand-Driven Adaptive Enterprise (DDAE) model introduced by the Demand Driven Institute (DDI) few years ago becomes of prime interest for both scholars and practitioners. This research work is investigating the rarely studied strategic part of this DDAE model called Adaptive Sales and Operations Planning (AS&OP) process. One of the main issues regarding this strategic process is to determine how to model it through product family aggregates. Actually, literature analysis demonstrated that no solution exists to support such a process. This research work intends to solve this issue by designing a first AS&OP model allowing an aggregate reasoning. This proposal has been successfully tested on a illustrative but realistic example.
{"title":"Toward an Aggregate Approach for Supporting Adaptive Sales And Operations Planning","authors":"Jean Vidal, M. Lauras, J. Lamothe, Romain Miclo","doi":"10.1109/ICIEA49774.2020.9102060","DOIUrl":"https://doi.org/10.1109/ICIEA49774.2020.9102060","url":null,"abstract":"The Demand-Driven Adaptive Enterprise (DDAE) model introduced by the Demand Driven Institute (DDI) few years ago becomes of prime interest for both scholars and practitioners. This research work is investigating the rarely studied strategic part of this DDAE model called Adaptive Sales and Operations Planning (AS&OP) process. One of the main issues regarding this strategic process is to determine how to model it through product family aggregates. Actually, literature analysis demonstrated that no solution exists to support such a process. This research work intends to solve this issue by designing a first AS&OP model allowing an aggregate reasoning. This proposal has been successfully tested on a illustrative but realistic example.","PeriodicalId":306461,"journal":{"name":"2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127682994","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}
Until 2017, coal still dominates up to 58.3% of the energy mix in Indonesia. Based on the 2027 projection for Sumatra Island, the composition of electricity production with coal primary energy will increase to 43.9% from the previous 37.7% [1]. By considering the principle of regional balance, the contribution of electricity needs in Sumatra Island mostly will be supplied from the coal fired steam power plant. One of important parameter in determining the efficiency of a power plant is the value of Heat Rate. In this study, it is consists of three subsystems, namely boiler, coal, and feed water. Dynamic System method is used to create a model that can represent the heat rate real system because its variables which influence the value are dynamic, complex and integrated one to another. The simulation results from modeling are useful for improvement process to predict the heat rate value in future periods. It is also describe which one will be the significant variables in heat rate system in order to reduce the operational costs. As the final results, it is predicted the total cost of heat rate losses will increase from 21,175 USD in the last 12 months to 38,851.9 USD for the next 36 months. The biggest cost in heat rate losses is the coal subsystem, which is 8,000 – 31,000 USD. Followed by boiler subsystem which is 12,000 – 18,000 USD and feed water subsystem is 1–15 USD. Coal moisture which contributes as the highest value losses in the heat rate losses system should be the main focus for South Sumatra-V management in making policies.
{"title":"Heat Rate Losses Simulation for Coal Fired Steam Power Plant at South Sumatra-V Cfspp using Dynamic System","authors":"Lulu Khoirunnisa, Lilia Trisyathia Quentara, Vivi Apriyanti","doi":"10.1109/ICIEA49774.2020.9102074","DOIUrl":"https://doi.org/10.1109/ICIEA49774.2020.9102074","url":null,"abstract":"Until 2017, coal still dominates up to 58.3% of the energy mix in Indonesia. Based on the 2027 projection for Sumatra Island, the composition of electricity production with coal primary energy will increase to 43.9% from the previous 37.7% [1]. By considering the principle of regional balance, the contribution of electricity needs in Sumatra Island mostly will be supplied from the coal fired steam power plant. One of important parameter in determining the efficiency of a power plant is the value of Heat Rate. In this study, it is consists of three subsystems, namely boiler, coal, and feed water. Dynamic System method is used to create a model that can represent the heat rate real system because its variables which influence the value are dynamic, complex and integrated one to another. The simulation results from modeling are useful for improvement process to predict the heat rate value in future periods. It is also describe which one will be the significant variables in heat rate system in order to reduce the operational costs. As the final results, it is predicted the total cost of heat rate losses will increase from 21,175 USD in the last 12 months to 38,851.9 USD for the next 36 months. The biggest cost in heat rate losses is the coal subsystem, which is 8,000 – 31,000 USD. Followed by boiler subsystem which is 12,000 – 18,000 USD and feed water subsystem is 1–15 USD. Coal moisture which contributes as the highest value losses in the heat rate losses system should be the main focus for South Sumatra-V management in making policies.","PeriodicalId":306461,"journal":{"name":"2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128957090","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}
Bike-sharing systems have been widely implemented in around 700 cities worldwide since the 2000s. The quick expansion is due to the growing concerns over environmental impacts and climate change problems. Bicycles are deemed to be a promising mode of transportation for achieving urban sustainability and sustainability in higher education. Sustainable transportation is an important factor in achieving the UN's Sustainable Development Goals. In Thailand, a bike-sharing service was first launched in Bangkok in 2012. However, bike-sharing in Thailand heavily relied on systems designed and operated by international companies. Many systems have not been very successful and some were discontinued. We discuss lessons learned from a locally designed bike-sharing system and its optimization for a Thai university. A pilot-scale of public bicycles was launched and over 24,000 trips were observed in six months. Most trips were 0–10 minutes and peak hours were in the morning, which means most students picked up the public bike on the last-mile based on study timetable. From heat maps of bicycle usage, nearly educational buildings and connecting transit points had the highest departure and arrival rates.
{"title":"Locally Designed Campus Smart Bike Sharing System: Lessons Learned and Design Optimization for Thailand","authors":"Chitsanu Pakdeewanich, Ronnachai Tiyarattanachai, Isara Anantavrasilp","doi":"10.1109/ICIEA49774.2020.9101911","DOIUrl":"https://doi.org/10.1109/ICIEA49774.2020.9101911","url":null,"abstract":"Bike-sharing systems have been widely implemented in around 700 cities worldwide since the 2000s. The quick expansion is due to the growing concerns over environmental impacts and climate change problems. Bicycles are deemed to be a promising mode of transportation for achieving urban sustainability and sustainability in higher education. Sustainable transportation is an important factor in achieving the UN's Sustainable Development Goals. In Thailand, a bike-sharing service was first launched in Bangkok in 2012. However, bike-sharing in Thailand heavily relied on systems designed and operated by international companies. Many systems have not been very successful and some were discontinued. We discuss lessons learned from a locally designed bike-sharing system and its optimization for a Thai university. A pilot-scale of public bicycles was launched and over 24,000 trips were observed in six months. Most trips were 0–10 minutes and peak hours were in the morning, which means most students picked up the public bike on the last-mile based on study timetable. From heat maps of bicycle usage, nearly educational buildings and connecting transit points had the highest departure and arrival rates.","PeriodicalId":306461,"journal":{"name":"2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116384428","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 : 2020-04-01DOI: 10.1109/ICIEA49774.2020.9102023
Nuno Costa, Paulo Fontes
A billets reheating furnace simulator was used to identify the variables that must be measured with more accurate devices and methods to estimate the furnace's energy efficiency when real energy audits are performed. For this purpose, experiments were statistically designed, and easy-to-implement data analysis methods were employed. The results analysis shows that the variables with practical and statistically significant effect on energy efficiency are the percentage of O2in the combustion gases, the fuel flow in the burners, and the combustion air temperature. A confirmatory experiment validated the results analysis and points out that Design of Experiments is a tool that cannot be ignored by those who perform energy audits or have the responsibility to combat energy waste in energy-intensive manufacturing industries.
{"title":"Energy Efficiency Estimate in Complex and Large Equipments","authors":"Nuno Costa, Paulo Fontes","doi":"10.1109/ICIEA49774.2020.9102023","DOIUrl":"https://doi.org/10.1109/ICIEA49774.2020.9102023","url":null,"abstract":"A billets reheating furnace simulator was used to identify the variables that must be measured with more accurate devices and methods to estimate the furnace's energy efficiency when real energy audits are performed. For this purpose, experiments were statistically designed, and easy-to-implement data analysis methods were employed. The results analysis shows that the variables with practical and statistically significant effect on energy efficiency are the percentage of O2in the combustion gases, the fuel flow in the burners, and the combustion air temperature. A confirmatory experiment validated the results analysis and points out that Design of Experiments is a tool that cannot be ignored by those who perform energy audits or have the responsibility to combat energy waste in energy-intensive manufacturing industries.","PeriodicalId":306461,"journal":{"name":"2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116950356","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 : 2020-04-01DOI: 10.1109/ICIEA49774.2020.9102097
Wichaya Sritrakool, P. Jarumaneeroj
This paper focuses on the development an Integer Programming (IP) model for the Deterministic Wave-based Same-day Pickup and Delivery Problem (D-WSDPD), where a vehicle is allowed to leave the depot at specific time periods, called waves. Moreover, each customer request comprises of a pair of services - namely pickup and delivery - not necessarily be completed in the same wave. If the request had been picked, it must be also be delivered by the end of the day. We explored how numbers of daily dispatch waves affect major service performance metrics, including total rewards from serving customer orders and the overall service level on 20 randomly generated instances. We found that, by increasing the numbers of daily dispatch waves, all service performance metrics could be potentially improved as expected, with greater numbers of dispatched waves. However, having too frequent daily dispatch waves would not significantly improve such metrics due to limited operational interval, i.e. planning horizon. In contrast, the computational times required grow exponentially; and, thence, cautious trade-offs between the desired service performance and operational costs must be made. While our mathematical formulation is only preliminary for the practical WSDPD, with high level of uncertainty, it could be regarded as a prelude to the development of efficient heuristics and policies that will be explored in the next steps.
{"title":"An Integer Programming Model for the Deterministic Wave-Based Same-Day Pickup and Delivery Problem","authors":"Wichaya Sritrakool, P. Jarumaneeroj","doi":"10.1109/ICIEA49774.2020.9102097","DOIUrl":"https://doi.org/10.1109/ICIEA49774.2020.9102097","url":null,"abstract":"This paper focuses on the development an Integer Programming (IP) model for the Deterministic Wave-based Same-day Pickup and Delivery Problem (D-WSDPD), where a vehicle is allowed to leave the depot at specific time periods, called waves. Moreover, each customer request comprises of a pair of services - namely pickup and delivery - not necessarily be completed in the same wave. If the request had been picked, it must be also be delivered by the end of the day. We explored how numbers of daily dispatch waves affect major service performance metrics, including total rewards from serving customer orders and the overall service level on 20 randomly generated instances. We found that, by increasing the numbers of daily dispatch waves, all service performance metrics could be potentially improved as expected, with greater numbers of dispatched waves. However, having too frequent daily dispatch waves would not significantly improve such metrics due to limited operational interval, i.e. planning horizon. In contrast, the computational times required grow exponentially; and, thence, cautious trade-offs between the desired service performance and operational costs must be made. While our mathematical formulation is only preliminary for the practical WSDPD, with high level of uncertainty, it could be regarded as a prelude to the development of efficient heuristics and policies that will be explored in the next steps.","PeriodicalId":306461,"journal":{"name":"2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114496440","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 : 2020-04-01DOI: 10.1109/ICIEA49774.2020.9102100
Christian John Immanuel S. Boydon, Carlo Angelo A. Sonday
Simulation is a widely used tool for the assessment and improvement of service industry firms like restaurants, banks, hospitals. However, most simulation studies do not mention the implementation of their findings and recommendations. In this paper, we take a sample of simulation studies for service systems in the past 20 years, verify this observation, and determine the reasons why this is the case. Review of these papers helped reveal some trends and manifestations in the literature of simulation studies on service systems, such as the industries where they are applied, motivations of these studies, types of solutions offered, and insights regarding implementation. Furthermore, we offer suggestions on how simulation studies can implement their recommended solutions, such as encouraging more collaboration between researchers and industry practitioners as well as the consideration of resource-neutral solutions which do not require additional cost for the organization to adopt.
{"title":"Simulation as a Tool for Implementing Resource-Neutral Solutions in Service Systems","authors":"Christian John Immanuel S. Boydon, Carlo Angelo A. Sonday","doi":"10.1109/ICIEA49774.2020.9102100","DOIUrl":"https://doi.org/10.1109/ICIEA49774.2020.9102100","url":null,"abstract":"Simulation is a widely used tool for the assessment and improvement of service industry firms like restaurants, banks, hospitals. However, most simulation studies do not mention the implementation of their findings and recommendations. In this paper, we take a sample of simulation studies for service systems in the past 20 years, verify this observation, and determine the reasons why this is the case. Review of these papers helped reveal some trends and manifestations in the literature of simulation studies on service systems, such as the industries where they are applied, motivations of these studies, types of solutions offered, and insights regarding implementation. Furthermore, we offer suggestions on how simulation studies can implement their recommended solutions, such as encouraging more collaboration between researchers and industry practitioners as well as the consideration of resource-neutral solutions which do not require additional cost for the organization to adopt.","PeriodicalId":306461,"journal":{"name":"2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122007633","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 : 2020-04-01DOI: 10.1109/ICIEA49774.2020.9102008
A. Susanty, N. B. Puspitasari, N. Susanto, S. Renaldi
the main purpose of this paper is to analyze the important success factors influencing the performance of dairy milk supply in three different regencies (West Java, Central Java, and East Java) by applying the Decision-making Trial and Evaluation Laboratory (DEMATEL) method. Ten success factors were employed from the previous study. In this study, seven, five, and eight experts were involved to determine the degree of direct influence between two success factors through a pairwise comparison for West Java, Central Java, and East Java respectively. The results revealed that the top three success factor affecting the performance of the dairy supply chain in three regencies is different. Based on this condition, this paper provides different practical suggestion for relevant agency and policymakers for each regency.
{"title":"Using a DEMATEL Method to Prioritize the Factors Contributed to the Performance Dairy Milk Supply: A Comparative Analysis","authors":"A. Susanty, N. B. Puspitasari, N. Susanto, S. Renaldi","doi":"10.1109/ICIEA49774.2020.9102008","DOIUrl":"https://doi.org/10.1109/ICIEA49774.2020.9102008","url":null,"abstract":"the main purpose of this paper is to analyze the important success factors influencing the performance of dairy milk supply in three different regencies (West Java, Central Java, and East Java) by applying the Decision-making Trial and Evaluation Laboratory (DEMATEL) method. Ten success factors were employed from the previous study. In this study, seven, five, and eight experts were involved to determine the degree of direct influence between two success factors through a pairwise comparison for West Java, Central Java, and East Java respectively. The results revealed that the top three success factor affecting the performance of the dairy supply chain in three regencies is different. Based on this condition, this paper provides different practical suggestion for relevant agency and policymakers for each regency.","PeriodicalId":306461,"journal":{"name":"2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125729873","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 : 2020-04-01DOI: 10.1109/iciea49774.2020.9101947
{"title":"Copyright","authors":"","doi":"10.1109/iciea49774.2020.9101947","DOIUrl":"https://doi.org/10.1109/iciea49774.2020.9101947","url":null,"abstract":"","PeriodicalId":306461,"journal":{"name":"2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125118826","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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