Pub Date : 2023-04-17DOI: 10.1109/SysCon53073.2023.10131051
Natalie Holliday, L. D. Otero
This research describes the construction of a discrete-event simulation model of the operations of servicing offshore wind turbines within offshore wind farms with the objective of optimizing cash flow. Specifically, the simulation model looks at alternate support vessels that carry crew to and from farms while completing operation and maintenance activities. Historical data were used to validate the model as well as data from prior simulation models. The simulation is able to identify feasibility concerns by analyzing four alternatives: the use of crew transport vessels (CTVs), adding an additional CTV, use of standard surface effect ships (SESs), and the use of optimized SESs. Of these alternatives, the number of support vessels, type of support vessel, and replacement of heavy-failure components can be assessed. The results showed that the average cash flows of the different alternatives were significantly different. Conclusions were made based on the results from the simulation study, and further research opportunities were identified.
{"title":"A Simulation Model for the Optimization of Crew Transport Vessels to Service Offshore Wind Farms","authors":"Natalie Holliday, L. D. Otero","doi":"10.1109/SysCon53073.2023.10131051","DOIUrl":"https://doi.org/10.1109/SysCon53073.2023.10131051","url":null,"abstract":"This research describes the construction of a discrete-event simulation model of the operations of servicing offshore wind turbines within offshore wind farms with the objective of optimizing cash flow. Specifically, the simulation model looks at alternate support vessels that carry crew to and from farms while completing operation and maintenance activities. Historical data were used to validate the model as well as data from prior simulation models. The simulation is able to identify feasibility concerns by analyzing four alternatives: the use of crew transport vessels (CTVs), adding an additional CTV, use of standard surface effect ships (SESs), and the use of optimized SESs. Of these alternatives, the number of support vessels, type of support vessel, and replacement of heavy-failure components can be assessed. The results showed that the average cash flows of the different alternatives were significantly different. Conclusions were made based on the results from the simulation study, and further research opportunities were identified.","PeriodicalId":169296,"journal":{"name":"2023 IEEE International Systems Conference (SysCon)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131108535","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 : 2023-04-17DOI: 10.1109/SysCon53073.2023.10131064
J. Al-Jaroodi, N. Mohamed, Nader Kesserwan, I. Jawhar
Recent advances in digitalizing healthcare services and related systems show great promise of effective use of technology to enhance the healthcare sector. Healthcare and healthcare-related industries are moving forward with the adoption of various smart services and Healthcare 4.0 systems to reduce costs, improve care, and enhance patient satisfaction. However, the research and development communities are offering a lot of innovative frameworks, applications and techniques to fully transform the healthcare industry into Healthcare 4.0. Adopting such technologies and solutions face various challenges. Some are technical and many of these are solvable, some financial, which can be addressed, somehow; yet, there are other obstacles hindering the efforts, namely, humans! Smart systems in general are invasive and require people to accept how these systems will be involved in their every day life. This leads to another important aspect, trust, as such invasive behavior require humans to trust these systems and those who operate them. They may also replace human interactions, which many see as essential for successful patient/practitioner relationships. Moreover, some view these as replacement for human workers, which may lead to layoffs and financial hardships. In this paper, we investigate the human factor affecting the acceptance and adoption of Healthcare 4.0 and smart healthcare systems among the different stakeholders. We will review current work on the topic and identify the major factors with respect to how they affect stakeholders and whether these are solvable with advances in technology. We see that technology can help solve many of the issues affecting human’s acceptance, yet there are also ones that are not, no matter how advanced the technology can get.
{"title":"Human Factors Affecting the Adoption of Healthcare 4.0","authors":"J. Al-Jaroodi, N. Mohamed, Nader Kesserwan, I. Jawhar","doi":"10.1109/SysCon53073.2023.10131064","DOIUrl":"https://doi.org/10.1109/SysCon53073.2023.10131064","url":null,"abstract":"Recent advances in digitalizing healthcare services and related systems show great promise of effective use of technology to enhance the healthcare sector. Healthcare and healthcare-related industries are moving forward with the adoption of various smart services and Healthcare 4.0 systems to reduce costs, improve care, and enhance patient satisfaction. However, the research and development communities are offering a lot of innovative frameworks, applications and techniques to fully transform the healthcare industry into Healthcare 4.0. Adopting such technologies and solutions face various challenges. Some are technical and many of these are solvable, some financial, which can be addressed, somehow; yet, there are other obstacles hindering the efforts, namely, humans! Smart systems in general are invasive and require people to accept how these systems will be involved in their every day life. This leads to another important aspect, trust, as such invasive behavior require humans to trust these systems and those who operate them. They may also replace human interactions, which many see as essential for successful patient/practitioner relationships. Moreover, some view these as replacement for human workers, which may lead to layoffs and financial hardships. In this paper, we investigate the human factor affecting the acceptance and adoption of Healthcare 4.0 and smart healthcare systems among the different stakeholders. We will review current work on the topic and identify the major factors with respect to how they affect stakeholders and whether these are solvable with advances in technology. We see that technology can help solve many of the issues affecting human’s acceptance, yet there are also ones that are not, no matter how advanced the technology can get.","PeriodicalId":169296,"journal":{"name":"2023 IEEE International Systems Conference (SysCon)","volume":"161 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126932984","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 : 2023-04-17DOI: 10.1109/SysCon53073.2023.10131107
H. Y. Tao, Nicole Hutchison, Megan M. Clifford, G. Kerr, P. Beling, Tim Sherburne, Paul Wach, David Long, Craig Arndt, D. Verma, Thomas A. McDermott
This paper presents the ongoing Year 2 of digital engineering (DE) simulation curriculum development by a research team from the Systems Engineering Research Center (SERC). This task, sponsored by the Defense Acquisition University (DAU), builds on the extensive DE research portfolio in SERC and leverages the existing literature in the systems engineering and DE communities. The goal of the research is to create a robust learning platform with relevant hands-on modeling and simulation experience that can be used to improve students’ DE proficiency levels across the workforce. Part of this research effort includes DAU’s partnership with SERC to develop a Simulation Training Environment for Digital Engineering (STEDE), which is intended to provide infrastructure and example case studies that allow DAU students to interact directly with models. The paper describes the curriculum development and modeling efforts to-date and addresses challenges associated with the development of the learning materials. An Advisory Board was established to provide guidance and expert knowledge in DE as the team is developing the DE curriculum. Working with the Advisory Board, the team discovered some critical skill gaps in DE which provide an opportunity for the team to further enhance the training and curriculum development to modernize the defense acquisition workforce.
{"title":"Challenges and Opportunities in the Digital Engineering Simulation Curriculum Development","authors":"H. Y. Tao, Nicole Hutchison, Megan M. Clifford, G. Kerr, P. Beling, Tim Sherburne, Paul Wach, David Long, Craig Arndt, D. Verma, Thomas A. McDermott","doi":"10.1109/SysCon53073.2023.10131107","DOIUrl":"https://doi.org/10.1109/SysCon53073.2023.10131107","url":null,"abstract":"This paper presents the ongoing Year 2 of digital engineering (DE) simulation curriculum development by a research team from the Systems Engineering Research Center (SERC). This task, sponsored by the Defense Acquisition University (DAU), builds on the extensive DE research portfolio in SERC and leverages the existing literature in the systems engineering and DE communities. The goal of the research is to create a robust learning platform with relevant hands-on modeling and simulation experience that can be used to improve students’ DE proficiency levels across the workforce. Part of this research effort includes DAU’s partnership with SERC to develop a Simulation Training Environment for Digital Engineering (STEDE), which is intended to provide infrastructure and example case studies that allow DAU students to interact directly with models. The paper describes the curriculum development and modeling efforts to-date and addresses challenges associated with the development of the learning materials. An Advisory Board was established to provide guidance and expert knowledge in DE as the team is developing the DE curriculum. Working with the Advisory Board, the team discovered some critical skill gaps in DE which provide an opportunity for the team to further enhance the training and curriculum development to modernize the defense acquisition workforce.","PeriodicalId":169296,"journal":{"name":"2023 IEEE International Systems Conference (SysCon)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133598543","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 : 2023-04-17DOI: 10.1109/SysCon53073.2023.10131068
Gisela A. Garza Morales, K. Nizamis, G. M. Bonnema
Background: An alternative to the difficulty of defining complexity is to explore its origins. This promising way of dealing with complexity, however, is currently hindered by a major shortcoming. We currently have various perspectives, terms, contexts, complexity study objectives, etc. This impedes consensus and overview of the complexity origins within the systems engineering communityObjective: We explored this variety through a scoping review covering the variety in the complexity terms (RQ1), complexity classifications (RQ2), engineering contexts (RQ3), and complexity study objectives (RQ4).Design: Four online databases were used to identify papers published 2012-2022, from which we selected 72 publications. Included publications had the word "complexity" in their title and abstract and discussed its origins or classifications.Results: We mapped 42 terms referring to complexity origins. We found over 300 classes and subclasses of complexity, which we organized in 31 clusters. We identified 29 engineering contexts interested in complexity origins. Finally, we identified five complexity study objectives, and their mapping showed that less than half the screened papers (31) were concered with identification of complexity origins.Conclusions: While it might not be necessary (or even possible) to have one single term or one single classification, it is currently very difficult to work with the extremely large number of different terms, and classes. Future efforts should also focus on unification, clarification, and standardization of the terminology and the classifications of complexity origins, which can get us closer to reaping the benefits of the already existing contributions.
{"title":"Why is there complexity in engineering? A scoping review on complexity origins","authors":"Gisela A. Garza Morales, K. Nizamis, G. M. Bonnema","doi":"10.1109/SysCon53073.2023.10131068","DOIUrl":"https://doi.org/10.1109/SysCon53073.2023.10131068","url":null,"abstract":"Background: An alternative to the difficulty of defining complexity is to explore its origins. This promising way of dealing with complexity, however, is currently hindered by a major shortcoming. We currently have various perspectives, terms, contexts, complexity study objectives, etc. This impedes consensus and overview of the complexity origins within the systems engineering communityObjective: We explored this variety through a scoping review covering the variety in the complexity terms (RQ1), complexity classifications (RQ2), engineering contexts (RQ3), and complexity study objectives (RQ4).Design: Four online databases were used to identify papers published 2012-2022, from which we selected 72 publications. Included publications had the word \"complexity\" in their title and abstract and discussed its origins or classifications.Results: We mapped 42 terms referring to complexity origins. We found over 300 classes and subclasses of complexity, which we organized in 31 clusters. We identified 29 engineering contexts interested in complexity origins. Finally, we identified five complexity study objectives, and their mapping showed that less than half the screened papers (31) were concered with identification of complexity origins.Conclusions: While it might not be necessary (or even possible) to have one single term or one single classification, it is currently very difficult to work with the extremely large number of different terms, and classes. Future efforts should also focus on unification, clarification, and standardization of the terminology and the classifications of complexity origins, which can get us closer to reaping the benefits of the already existing contributions.","PeriodicalId":169296,"journal":{"name":"2023 IEEE International Systems Conference (SysCon)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130759372","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 : 2023-04-17DOI: 10.1109/SysCon53073.2023.10131109
J. Colombi, Travis W. Odom, Warren J Connell
The research shows how to improve the Test and Evaluation Strategy (TES) during developmental test and evaluation (DT&E), supported by Model-based Systems Engineering and the System Modeling Language. Specifically, a domain-specific Department of Defense (DoD) testing profile was developed called UTP-D. The profile combines aspects of the UML Testing Profile (UTP) and the Test Description Language (TDL) standard. It captures required test information and relationships and adheres to the language used throughout DoD directives and instructions. As a demonstration, the profile was used to model and simulate developmental tests for a prototype hybrid SUV, specifically acceleration and safety tests. Using domain-specific modeling for DT&E could improve test planning and show how to continue the DoD digital transformation of acquisition processes.
{"title":"A DoD Testing Profile: MBSE for Test and Evaluation Strategy","authors":"J. Colombi, Travis W. Odom, Warren J Connell","doi":"10.1109/SysCon53073.2023.10131109","DOIUrl":"https://doi.org/10.1109/SysCon53073.2023.10131109","url":null,"abstract":"The research shows how to improve the Test and Evaluation Strategy (TES) during developmental test and evaluation (DT&E), supported by Model-based Systems Engineering and the System Modeling Language. Specifically, a domain-specific Department of Defense (DoD) testing profile was developed called UTP-D. The profile combines aspects of the UML Testing Profile (UTP) and the Test Description Language (TDL) standard. It captures required test information and relationships and adheres to the language used throughout DoD directives and instructions. As a demonstration, the profile was used to model and simulate developmental tests for a prototype hybrid SUV, specifically acceleration and safety tests. Using domain-specific modeling for DT&E could improve test planning and show how to continue the DoD digital transformation of acquisition processes.","PeriodicalId":169296,"journal":{"name":"2023 IEEE International Systems Conference (SysCon)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132868297","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 : 2023-04-17DOI: 10.1109/SysCon53073.2023.10131074
Viviana Lopez, Aditya Akundi
As the complexity of both products and systems increases across a wide range of industry sectors, there has been an influx in demand for methods of system organization and optimization. MBSE enhances the ability to obtain, analyze, communicate, and manage data on a comprehensive architecture of a system. In this study, a military combat surveillance scenario is modeled using SysML generating state machine diagrams and activity diagrams using the Magic Model Analyst execution framework plugin. This study seeks to prove the feasibility of an MBSE-enabled framework using SysML to create and simulate a surveillance system that monitors and reports on the health status and performance of an armored fighting vehicle (combat tank) through an Unmanned Ariel Vehicle (UAV). The Magic System of Systems Architect, which actively promotes system development architectural frameworks, was used to construct SysML-compliant models, allowing the creation of intricate model diagrams. The construction of the UAV surveillance scenario emphasized the capability of modifying a diagram feature and ensuring that the alteration is communicated to all linked model diagrams. This study builds on a previously published MBSE-enabled conceptual framework for creating digital twins. The purpose of this research is to test and validate the framework's procedures.
随着产品和系统的复杂性在广泛的工业部门中不断增加，对系统组织和优化方法的需求不断增加。MBSE增强了在系统的综合体系结构上获取、分析、通信和管理数据的能力。在本研究中，使用SysML对军事战斗监视场景进行建模，使用Magic Model Analyst执行框架插件生成状态机图和活动图。该研究旨在证明使用SysML创建和模拟监视系统的mbse支持框架的可行性，该监视系统通过无人驾驶Ariel车辆(UAV)监视和报告装甲战车(战斗坦克)的健康状态和性能。系统架构师的神奇系统，它积极地促进了系统开发架构框架，被用来构造符合sysml的模型，允许创建复杂的模型图。无人机监视场景的构建强调修改图特征的能力，并确保将更改传达给所有链接的模型图。这项研究建立在先前发表的用于创建数字双胞胎的mbse支持的概念框架之上。本研究的目的是测试和验证框架的程序。
{"title":"Modeling A UAV Surveillance Scenario- An Applied MBSE Approach","authors":"Viviana Lopez, Aditya Akundi","doi":"10.1109/SysCon53073.2023.10131074","DOIUrl":"https://doi.org/10.1109/SysCon53073.2023.10131074","url":null,"abstract":"As the complexity of both products and systems increases across a wide range of industry sectors, there has been an influx in demand for methods of system organization and optimization. MBSE enhances the ability to obtain, analyze, communicate, and manage data on a comprehensive architecture of a system. In this study, a military combat surveillance scenario is modeled using SysML generating state machine diagrams and activity diagrams using the Magic Model Analyst execution framework plugin. This study seeks to prove the feasibility of an MBSE-enabled framework using SysML to create and simulate a surveillance system that monitors and reports on the health status and performance of an armored fighting vehicle (combat tank) through an Unmanned Ariel Vehicle (UAV). The Magic System of Systems Architect, which actively promotes system development architectural frameworks, was used to construct SysML-compliant models, allowing the creation of intricate model diagrams. The construction of the UAV surveillance scenario emphasized the capability of modifying a diagram feature and ensuring that the alteration is communicated to all linked model diagrams. This study builds on a previously published MBSE-enabled conceptual framework for creating digital twins. The purpose of this research is to test and validate the framework's procedures.","PeriodicalId":169296,"journal":{"name":"2023 IEEE International Systems Conference (SysCon)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133291551","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 : 2023-04-17DOI: 10.1109/SysCon53073.2023.10131094
Mohammadreza Torkjazi, Ali K. Raz
Multi-Attribute Decision Making (MADM) methods are an integral component of trade-off studies which are frequently employed in Systems Engineering when multiple interdependent decision criteria are involved. In MADM methods, each decision criterion is assigned a weight based on how important it is to the Decision-Makers (DMs), and a decision matrix is populated with values representing assessments of each alternative with respect to the decision criteria. MADM methods, therefore, are susceptible to subjectivity due to inherent bias in DM’s preferences where slight fluctuation in stated DM’s preference can drastically impact the outcome. In this paper, we propose a data-driven methodology with Machine Learning to improve the effectiveness of MADM methods by reducing DMs’ subjective biases resulting from criteria weights. In addition, the proposed methodology leverages Exploratory Data Analysis to better determine the type of criteria as cost or benefit, depending upon whether it positively or negatively affects the MADM outcome. A sample trade study example of selecting a metropolitan area based on housing affordability is provided to illustrate how the proposed method is applied to generate data-based true criteria weights and types.
{"title":"Data-Driven Approach with Machine Learning to Reduce Subjectivity in Multi-Attribute Decision Making Methods","authors":"Mohammadreza Torkjazi, Ali K. Raz","doi":"10.1109/SysCon53073.2023.10131094","DOIUrl":"https://doi.org/10.1109/SysCon53073.2023.10131094","url":null,"abstract":"Multi-Attribute Decision Making (MADM) methods are an integral component of trade-off studies which are frequently employed in Systems Engineering when multiple interdependent decision criteria are involved. In MADM methods, each decision criterion is assigned a weight based on how important it is to the Decision-Makers (DMs), and a decision matrix is populated with values representing assessments of each alternative with respect to the decision criteria. MADM methods, therefore, are susceptible to subjectivity due to inherent bias in DM’s preferences where slight fluctuation in stated DM’s preference can drastically impact the outcome. In this paper, we propose a data-driven methodology with Machine Learning to improve the effectiveness of MADM methods by reducing DMs’ subjective biases resulting from criteria weights. In addition, the proposed methodology leverages Exploratory Data Analysis to better determine the type of criteria as cost or benefit, depending upon whether it positively or negatively affects the MADM outcome. A sample trade study example of selecting a metropolitan area based on housing affordability is provided to illustrate how the proposed method is applied to generate data-based true criteria weights and types.","PeriodicalId":169296,"journal":{"name":"2023 IEEE International Systems Conference (SysCon)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133980622","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 : 2023-04-17DOI: 10.1109/SysCon53073.2023.10131099
Dean Revell, David C. Gross, Gong Zhou, Adrian Hernandez
The present work reports on experiences gleaned in the application of systems engineering on a research project whose objective is technology development. The benefits of systems engineering for system development throughout the lifecycle are well known. Inclusion of systems engineering has a measurable and significant beneficial effect on system development project performance measured by costs, schedules, and features implemented. Technology development however differs from product or service-oriented development and the potential systems engineering for such are unknown. The authors sought to utilize proven MBSE methodologies to aid in a research project for an emerging technology. The project addressed by the present work was a Phase I Small Business Innovative Research Project to determine the feasibility and utility of wireless acoustic power transfer systems in an operational environment. The purpose of this paper therefore is to report on the selection and application of a MBSE methodology for this small-scale technology development program. A summary of the work performed by the MBSE team is given, along with example modeling products and their intended uses. It discusses missteps as well as successes and from its findings proposes additional research to develop a method to evaluate these methodologies based on the nature of the project.
{"title":"Applying a MBSE Methodology in Small Scale Technology Development 1","authors":"Dean Revell, David C. Gross, Gong Zhou, Adrian Hernandez","doi":"10.1109/SysCon53073.2023.10131099","DOIUrl":"https://doi.org/10.1109/SysCon53073.2023.10131099","url":null,"abstract":"The present work reports on experiences gleaned in the application of systems engineering on a research project whose objective is technology development. The benefits of systems engineering for system development throughout the lifecycle are well known. Inclusion of systems engineering has a measurable and significant beneficial effect on system development project performance measured by costs, schedules, and features implemented. Technology development however differs from product or service-oriented development and the potential systems engineering for such are unknown. The authors sought to utilize proven MBSE methodologies to aid in a research project for an emerging technology. The project addressed by the present work was a Phase I Small Business Innovative Research Project to determine the feasibility and utility of wireless acoustic power transfer systems in an operational environment. The purpose of this paper therefore is to report on the selection and application of a MBSE methodology for this small-scale technology development program. A summary of the work performed by the MBSE team is given, along with example modeling products and their intended uses. It discusses missteps as well as successes and from its findings proposes additional research to develop a method to evaluate these methodologies based on the nature of the project.","PeriodicalId":169296,"journal":{"name":"2023 IEEE International Systems Conference (SysCon)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114569572","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 : 2023-04-17DOI: 10.1109/SysCon53073.2023.10131138
Muhammad Hayyan Bin Shahid, Akramul Azim
Faults in a transmission line (TL) are the most common faults faced by almost every power station. Suppose these faults are not detected in time. In that case, they can result in multiple losses, such as a loss in an estimated power generation w.r.t predicted time and financial losses. In order to investigate the fault, the systematic approach of an engineer would be first to detect whether there is a fault or not. If a fault is detected in the transmission line, it should be classified as soon as possible. The following classifications would help the maintenance team identify the fault type: line fault, line-to-line fault, double line fault, triple line fault, single-line-to-ground fault, double line-to-ground fault, three-phase fault, and no fault. This paper proposes that the ensemble method, using the Machine Learning (ML) technique, will help the engineers detect and classify the faults in the transmission line. The investigation also trained and tested multiple ML classifiers to inform better recommendations. The shared research will help the user find the best possible ML results for predicting faults in the transmission line. Hence early and accurate fault detection will enhance safety and reliability and reduce interruption and downtime.
{"title":"Ensemble Method For Fault Detection & Classification in Transmission Lines Using ML","authors":"Muhammad Hayyan Bin Shahid, Akramul Azim","doi":"10.1109/SysCon53073.2023.10131138","DOIUrl":"https://doi.org/10.1109/SysCon53073.2023.10131138","url":null,"abstract":"Faults in a transmission line (TL) are the most common faults faced by almost every power station. Suppose these faults are not detected in time. In that case, they can result in multiple losses, such as a loss in an estimated power generation w.r.t predicted time and financial losses. In order to investigate the fault, the systematic approach of an engineer would be first to detect whether there is a fault or not. If a fault is detected in the transmission line, it should be classified as soon as possible. The following classifications would help the maintenance team identify the fault type: line fault, line-to-line fault, double line fault, triple line fault, single-line-to-ground fault, double line-to-ground fault, three-phase fault, and no fault. This paper proposes that the ensemble method, using the Machine Learning (ML) technique, will help the engineers detect and classify the faults in the transmission line. The investigation also trained and tested multiple ML classifiers to inform better recommendations. The shared research will help the user find the best possible ML results for predicting faults in the transmission line. Hence early and accurate fault detection will enhance safety and reliability and reduce interruption and downtime.","PeriodicalId":169296,"journal":{"name":"2023 IEEE International Systems Conference (SysCon)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114617873","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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