{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/146660"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/146660","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Development of Industrial Internet of Things Architecture and Business Strategy for Digital Substation Asset Management","abstract":"MR is a medium-sized, family owned company that is a market leader in electrical substation component manufacturing, especially the on-load tap changer for transformers. However, as changes in the industry are creating new competitors and demand for higher quality and efficiency, there is now an increased need to employ new technology focused on connectivity and data to maintain the current leadership. Application of Industrial Internet of Things (IIoT) in the context of substation asset management is thus considered as a possible business value proposition. Market status based on customer interviews showed that while many utilities were eager to adopt IIoT technologies to their operations, lack of standardization and data literacy hindered the adoption process. An architecture of IIoT for MR, based on existing industry standards, was created to guide the company in deploying IIoT-based services to their customers. A potential use-case of on-load tap changer vibroacoustic monitoring sensor anomaly detection using artificial neural network autoencoder is explored as an enabled application of the IIoT technology. The autoencoder was able to discern artificially introduced anomaly in real vibroacoustic monitoring data.","abstract_html":"MR is a medium-sized, family owned company that is a market leader in electrical substation component manufacturing, especially the on-load tap changer for transformers. However, as changes in the industry are creating new competitors and demand for higher quality and efficiency, there is now an increased need to employ new technology focused on connectivity and data to maintain the current leadership. Application of Industrial Internet of Things (IIoT) in the context of substation asset management is thus considered as a possible business value proposition. Market status based on customer interviews showed that while many utilities were eager to adopt IIoT technologies to their operations, lack of standardization and data literacy hindered the adoption process. An architecture of IIoT for MR, based on existing industry standards, was created to guide the company in deploying IIoT-based services to their customers. A potential use-case of on-load tap changer vibroacoustic monitoring sensor anomaly detection using artificial neural network autoencoder is explored as an enabled application of the IIoT technology. The autoencoder was able to discern artificially introduced anomaly in real vibroacoustic monitoring data.","abstract_has_math":false,"creators":["Kim, Hunjoo"],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. 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However, as changes in the industry are creating new competitors and demand for higher quality and efficiency, there is now an increased need to employ new technology focused on connectivity and data to maintain the current leadership. Application of Industrial Internet of Things (IIoT) in the context of substation asset management is thus considered as a possible business value proposition. Market status based on customer interviews showed that while many utilities were eager to adopt IIoT technologies to their operations, lack of standardization and data literacy hindered the adoption process. An architecture of IIoT for MR, based on existing industry standards, was created to guide the company in deploying IIoT-based services to their customers. A potential use-case of on-load tap changer vibroacoustic monitoring sensor anomaly detection using artificial neural network autoencoder is explored as an enabled application of the IIoT technology. 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