Visually enhanced situation awareness for complex manufacturing facility monitoring in smart factories
With the widespread application of networked information-based technologies throughout industry manufacturing, modern manufacturing facilities give rise to unprecedented levels of process data generation. Data-rich manufacturing environments provide a broad stage on which advanced data analytics pla...
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Published in | Journal of visual languages and computing Vol. 44; pp. 58 - 69 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.02.2018
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Subjects | |
Online Access | Get full text |
ISSN | 1045-926X 1095-8533 |
DOI | 10.1016/j.jvlc.2017.11.004 |
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Abstract | With the widespread application of networked information-based technologies throughout industry manufacturing, modern manufacturing facilities give rise to unprecedented levels of process data generation. Data-rich manufacturing environments provide a broad stage on which advanced data analytics play leading roles in creating manufacturing intelligence to support operational efficiency and process innovation. In this paper, we introduce a process data analysis solution that integrates the technologies of situation awareness and visual analytics for the routine monitoring and troubleshooting of roller hearth kiln (RHK), a complex key manufacturing facility for lithium battery cathode materials. Guided by a set of detailed scenarios and requirement analyses, we first propose a qualitative and quantitative situation assessment model to generate the comprehensive description of RHK's operating situation. An informative visual analysis system then is designed and implemented to enhance the users’ abilities of situation perception and understanding for insightful anomaly root cause reasoning and efficient decision making. We conduct case studies and a user interview together with the managers and operators from manufacturing sites as system evaluation. The result demonstrates its effectiveness and prospects its possible inspiration for other similar scenarios about complex manufacturing facility monitoring in smart factories. |
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AbstractList | With the widespread application of networked information-based technologies throughout industry manufacturing, modern manufacturing facilities give rise to unprecedented levels of process data generation. Data-rich manufacturing environments provide a broad stage on which advanced data analytics play leading roles in creating manufacturing intelligence to support operational efficiency and process innovation. In this paper, we introduce a process data analysis solution that integrates the technologies of situation awareness and visual analytics for the routine monitoring and troubleshooting of roller hearth kiln (RHK), a complex key manufacturing facility for lithium battery cathode materials. Guided by a set of detailed scenarios and requirement analyses, we first propose a qualitative and quantitative situation assessment model to generate the comprehensive description of RHK's operating situation. An informative visual analysis system then is designed and implemented to enhance the users’ abilities of situation perception and understanding for insightful anomaly root cause reasoning and efficient decision making. We conduct case studies and a user interview together with the managers and operators from manufacturing sites as system evaluation. The result demonstrates its effectiveness and prospects its possible inspiration for other similar scenarios about complex manufacturing facility monitoring in smart factories. |
Author | Lin, Xiaoru Chen, Yi Chen, Ning Gui, Weihua Luo, Xiaobo Zhou, Fangfang Zhao, Ying |
Author_xml | – sequence: 1 givenname: Fangfang surname: Zhou fullname: Zhou, Fangfang organization: School of Information Science and Engineering, Central South University, Changsha, Hunan, China – sequence: 2 givenname: Xiaoru surname: Lin fullname: Lin, Xiaoru organization: School of Information Science and Engineering, Central South University, Changsha, Hunan, China – sequence: 3 givenname: Xiaobo surname: Luo fullname: Luo, Xiaobo organization: School of Information Science and Engineering, Central South University, Changsha, Hunan, China – sequence: 4 givenname: Ying surname: Zhao fullname: Zhao, Ying email: zhaoying@csu.edu.cn organization: School of Information Science and Engineering, Central South University, Changsha, Hunan, China – sequence: 5 givenname: Yi surname: Chen fullname: Chen, Yi organization: Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing, China – sequence: 6 givenname: Ning surname: Chen fullname: Chen, Ning organization: School of Information Science and Engineering, Central South University, Changsha, Hunan, China – sequence: 7 givenname: Weihua surname: Gui fullname: Gui, Weihua organization: School of Information Science and Engineering, Central South University, Changsha, Hunan, China |
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Keywords | Situation awareness Roller Hearth Kiln Visual analytics Smart factory Manufacturing industry |
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SubjectTerms | Manufacturing industry Roller Hearth Kiln Situation awareness Smart factory Visual analytics |
Title | Visually enhanced situation awareness for complex manufacturing facility monitoring in smart factories |
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