A Generic Data Analytics System for Manufacturing Production
The increase in the amount of manufacturing information available means that big data can be collected and, with appropriate deep analysis, could be of great value to manufacturers. However, most small manufacturers cannot afford the overhead of a professional data analytics team. To address this pr...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Tsinghua University Press
2018-06-01
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| Series: | Big Data Mining and Analytics |
| Subjects: | |
| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2018.9020016 |
| _version_ | 1811250420856651776 |
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| author | Hao Zhang Hongzhi Wang Jianzhong Li Hong Gao |
| author_facet | Hao Zhang Hongzhi Wang Jianzhong Li Hong Gao |
| author_sort | Hao Zhang |
| collection | DOAJ |
| description | The increase in the amount of manufacturing information available means that big data can be collected and, with appropriate deep analysis, could be of great value to manufacturers. However, most small manufacturers cannot afford the overhead of a professional data analytics team. To address this problem, in this paper a generic data analytics system, Generic Manufacturing Data Analytics system (GMDA), is proposed. This system can perform most manufacturing data analytics tasks and users can easily carry out data analysis even if they have no prior knowledge or experience of data analytics. To establish such a system, we designed an abstract language, GMDL, to describe the manufacturing data analytics tasks. Aimed at factory data analytics, several algorithms were selected, tuned, optimized, and finally integrated into the system. Some noteworthy techniques were developed in GMDA such as proper algorithm selection strategy and an optimal parameter determination algorithm. Case studies show the practicability and reliability of the system. |
| first_indexed | 2024-04-12T16:04:27Z |
| format | Article |
| id | doaj.art-6aa3bf753bf645fbaccf9b69724aa5e3 |
| institution | Directory Open Access Journal |
| issn | 2096-0654 |
| language | English |
| last_indexed | 2024-04-12T16:04:27Z |
| publishDate | 2018-06-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Big Data Mining and Analytics |
| spelling | doaj.art-6aa3bf753bf645fbaccf9b69724aa5e32022-12-22T03:26:07ZengTsinghua University PressBig Data Mining and Analytics2096-06542018-06-011216017110.26599/BDMA.2018.9020016A Generic Data Analytics System for Manufacturing ProductionHao Zhang0Hongzhi Wang1Jianzhong Li2Hong Gao3<institution content-type="dept">Department of Computer Science and Technology</institution>, <institution>Harbin Institute of Technology</institution>, <city>Harbin</city> <postal-code>150001</postal-code>, <country>China</country>.<institution content-type="dept">Department of Computer Science and Technology</institution>, <institution>Harbin Institute of Technology</institution>, <city>Harbin</city> <postal-code>150001</postal-code>, <country>China</country>.<institution content-type="dept">Department of Computer Science and Technology</institution>, <institution>Harbin Institute of Technology</institution>, <city>Harbin</city> <postal-code>150001</postal-code>, <country>China</country>.<institution content-type="dept">Department of Computer Science and Technology</institution>, <institution>Harbin Institute of Technology</institution>, <city>Harbin</city> <postal-code>150001</postal-code>, <country>China</country>.The increase in the amount of manufacturing information available means that big data can be collected and, with appropriate deep analysis, could be of great value to manufacturers. However, most small manufacturers cannot afford the overhead of a professional data analytics team. To address this problem, in this paper a generic data analytics system, Generic Manufacturing Data Analytics system (GMDA), is proposed. This system can perform most manufacturing data analytics tasks and users can easily carry out data analysis even if they have no prior knowledge or experience of data analytics. To establish such a system, we designed an abstract language, GMDL, to describe the manufacturing data analytics tasks. Aimed at factory data analytics, several algorithms were selected, tuned, optimized, and finally integrated into the system. Some noteworthy techniques were developed in GMDA such as proper algorithm selection strategy and an optimal parameter determination algorithm. Case studies show the practicability and reliability of the system.https://www.sciopen.com/article/10.26599/BDMA.2018.9020016manufactorydata analyticsdata miningoptimization |
| spellingShingle | Hao Zhang Hongzhi Wang Jianzhong Li Hong Gao A Generic Data Analytics System for Manufacturing Production Big Data Mining and Analytics manufactory data analytics data mining optimization |
| title | A Generic Data Analytics System for Manufacturing Production |
| title_full | A Generic Data Analytics System for Manufacturing Production |
| title_fullStr | A Generic Data Analytics System for Manufacturing Production |
| title_full_unstemmed | A Generic Data Analytics System for Manufacturing Production |
| title_short | A Generic Data Analytics System for Manufacturing Production |
| title_sort | generic data analytics system for manufacturing production |
| topic | manufactory data analytics data mining optimization |
| url | https://www.sciopen.com/article/10.26599/BDMA.2018.9020016 |
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