1006861.pdf
This open access work presents selected results from the European research and innovation project IMPROVE which yielded novel data-based solutions to enhance machine reliability and efficiency in the fields of simulation and optimization, condition monitoring, alarm management, and quality predictio...
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Springer Nature
2020
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| Διαθέσιμο Online: | https://www.springer.com/9783662578056 |
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oapen-20.500.12657-23294 |
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oapen-20.500.12657-232942024-03-22T19:23:41Z IMPROVE - Innovative Modelling Approaches for Production Systems to Raise Validatable Efficiency Niggemann, Oliver Schüller, Peter Engineering Quality control Reliability Industrial safety Robotics Automation Input-output equipment (Computers) thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGP Production and industrial engineering::TGPR Reliability engineering thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering::TJFM1 Robotics thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications This open access work presents selected results from the European research and innovation project IMPROVE which yielded novel data-based solutions to enhance machine reliability and efficiency in the fields of simulation and optimization, condition monitoring, alarm management, and quality prediction. 2020-03-18 13:36:15 2020-04-01T09:10:30Z 2020-04-01T09:10:30Z 2018 book 1006861 http://library.oapen.org/handle/20.500.12657/23294 eng Technologien für die intelligente Automation application/pdf n/a 1006861.pdf https://www.springer.com/9783662578056 Springer Nature 10.1007/978-3-662-57805-6 10.1007/978-3-662-57805-6 6c6992af-b843-4f46-859c-f6e9998e40d5 129 Berlin, Heidelberg open access |
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OAPEN |
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English |
| description |
This open access work presents selected results from the European research and innovation project IMPROVE which yielded novel data-based solutions to enhance machine reliability and efficiency in the fields of simulation and optimization, condition monitoring, alarm management, and quality prediction. |
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1006861.pdf |
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1006861.pdf |
| title_full |
1006861.pdf |
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1006861.pdf |
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| publisher |
Springer Nature |
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2020 |
| url |
https://www.springer.com/9783662578056 |
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1799945309014458368 |
