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Material Disposition and Scheduling in Regeneration Processes using Prognostic Data Mining

Bibliographic Details
Journal Title: Procedia Manufacturing
Authors and Corporations: Heuer, Tammo, Lucht, Torben, Nyhuis, Peter
In: Procedia Manufacturing, 43, 2020, p. 208-214
Type of Resource: E-Article
Language: English
published:
Elsevier BV
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rft.atitle Material Disposition and Scheduling in Regeneration Processes using Prognostic Data Mining
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rft.date 2020-01-01
x.date 2020-01-01T00:00:00Z
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Array ( [rft.aulast] => Lucht [rft.aufirst] => Torben )
Array ( [rft.aulast] => Nyhuis [rft.aufirst] => Peter )
doi 10.1016/j.promfg.2020.02.138
languages eng
url http://dx.doi.org/10.1016/j.promfg.2020.02.138
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spelling Heuer, Tammo Lucht, Torben Nyhuis, Peter 2351-9789 Elsevier BV Artificial Intelligence Industrial and Manufacturing Engineering http://dx.doi.org/10.1016/j.promfg.2020.02.138 Material Disposition and Scheduling in Regeneration Processes using Prognostic Data Mining Procedia Manufacturing
spellingShingle Heuer, Tammo, Lucht, Torben, Nyhuis, Peter, Procedia Manufacturing, Material Disposition and Scheduling in Regeneration Processes using Prognostic Data Mining, Artificial Intelligence, Industrial and Manufacturing Engineering
title Material Disposition and Scheduling in Regeneration Processes using Prognostic Data Mining
title_full Material Disposition and Scheduling in Regeneration Processes using Prognostic Data Mining
title_fullStr Material Disposition and Scheduling in Regeneration Processes using Prognostic Data Mining
title_full_unstemmed Material Disposition and Scheduling in Regeneration Processes using Prognostic Data Mining
title_short Material Disposition and Scheduling in Regeneration Processes using Prognostic Data Mining
title_sort material disposition and scheduling in regeneration processes using prognostic data mining
topic Artificial Intelligence, Industrial and Manufacturing Engineering
url http://dx.doi.org/10.1016/j.promfg.2020.02.138