An approach to integrating tactical decision-making in industrial maintenance balance scorecards using principal components analysis and machine learning
DOI10.1155/2017/3759514zbMATH Open1377.90045OpenAlexW2761188801MaRDI QIDQ1688059
Marta Marín, Rosario Domingo, Néstor Rodríguez-Padial
Publication date: 5 January 2018
Published in: Complexity (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1155/2017/3759514
production systemsmachine learningdecision-makingartificial neural networkbalance scorecardsPrincipal Component Analysis algorithmsuncertainty of demand
Learning and adaptive systems in artificial intelligence (68T05) Management decision making, including multiple objectives (90B50) Production models (90B30) Neural networks for/in biological studies, artificial life and related topics (92B20)
Cites Work
- Selecting optimum maintenance strategy by fuzzy interactive linear assignment method
- Operational flexibility quantification in a make-to-order assembly system
- The strategic decision-making as a complex adaptive system: a conceptual scientific model
- Systemic criterion of sustainability in agile manufacturing
- Learning representations by back-propagating errors
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