00000cmm a22000004i 4500 UP-99796217613392260 Buklod 20200615214933.0 m |o d | cr cu|mmmmuaua 180820s2018 xx o u | eng d 9783662578056 (online ISBN) (iLib)UPD-00516571442 WaSeSS DENGII rda eng TA 169.7 I47 2018eb IMPROVE - innovative modelling approaches for production systems to raise validatable efficiency intelligent methods for the factory of the future Oliver Niggemann, Peter Schuller, editors. Berlin, Heidelberg Springer Berlin Heidelberg [2018] 1 online resource. text rdacontent computer rdamedia online resource rdacarrier Technologien für die intelligente Automation, Technologies for Intelligent Automation Concept and Implementation of a Software Architecture for Unifying Data Transfer in Automated Production Systems -- Social Science Contributions to Engineering Projects: Looking Beyond Explicit Knowledge Through the Lenses of Social Theory -- Enable learning of Hybrid Timed Automata in Absence of Discrete Events through Self-Organizing Maps -- Anomaly Detection and Localization for Cyber-Physical Production Systems with Self-Organizing Maps -- A Sampling-Based Method for Robust and Efficient Fault Detection in Industrial Automation Processes -- Validation of similarity measures for industrial alarm flood analysis -- Concept for Alarm Flood Reduction with Bayesian Networks by Identifying the Root Cause. IP-based subscription, on campus and remote access. Access via Electronic Resources of the UPD Engineering Library and University Library websites. System safety. Data transmission systems. Electronic books. Niggemann, Oliver editor. Schüller, Peter editor. SpringerLink (Online service). Available for University of the Philippines System via SpringerLink. Click here to access https://doi.org/10.1007/978-3-662-57805-6 Also available remotely for University of the Philippines System via SpringerLink. Click here to access thru EZproxy https://link.springer.com.ezproxy.engglib.upd.edu.ph/book/10.1007%2F978-3-662-57805-6 (viewed 15 June 2020) FO UPD DENG-II Electronic Resource