عنوان

IMPROVE -- innovative modelling approaches for production systems to raise validatable efficiency :

شابک

3662578050

شابک

9783662578056

شابک اشتباه

3662578042

شابک اشتباه

9783662578049

عنوان اصلي

IMPROVE -- innovative modelling approaches for production systems to raise validatable efficiency :

نام عام مواد

[Book]

ساير اطلاعات عنواني

intelligent methods for the factory of the future /

نام نخستين پديدآور

Oliver Niggemann, Peter Schüller, editors.

محل نشرو پخش و غیره

Berlin, Germany :

نام ناشر، پخش کننده و غيره

Springer Vieweg,

تاریخ نشرو بخش و غیره

2018.

نام خاص و کميت اثر

1 online resource (vii, 129 pages) :

ساير جزييات

illustrations (some color)

عنوان فروست

Technologien für die intelligente Automation, Technologies for Intelligent Automation,

مشخصه جلد

Band 8

شاپا ي ISSN فروست

2522-8579 ;

متن يادداشت

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.

بدون عنوان

0

متن يادداشت

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. The Editors Prof. Dr. Oliver Niggemann is Professor for Artificial Intelligence in Automation. His research interests are in the fields of machine learning and data analysis for Cyber-Physical Systems and in the fields of planning and diagnosis of distributed systems. He is a board member of the research institute inIT and deputy director at the Fraunhofer Application Center Industrial Automation INA located in Lemgo. Dr. Peter Schüller is postdoctoral researcher at Technische Universität Wien. His research interests are hybrid reasoning systems that combine Knowledge Representation and Machine Learning and applications in the fields of Cyber-Physical systems and Natural Language Processing.

عنوان

IMPROVE -- innovative modelling approaches for production systems to raise validatable efficiency.

شماره استاندارد بين المللي کتاب و موسيقي

9783662578049

موضوع مستند نشده

Industrial efficiency-- Computer simulation.

موضوع مستند نشده

Production management.

موضوع مستند نشده

Production management.

شماره

ويراست

شماره رده

مستند نام اشخاص تاييد نشده

Niggemann, Oliver

مستند نام اشخاص تاييد نشده

Schüller, Peter

تاريخ عمليات

20200823192340.0

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y