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VDI Wissensforum GmbH (ed.)

Automation 2020

Series: VDI-Berichte

Volume 2375 2020

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M. W. Hoffmann, R. Drath, C. Ganz Industrielle Anforderungen an Künstliche Intelligenz-Lösungen S. 617-628

„… decision support system for condition-based maintenance." The International Journal of Advanced …” „… Production 142: 626- 641, 2017. 16. Lee, J, et al. "Industrial Artificial Intelligence for industry 4.0 …” „… -based manufacturing systems." Manufacturing letters 18: 20-23, 2018. 17. Zhang, , et al. "A reference …”

S. Baer, F. Baer, D. Turner, S. Pol, T. Meisen Integration of a Reactive Scheduling Solution using Reinforcement Learning in a Manufacturing System S. 645-658

„… . The production control is carried out by the PLC, which is informed about the agents’ decisions via …” „… Systems (FMS) and require a suitable production control. In the following, we describe the challenges of …” „… production is in focus, have one common goal: productivity. Most of these systems have a sequential …”

M. Müller, B. Ashtari Talkheshtani, N. Jazdi, M. Weyrich, R. Rosen, J. C. Wehrstedt Informationsmodelle mit intelligenter Auswertung für den Digitalen Zwilling S. 659-674

„… understanding and AI algorithms is the basis of the presented concept. By intelligently evaluating the …” „… proposed which automatically finds a solution based on cooperative information from the value network. The …” „… evaluation of the concept using a scenario from logistics and from production delivers promising results …”

K. Land, B. Vogel-Heuser, S. Ziegltrum, U. Jumar, M. Reider, K. Meinecke, B. Wissler Anforderungsbasiertes Testen mechatronischer Automatisierungsprodukte – Von Testfallgenerierung und -priorisierung zur semiautomatischen Ausführung S. 429-442

„… Energie (BMWi) über die Arbeitsgemeinschaft industrieller Forschungsvereinigungen (AiF) e. V. aufgrund …” „… , „Evolution of software in automated production systems: Challenges and research directions,“ JSS, Nr. vol …” „… , 2011. [5] A. Hartman und K. Nagin, „The AGEDIS Tools for Model Based Testing,“ Lecture Notes in …”

C. Huang, S. Seidel, F. Alberto Velarde Gonzales, D. Mayer Kostenoptimale Steuerung eines multivalenten Gebäudeenergiesystems mittels modellprädiktivem Ansatz und Reinforcement Learning S. 43-58

„… existing alternative options of energy production and saving a mixed-integer optimization problem arises …” „… predictive control system. In comparison, a reinforcement learning based approach is developed and analyzed …” „… .): Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. Berlin …”

doi.org/10.51202/9783181023754

VDI Wissensforum GmbH - Reifen – Fahrwerk – Fahrbahn

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VDI Wissensforum GmbH (ed.)

Reifen – Fahrwerk – Fahrbahn

Series: VDI-Berichte

Volume 2356 2019

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K. Singh, F. Petry, P. Alipour, D. Khadraoui Application of Machine Learning & Deep Learning Techniques in the Context of Use Cases Relevant for the Tire Industry S. 241-268

„… artificial intelligence (AI) based learning models. State-of-the-art machine learning (ML) and deep learning …” „… and DL based learning models is growing. This article provides an overview of the recent advances and …” „… (combinations of other models). DL generally refers to a specific class of models and algorithms based on deep …”

doi.org/10.51202/9783181023563

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wt Werkstattstechnik online

Browse Volumes: wt Werkstattstechnik online

wt Volume 110 (2020) Issue 03 ISSN Online: 1436-4980

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Benedikt Schmucker, Maximilian Busch, F. Michael Zäh Edge- und cloudbasierte Prozessüberwachung/Edge and Cloud-based Process Monitoring and Control: System Identification and Control of Machine Tools under consideration of Data Protection S. 113-118

„… und verschlüsselt werden. Edge and Cloud-based Process Monitoring and Control: System Identification …” „… parameters during machining operation. Cloud-based approaches facilitate the evaluation of large amounts of …” „… data and the aggregation of information from various machine tools and production sites. However, in …”

Christian Bayer, Rami Makhlouf, Joachim Metternich /Digitale Assistenzsysteme in der ProduktionDigital assistance systems in the production area – Specifying the relevant functions S. 103-107

„… Bauer, H. et al.: Smartening up with Artificial Intelligence (AI) – What’s in it for Germany and its …” „… intelligence/Smartening-upwith-artificial-intelligence.ashx. Zugriff am 13.01.2020 Bogner, E. et al.: Study Based Analysis on the Current Digitalization …” „… . International Journey of Production Research 54 (2015) 8, pp. 2260–2274 Arnold, P. et al.: Handbuch E-Learning …”

doi.org/10.37544/1436-4980-2020-03

Juan José Wilhelm Victoria Villeda - Reaction Network Generation and Evaluation for the Design of Biofuel Value Chains

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Juan José Wilhelm Victoria Villeda

Reaction Network Generation and Evaluation for the Design of Biofuel Value Chains

Series: Verfahrenstechnik

Volume 950 2017

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Reaction network generation: Introduction to the basic algorithm S. 11-54

„… network generators that include reaction kinetics further offer the opportunity to compare the production …” „… production rates of all substances fall below this threshold. Reaction network generation can be applied in 2 …” „… set of generic reaction rules, and (iii) formal methods based on graph theory, performing reactions …”

Network evaluation strategy S. 77-94

„… 5 Network evaluation strategy It was mentioned in Section 1.2 that an optimization-based evaluation …” „… optimization-based evaluation technique and subsequently the novel approach that also assesses the network topology …” „… and the integration of waste streams. 77 5 Network evaluation strategy 5.1 Optimization-based network …”

Appendices S. 132-169

„… number of sets, A1, ..., An is defined by A1 × ...× An := {(a1, an)|ai ∈ Ai for {i = 1, ..., n}}. (A.8 …” „… + a2 ·D2 + a3 ·D3 + .... (D.1) Di is a subset of descriptors and ai are weights derived by an adequate …” „… production process. They are the most widely applied measures of the efficiency of a process or product …”

doi.org/10.51202/9783186950031

Christian Brecher, Jörg Krüger, Eckart Uhlmann, Alexander Verl, Oliver Riedel, Armin Lechler - KI in der Produktion – Innovative Anwendungsfälle

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Christian Brecher, Jörg Krüger, Eckart Uhlmann, Alexander Verl, Oliver Riedel, Armin Lechler

KI in der Produktion – Innovative Anwendungsfälle

Series: Fertigungstechnik

Volume 707 2022

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L. Gründel, S. Storms, Ch. Brecher Strategien zur Integration datengetriebener Ansätze für die Dynamikmodellierung von Industrierobotern S. 27-36

„… .: Prototype for Enhanced Product Data Acquisition Based on Inherent Features in Logistics, IEEE 21st …” „… ] Schlüter, M.; Niebuhr, C.; Lehr, J.; Krüger, J.: Vision-based Identification Service for Remanufacturing …” „… .; Bischoff, N.: Deep learning for part identification based on inherent features, CIRP Annals, Volume 68 …”

doi.org/10.51202/9783186707024

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