Knowledge based automated production systems and services-enabled by data analytics

2017 ◽  
Vol 65 (6) ◽  
Author(s):  
Stefan Windmann ◽  
Oliver Niggemann

AbstractIn this paper, a self-configurable fault detection system for automated production systems with Industrial Ethernet is proposed. The scope of the proposed fault detection system are process variables, i.e., the observed actuator and sensor signals. Self-configuration of the fault detection system is enabled by recording and analyzing the link connection of the Ethernet network during system start. In a subsequent training phase, a knowledge base is automatically built from the observed process variables. Knowledge-based fault detection is accomplished once the knowledge base is established. Fault detection has been evaluated for a glue production process. In this application case, the knowledge-based fault detection method yielded a balanced accuracy of 99.81%, while a model-based method, which has been used as reference, produced a balanced accuracy of 93.11%.


Climate ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 60
Author(s):  
Patricia Ruiz-García ◽  
Cecilia Conde-Álvarez ◽  
Jesús David Gómez-Díaz ◽  
Alejandro Ismael Monterroso-Rivas

Local knowledge can be a strategy for coping with extreme events and adapting to climate change. In Mexico, extreme events and climate change projections suggest the urgency of promoting local adaptation policies and strategies. This paper provides an assessment of adaptation actions based on the local knowledge of coffee farmers in southern Mexico. The strategies include collective and individual adaptation actions that farmers have established. To determine their viability and impacts, carbon stocks and fluxes in the system’s aboveground biomass were projected, along with water balance variables. Stored carbon contents are projected to increase by more than 90%, while maintaining agroforestry systems will also help serve to protect against extreme hydrological events. Finally, the integration of local knowledge into national climate change adaptation plans is discussed and suggested with a local focus. We conclude that local knowledge can be successful in conserving agroecological coffee production systems.


2019 ◽  
Vol 23 (2) ◽  
pp. 44-47
Author(s):  
Konstantin Novikov ◽  
Pavel Vranek ◽  
Jana Kleinova ◽  
Michal Šimon

2018 ◽  
Vol 66 (4) ◽  
pp. 344-355 ◽  
Author(s):  
Iris Weiß ◽  
Birgit Vogel-Heuser

AbstractData mining in automated production systems provide high potential to increase the Overall Equipment Effectiveness. Nevertheless, data of such machines/plants include specific characteristics regarding the variance and distribution of the dataset. For modelling product quality prediction, these characteristics have to be analysed to interpret the results correctly. Therefore, an approach for the analysis of variance and distribution of datasets is proposed. The evaluation of this approach validates the developed guidelines, which identify the reasons for inconsistent prediction results based on two different datasets of the same production system.


2015 ◽  
Vol 105 (09) ◽  
pp. 651-656
Author(s):  
A. König ◽  
T. Benkner ◽  
J.-P. Schulz

Der Fachartikel beschreibt ein neues Konzept zur interdisziplinären, gewerkeübergreifenden Zusammenarbeit von Unternehmen im Planungsprozess von automatisierten Produktionssystemen. Der Ansatz „conexing“ definiert ein planungsübergreifendes Dateiformat auf Basis des AutomationML-Standards für Anlagenkomponenten sowie eine Austauschschnittstelle mittels eines Webportals. Die hier vorgestellte Methodik erlaubt den Austausch von Komponenten inklusive ihres logischen Verhaltens für die virtuelle Inbetriebnahme zwischen unterschiedlichen Engineering-Werkzeugen.   This article describes a new approach to interdisciplinary – cross-trade business cooperation in the planning process of automated production systems. The conexing approach defines so called SmartComponent, as a file format for system components based on the AutomationML standards for the exchange of plant engineering information. These SmartComponents include detailed system component information as well as their logical behavior. The presented approach additionally allows an exchange of SmartComponents between different engineering tools for virtual commissioning via a web portal.


2018 ◽  
Vol 66 (10) ◽  
pp. 784-794 ◽  
Author(s):  
Jakob Mund ◽  
Safa Bougouffa ◽  
Iman Badr ◽  
Birgit Vogel-Heuser

Abstract Continuous integration (CI) is widely used in software engineering. The observed benefits include reduced efforts for system integration, which is particularly appealing for engineering automated production systems (aPS) due to the different disciplines involved. Yet, while many individual quality assurance means for aPS have been proposed, their adequacy for and systematic use in CI remains unclear. In this article, the authors provide two key contributions: First, a quality model for a model-based engineering approach specifically developed for aPS. Based thereon, a discussion of the suitable verification techniques for aPS and their systematic integration in a CI process are given. As a result, the paper provide a blueprint to be further studied in practice, and a research agenda for quality assurance of aPS.


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