Towards a common classification of changes for information and automated production systems as precondition for maintenance effort estimation

2016 ◽  
Author(s):  
Birgit Vogel-Heuser ◽  
Thomas Simon ◽  
Jens Folmer ◽  
Robert Heinrich ◽  
Kiana Rostami ◽  
...  
Keyword(s):  
Production Systems ◽  
Effort Estimation ◽  
Automated Production

scholarly journals Reliability analysis using experimental statistical methods and AIS: application in continuous flow tubes of gaseous medium

2021 ◽  
Vol 43 ◽  
pp. e55825
Author(s):  
Roberto Outa ◽  
Fábio Roberto Chavarette ◽  
Aparecido Carlos Gonçalves ◽  
Sidney Leal da Silva ◽  
Vishnu Narayan Mishra ◽  
...  
Keyword(s):  
Standardized Tests ◽  
Negative Selection ◽  
Production Systems ◽  
Wiener Filter ◽  
Pressure Vessels ◽  
Signal Recognition ◽  
Security Risk ◽  
Artificial Immune ◽  
Degree Of Severity

The motivation for the development of this work arose from the observation of maintenance in pressure vessels, which are categorized as highly hazardous security risk products. The costs of detecting failures in the production systems allow the result of the process to be safe and of good quality, using standardized tests internally within the company. The main objective of this work demonstrates the efficiency and robustness of the artificial immune system (AIS) of negative selection in the detection of failures by recognizing the vibration signals and categorizing them in the degree of probability and level of severity of failures. The intrinsic objectives are the application of the elimination of signal noise by the Wiener filter, and the processing of data-Wiener data using experimental statistics. The result of this work successfully demonstrates the precision between the experimental statistical and AIS techniques of negative selection; the robustness of the algorithm in precision and signal recognition; and the classification of the degree of severity and probability of failure

scholarly journals Reducing the Costs of Automated Production Systems

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

Assessment of variance & distribution in data for effective use of statistical methods for product quality prediction

2018 ◽  
Vol 66 (4) ◽  
pp. 344-355 ◽  
Author(s):  
Iris Weiß ◽  
Birgit Vogel-Heuser
Keyword(s):  
Data Mining ◽  
Product Quality ◽  
Statistical Methods ◽  
Analysis Of Variance ◽  
Production System ◽  
Production Systems ◽  
High Potential ◽  
Quality Prediction ◽  
Automated Production ◽  
Effective Use

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.

conexing/conexing: Simulation total – Internet as Infochannel

2015 ◽  
Vol 105 (09) ◽  
pp. 651-656
Author(s):  
A. König ◽  
T. Benkner ◽  
J.-P. Schulz
Keyword(s):  
Planning Process ◽  
Production Systems ◽  
System Component ◽  
File Format ◽  
Web Portal ◽  
New Approach ◽  
Automated Production ◽  
Virtual Commissioning ◽  
System Components ◽  
Engineering Information

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.

Towards verified continuous integration in the engineering of automated production systems

2018 ◽  
Vol 66 (10) ◽  
pp. 784-794 ◽  
Author(s):  
Jakob Mund ◽  
Safa Bougouffa ◽  
Iman Badr ◽  
Birgit Vogel-Heuser
Keyword(s):  
Quality Assurance ◽  
Software Engineering ◽  
System Integration ◽  
Research Agenda ◽  
Production Systems ◽  
Individual Quality ◽  
Quality Model ◽  
Automated Production ◽  
Continuous Integration ◽  
Verification Techniques

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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