An approach to design and develop reconfigurable control software for highly automated production systems

2014 ◽  
Vol 28 (3) ◽  
pp. 321-336 ◽  
Author(s):  
A. Valente ◽  
M. Mazzolini ◽  
E. Carpanzano
Keyword(s):  
Production Systems ◽  
Control Software ◽  
Reconfigurable Control ◽  
Automated Production

scholarly journals Success Factors for the Design of Field-level Control Code in Machine and Plant Manufacturing - an Industrial Survey -

2021 ◽  
Author(s):  
Birgit Vogel-Heuser ◽  
Juliane Fischer ◽  
Eva-Maria Neumann ◽  
Matthias Kreiner
Keyword(s):  
Software Engineering ◽  
Success Factors ◽  
Production Systems ◽  
Development Effort ◽  
Manufacturing Companies ◽  
Level Control ◽  
Control Software ◽  
Automated Production ◽  
Field Level ◽  
Control Code

Abstract The amount of software in automated production systems, including its development effort, is continuously increasing to currently up to 35-50% of the development personnel. Consequently, success factors for achieving modularity and complexity management of control software are of high economic interest. Scientific solutions are manifold but often not implemented in industry. This paper introduces the study QoaPS SWE (Quality of automated Production Systems’ Software Engineering) providing insights into 61 machine and plant manufacturing companies to give quantitative and qualitative results to five essential research questions on success factors in the design of field-level control code. Compared to preceding surveys, QoaPS SWE achieves statistically significant results for software maturity (MMOD+), complexity, and model-based software engineering and provides detailed insights into causes and consequences for single criteria, thus clearly identifying obstacles to be addressed in future research and with industrial countermeasures. Especially staff qualification and organizational issues are identified as obstacles to applying the object-oriented programming paradigm for control software in machine and plant manufacturing. Validity is ensured by analyzing the statistical significance of the results in addition to comparisons with earlier surveys and interviews as well as the comparison with already existing and accepted maturity levels. The provided qualitative and quantitative results will allow the benchmarking of companies’ maturity and the derivation of concrete recommendations for companies depending on their MMOD+ value and the evaluated characteristics.

scholarly journals MICOSE4aPS: Industrially Applicable Maturity Metric to Improve Systematic Reuse of Control Software

2022 ◽  
Vol 31 (1) ◽  
pp. 1-24
Author(s):  
Birgit Vogel-Heuser ◽  
Eva-Maria Neumann ◽  
Juliane Fischer
Keyword(s):  
Food Packaging ◽  
Manufacturing Industry ◽  
Production Systems ◽  
System Quality ◽  
Control Software ◽  
Mechatronic Systems ◽  
Automated Production ◽  
Quality Of Control ◽  
Software Modules ◽  
Systematic Reuse

automated Production Systems (aPS) are highly complex, mechatronic systems that usually have to operate reliably for many decades. Standardization and reuse of control software modules is a core prerequisite to achieve the required system quality in increasingly shorter development cycles. However, industrial case studies in aPS show that many aPS companies still struggle with strategically reusing software. This paper proposes a metric-based approach to objectively measure the m aturity of i ndustrial IEC 61131-based co ntrol s oftwar e in aPS (MICOSE4aPS) to identify potential weaknesses and quality issues hampering systematic reuse. Module developers in the machine and plant manufacturing industry can directly benefit as the metric calculation is integrated into the software engineering workflow. An in-depth industrial evaluation in a top-ranked machine manufacturing company in food packaging and an expert evaluation with different companies confirmed the benefit of efficiently managing the quality of control software.

scholarly journals Key maturity indicators for module libraries for PLC-based control software in the domain of automated Production Systems

2018 ◽  
Vol 51 (11) ◽  
pp. 1610-1617 ◽  
Author(s):  
Birgit Vogel-Heuser ◽  
Juliane Fischer ◽  
Eva-Maria Neumann ◽  
Sebastian Diehm
Keyword(s):  
Production Systems ◽  
Control Software ◽  
Automated Production

Change analysis on evolving PLC software in automated production systems

2018 ◽  
Vol 66 (10) ◽  
pp. 806-818 ◽  
Author(s):  
Alexander Schlie ◽  
Safa Bougouffa ◽  
Juliane Fischer ◽  
Ina Schaefer ◽  
Birgit Vogel-Heuser
Keyword(s):  
Static Analysis ◽  
Software Evolution ◽  
Production Systems ◽  
Feasibility Studies ◽  
System Quality ◽  
Control Software ◽  
Change Analysis ◽  
Automated Production ◽  
Long Run ◽  
Manual Examination

Abstract Control software for automated Production Systems (aPSs) becomes increasingly complex. Respective systems undergo constant evolution. Yet, proper documentation may not always be present, entailing maintenance issues in the long run. While manual examination of software for aPSs is an error-prone task, static analysis can improve system quality. However, it has not been applied to describe software evolution by means of changed systems artifacts. The authors address this issue and perform change analyses on IEC61131-3 projects, identifying introduced and removed systems artifacts as well as existing ones affected. By that, the authors aim to support sustainable evolution. Two feasibility studies, implemented independently, but for the same evolution scenarios for an automation plant, are used for evaluation. The technique is shown to be efficient and highly precise.

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.

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