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The Compressed Enterprise-Control System Integration and the Era of Industry 4.0

The Compressed Enterprise-Control System Integration and the Era of Industry 4.0

How the digital control twin is changing operational applications and the integration of IT systems in a company
Wilmjakob Herlyn ORCID Icon
The Enterprise-Control System Integration of the operational applications is described in IEC-62264 and also referred to as the automation pyramid. This integration model is built on the MRP-II model developed in the 1980s. This model was groundbreaking for its time and still forms the basis of operational IT systems today. According to this concept, operational applications are run through hierarchically-sequentially (waterfall principle), which results in disadvantages such as: many interfaces, time delays, data loss, inconsistencies, etc. This sequential model neither meets the current requirements nor the informational and technical possibilities of Industry 4.0. It can be replaced by the concept of the digital control twin, which has corresponding effects on the automation pyramid.
Industrie 4.0 Management | Volume 39 | 2023 | Edition 5 | Pages 42-47
Automated Detection of Fragile Production Behavior

Automated Detection of Fragile Production Behavior

Simple early detection of deterministic-chaotic behavior in highly available production systems
Martin Manns ORCID Icon, Denny Höhnen
Routing flexibility enables a robust, resilient design of production. However, in highly available, decentralized controlled production systems with cyclic material flow, it can reduce efficiency due to undesired deterministic-chaotic behavior. An automated method for measuring such behavior is presented. It is tested with a double conveyor belt laboratory system. An embedded system simplifies data acquisition. Results indicate that the method is usable for manual and automatic production systems. It has the potential to recognize modeling deficiencies in Industry 4.0 control with IEC 61499. (Only in German)
Industrie 4.0 Management | Volume 39 | 2023 | Edition 5 | Pages 17-21
Modeling of Robust Processes

Modeling of Robust Processes

Requirements for process modeling
Annika Lange ORCID Icon, Thomas Knothe ORCID Icon
In order to withstand disruptions manufacturing companies need to improve their robustness. In the past only infrastructures and resources were considered in the context of robustness, neglecting the interconnectedness of processes. However, a consideration of processes in the context of robustness is highly relevant. Process modeling is used for the design and analysis of processes. This paper describes the requirements for modeling methodology and evaluates existing approaches. (Only in German)
Industrie 4.0 Management | Volume 39 | 2023 | Edition 5 | Pages 62-65
Modeling Influences on the Wire Arc Additive Manufacturing Process

Modeling Influences on the Wire Arc Additive Manufacturing Process

Tim Sebastian Fischer, Lennart Grüger ORCID Icon, Ralf Woll
Wire Arc Additive Manufacturing (WAAM) is an additive manufacturing process which produces metallic components on the basis of arc welding. ISO/ASTM 52900 describes additive manufacturing as a process that creates components layer by layer from 3D model data. The basic equipment required includes a welding device, introducing the energy necessary for melting the metal wire, and a guiding machine, which traces the specified geometry of the component. Applications for WAAM include rapid prototyping and tooling, direct manufacturing and additive repair. The greatest advantages the process offers are low-cost system technology and a high deposition rate. The disadvantages of the process are the lack of process stability and exact repeatability. This article is intended to provide a clear overview of the WAAM manufacturing process, and to address its complex interactions.
Industrie 4.0 Management | Volume 39 | 2023 | Edition 5 | | DOI 10.30844/I4SE.23.1.80
Optimization of Line Feeding Strategy for the Assembly Line

Optimization of Line Feeding Strategy for the Assembly Line

A holistic approach for improving the intralogistics in production industry
Christina Braun, Lea Isfort
The logistics industry offers numerous opportunities for data-driven solutions, such as improving the part feeding problem in assembly line industries. A data-based approach for will lead to an improvement of cost-effectiveness through optimized processes, resource utilization, and consistent supply to the assembly line. The generated approach is a mixed integer programming model which considers limited storage space, uses constraints, and various cost factors related to transport, replenishment, and picking.
Industrie 4.0 Management | Volume 39 | 2023 | Edition 5 | Pages 58-61
Potentials and Application of the Industrial Metaverse

Potentials and Application of the Industrial Metaverse

Convergence from simulation to reality
Oliver Petrovic, Yannick Dassen, Christian Brecher
This paper deals with the concept of the Industrial Metaverse and its potential impact on the manufacturing industry. First, the possibilities of the Industrial Metaverse are explained in general and then possible resulting functionalities for production technology along the life cycle are presented. For the two topics "Synthetic Data Generation" and "Virtual Qualification" the implications of the Industrial Metaverse are considered more concretely.
Industrie 4.0 Management | Volume 39 | 2023 | Edition 5 | Pages 27-32 | DOI 10.30844/IM_23-5_27-32
Forecasting the Business Crisis in the Auto Industry

Forecasting the Business Crisis in the Auto Industry

A comparative analysis of models
Joseph W. Dörmann, Shobith Ramakrishnaiah
This paper examines various forecasting models used to predict business crises in the automotive and electronic manufacturing industries, with a focus on German companies. By comparing the performance of these models, we aim to identify the best approach for each industry. We also discuss real-world business case scenarios to demonstrate the practical implications of our findings, including the role of risk management in supply chain and procurement departments. Our results show that the most effective model for forecasting crises in the automotive industry is the VAR model, while the EWS model is best suited for the electronic manufacturing industry. Furthermore, we identify key risk factors that supply chain and procurement departments must consider enhancing their resilience in the face of crises.
Industrie 4.0 Management | Volume 39 | 2023 | Edition 5 | Pages 6
Process Modeling: Practice-Oriented and Methodologically Founded

Process Modeling: Practice-Oriented and Methodologically Founded

Jörg Becker ORCID Icon, Florian Schmolke ORCID Icon
Changes in the economic environment always generate new challenges for companies. In order to consider these challenges, it is necessary to have a comprehensive knowledge of the processes and a high level of transparency of the company's process organization. The process, represented in a documentation based on models, takes on a significant role as a reflection of the activities.
Industrie 4.0 Management | Volume 39 | 2023 | Edition 5 | Pages 48-52 | DOI 10.30844/IM_23-5_48-52
Vom Energiedatenmanagement zum Digitalen Zwilling

Vom Energiedatenmanagement zum Digitalen Zwilling

Vereinfachte Modellierung eines Digitalen Zwillings mithilfe von Energiedaten
Alexander Blinn, Henrik te Heesen, Joachim Brinkmann, Julius Herzog
Bedingt durch globale Entwicklungen hinsichtlich der Preise und Versorgungssicherheit im Energiesektor stehen besonders energieintensive Unternehmen vor großen Herausforderungen. Zusätzlich fordern Kunden mehr Informationen über Energiekennzahlen und CO₂-Emissionen sowie ressourcenschonendere Prozesse. Mit einer energiedatenbasierten Simulationsmethode werden die Ressourceninformationen direkt aus dem Energiedatenmanagementsystem (EDMS) extrahiert und weiterverarbeitet. Hierbei werden sowohl aktuelle als auch stetig aktualisierte historische Daten verwendet, die automatisiert abgeglichen werden. Die digitale Abbildung der vorhandenen Prozesse ist lediglich auf Seiten der Energiedaten notwendig, ohne die technischen Prozesse in ihrer Gänze analysieren zu müssen. Mit dem so erstellten energetischen digitalen Schatten lassen sich Energiebedarfe für bevorstehende Produktionen und Produkte simulieren und können durch automatisierte Vorschläge in der Produktionsplanung positiv ...
Industrie 4.0 Management | Volume 39 | 2023 | Edition 5 | Pages 33-36 | DOI 10.30844/IM_23-5_33-36
Tool for Data-Based Continuous Improvement in Manufacturing Companies

Tool for Data-Based Continuous Improvement in Manufacturing Companies

Konstantin Neumann, Nicole Oertwig ORCID Icon
The introduction of Lean Management System and their continuous improvement regularly poses challenges for companies. In the face of advancing digitalisation, new opportunities for analysis are opening up that also support the continuous improvement process. The article shows how process orientation, digitalisation and operational activities can be systematically applied for the development and integration of a data-based continuous improvement process in manufacturing companies. (Only in German)
Industrie 4.0 Management | Volume 39 | 2023 | Edition 5 | Pages 13-16
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