Production Control

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AI-Assisted Work Planning

AI-Assisted Work Planning

Extracting expert knowledge from historical data for streamlined efficiency and error mitigation
Jochen Deuse ORCID Icon, Mathias Keil, Nils Killich, Ralph Hensel-Unger
Global competitive pressure is forcing companies to use resources efficiently, especially in high-wage countries. This is further intensified by market and legislative pressure for sustainable products and processes. In the face of digital and ecological change, holistic approaches to optimizing manual work processes are essential. An AI-supported assistance system for work plan creation is intended to remedy this and thus enable more efficient process design.
Industry 4.0 Science | Volume 40 | 2024 | Edition 5 | Pages 74-80 | DOI 10.30844/I4SE.24.5.74
Integration of Artificial Intelligence into Factory Control

Integration of Artificial Intelligence into Factory Control

Norbert Gronau ORCID Icon
With the increasing availability of IoT devices and significantly greater incorporation of Internet-enabled technologies into manufacturing processes, the idea of improving factory control through the use of artificial intelligence (AI) is also coming to the fore. Using the example of high-variation series manufacturing, this article describes which steps need to be taken to improve factory control with AI.
Industry 4.0 Science | Volume 39 | 2023 | Edition 1 | Pages 95-99 | DOI 10.30844/I4SE.23.1.95
Trends and Challenges in Factory Software

Trends and Challenges in Factory Software

Norbert Gronau ORCID Icon
Any networked information system that is used in the context of manufacturing and logistics in a factory can be referred to as factory software. This article describes six trends that will significantly influence the way software is used in factories in the near future. The trends are described in ascending order in terms of significance of impact.
Industry 4.0 Science | Volume 39 | 2023 | Edition 1 | Pages 114-119 | DOI 10.30844/I4SE.23.1.114
Interactive Situation Picture for Crisis Management

Interactive Situation Picture for Crisis Management

A tool for process-oriented companies
Holger Kohl, Thomas Knothe ORCID Icon, Nicole Oertwig ORCID Icon, Patrick Gering, Julia-Anne Scholz
The SARS-CoV-2-crisis has brought many companies into existential distress. The sudden loss of suppliers and customers as well as short-term changes in regulations and relevant information sources pose challenges for companies. The linking and visualization of information from the corporate environment with internal capabilities remain an unsolved problem. This article shows how a situation picture can help companies to act in a goal-oriented manner.
Industrie 4.0 Management | Volume 37 | 2021 | Edition 1 | Pages 37-40
Tool Management of the Future – A Practical Approach to the Use of Digital Twins

Tool Management of the Future - A Practical Approach to the Use of Digital Twins

Praxisorientierte Ansätze zur Nutzung Digitaler Zwillinge
Anja Wilde, Stefan Wiemers, Jan Theissen
A fast flow of information throughout the entire supply chain is unavoidable for risk minimization and is not subject of a discussion in volatile times or crisis situations. The flow of information within the supply chain is characterized by various forms of transmission: EDI, cloud applications or other system interfaces are manifold in the areas of value-added networks for digital risk monitoring and process efficiency increase. If corporate processes are examined more closely, one area remains digitally underrepresented at the moment: The digital twin of a production tool. The handling of these production tools must now be taken to a new level.
Industrie 4.0 Management | Volume 36 | 2020 | Edition 6 | Pages 39-42
Levelling Production in the Process Industry with the Product Wheel

Levelling Production in the Process Industry with the Product Wheel

Vorgehensmodell, Erfolgsfaktoren und Case Study
Christopher Borgmann, Carsten Feldmann
Volatility in market demand leads to temporary over- and under-utilization of production assets and stocks. Levelling (heijunka) as a lean method aims at de-coupling production from market volatility. The production program is spread as even as possible over time. This achieves high asset utilization, short lead times, and low inventories. There are validated heijunka methods for the manufacturing industry, but for the process industry this remains a research gap. This article describes the Product Wheel and its validation at a building material manufacturer in order to close that gap.
Industrie 4.0 Management | Volume 36 | 2020 | Edition 5 | Pages 33-37
Quality-oriented Concept for a Control System for Delicatessen Food Production

Quality-oriented Concept for a Control System for Delicatessen Food Production

Integration zutatenspezifischer Qualitätsfunktionen in die Produktionssteuerung
Ann-Kathrin Rohde, Lennart Steinbacher, Michael Lütjen ORCID Icon, Michael Freitag ORCID Icon, Ramona Bosse, Gunnar Bosse, Frederike Reimold
The food production process and raw material specific parameters significantly influence the quality of the final product. Furthermore, for products with several ingredients, complex parameter effects occur. This complexity causes the desire for a production control that considers these effects and orientates on final product quality. This article describes the state of the art and derives requirements form a case study in a delicatessen food production system. In summary, this paper presents a concept for production control with special consideration of the final product quality for the production of delicatessen salads.
Industrie 4.0 Management | Volume 36 | 2020 | Edition 5 | Pages 53-57
5G-based Sensor Technology for Production Monitoring

5G-based Sensor Technology for Production Monitoring

Erprobung der 5G Mobilfunktechnologie in der Produktion auf dem 5G-Industry Campus Europe
Sarah Schmitt, Sven Jung, Niels König, Robert Schmitt ORCID Icon
The complexity of production and logistics systems generates the demand for industrial transformation: with sensor technology that enables efficient, flexible and reliable process monitoring and control using a 5G communication-infrastructure. In the “5GSensPRO” project, the Fraunhofer IPT in Aachen is developing a modularly expandable sensor cloud system for existing machines. Within a unique research environment, the world’s first 5G mobile radio network provides the opportunity to investigate and implement applications of 5G in production engineering.
Industrie 4.0 Management | Volume 36 | 2020 | Edition 1 | Pages 33-35
Challenges in Dealing with Production Disturbances

Challenges in Dealing with Production Disturbances

Results of a survey on the current state of disturbance management
Norbert Gronau ORCID Icon, Eva-Maria Kern, Hendrik Jonitz
Current State of Disturbance Management Disturbances in production systems can lead to massive costs for enterprises. It is a highly relevant ability for manufacturing companies to cope with the effects of occurring disturbances and their prevention. A survey on manufacturing companies draws a current picture of disturbance management and identifies challenges for coping with disturbances.
Industrie 4.0 Management | Volume 35 | 2019 | Edition 6 | Pages 33-36 | DOI 10.30844/I40M_19-6_S29-32
Digital Twins as Enabler for Changeable Production

Digital Twins as Enabler for Changeable Production

Realisierung einer durchgängig digitalisierten Industrie 4.0-Fertigung
Thomas Kuhn, Frank Schnicke
Today, manufacturing facilities are designed for mass-producing identical goods. Although they often have a certain flexibility, they are not fully changeable. Changes are associated with a high cost. Changeability allows producers to react more quickly to changing demand situations and to efficiently produce small quantities. The Digital Twin is a key concept for implementing the required changeability. In the reference project BaSys 4.0, funded by the German Federal Ministry of Education and Research (BMBF), we have developed a manufacturing concept that enables changeable production. Our open source middleware Eclipse BaSyx provides a reference implementation of the BaSys 4.0 concepts.
Industrie 4.0 Management | Volume 35 | 2019 | Edition 5 | Pages 13-16
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