Smart Factory

Smart Factory

Smart Factory

Reducing lead time in toolmaking by 90%
Christian Ludwig, Hilmar Gensert, Thomas Farrenkopf, Thomas Panske
Smart Factory is the vision of a production environment in which manufacturing plants and logistics systems organize themselves as far as possible without human intervention. The article describes a project, at the start of which none of the participants created a relation to “Smart Factory” or “Industry 4.0”. Rather, the objective was to drastically reduce the current delivery time of 6-8 weeks. The result is a completely digitized business process from order creation, product development, design, manufacturing as well as processing for “batch size 1” with a reduction in lead time to less than 10 %.
Industrie 4.0 Management | Volume 37 | 2021 | Edition 4 | Pages 29-33 | DOI 10.30844/I40M_21-4_S29-33
Exchanging Data Between Industrial Companies − Smart Factories Use a Cloud-Based Common Data Environment as their Central Information Hub

Exchanging Data Between Industrial Companies − Smart Factories Use a Cloud-Based Common Data Environment as their Central Information Hub

Cloudbasiertes Common Data Environment als zentraler Informationshub in der Smart Factory
Andreas Dangl
Right now, there’s virtually no single issue impacting the mechanical and plant engineering sector as profoundly as that of the “smart factory.” In fact, according to an industry survey conducted in 2019 [1], as many as 68 percent of the respondents reported that they had already launched initial smart factory initiatives. According to the Capgemini study “Smart Factories @ Scale” [2], by the end of 2019, a third of the factories had already been transformed into intelligent factories. This article presents insight into how leveraging the advantages of a cloud-based solution can ensure that the flow of information within a network of smart factories can be managed effectively.
Industrie 4.0 Management | Volume 37 | 2021 | Edition 4 | Pages 63-66
Working in a Volatile Environment

Working in a Volatile Environment

Skills and working models in the age of the digital transformation
Dominik Augenstein, Eugen Wiebe
Through disruptive changes and an increasing globalization, companies have to rethink their traditional working models. Thereby, the digital transformation seems to provide a solid answer to this challenge and enables a rapid adaption to the new circumstances. Humans are of central importance to respond to these changing demands. A challenge hereby is, that humans have to be embedded in such a flexible working environment considering, that the competence profile is changing rapidly. In order to solve these challenges, a competence profile is provided. Furthermore, it is shown that a working model for the digital transformation enables a company to respond quickly and flexibly to new environmental conditions.
Industrie 4.0 Management | Volume 36 | 2020 | Edition 6 | Pages 51-54
Self-loading Workstation Systems in Logistics

Self-loading Workstation Systems in Logistics

Networked Workstation System for Proactive Bottleneck Avoidance within Demanding Intralogistics Processes
Patrick Adler, Holger Dander ORCID Icon, Gerd Witt
Modern logistic processes are still characterized by manual labour. In general, mainly unqualified or low-skilled employees are used to carry out value-added services. Individual workloads, employee skills and technical workplace equipment are linked in a developed system. By simulating the effect of changes in workplace equipment, optimizations can be identified. The self-developed algorithm can also be used in other industries.
Industrie 4.0 Management | Volume 36 | 2020 | Edition 5 | Pages 29-32
Real-Time-Capable Information Flow in Shipbuilding Pipe Production

Real-Time-Capable Information Flow in Shipbuilding Pipe Production

Ein System zur datenbasierten Abbildung des Produktionsprozesses
Konrad Jagusch, Jan Sender, Wilko Flügge
Inadequate communication with media discontinuities makes it difficult to implement simulataneous engineering. Missing process data prevent data-based control measures and the layout of design adaptations to unfinished components. Therefore, the subject of this article is the description of a system for real-time data acquisition and the digitalization of the information flow in shipbuilding.
Industrie 4.0 Management | Volume 35 | 2019 | Edition 5 | Pages 9-12
Digitalization Increases the Competitiveness of the Wind Industry

Digitalization Increases the Competitiveness of the Wind Industry

Horst Wildemann
The phase-out of nuclear energy decided by the politicians and the goal of significantly aligning the energy mix with renewable energies will give the industry great growth potential. Digitalization and the resulting technologies, such as sensors, robotics and assistance systems, artificial intelligence, virtual reality and augmented reality, are helping companies realise their potential. The study “Industrialization of the Wind Industry” by the Technical University of Munich has shown that digitalization will have a positive effect on the “Levelized Cost of Energy” (LCOE).
Industrie 4.0 Management | Volume 35 | 2019 | Edition 4 | Pages 63-65
Virtual Production

Virtual Production

A study on the use of digitalization in the manufacturing industry with focus on AR
Axel Wellendorf, Felix Kottenbrock, Sebastian Trampnau
In times of increasing globalization, international capital and consumer markets get more and more dynamic. To remain competitive, companies have to respond to new requirements and move away from traditional manufacturing concepts. Digitalization offers different technologies and methods to provide a remedy. The following article describes the status quo, as well as future possibilities of Virtual Production with a particular focus on Augmented Reality in the production environment. It gives a comprehensive overview of the current market situation and facilitates strategic investment decisions.
Industrie 4.0 Management | Volume 35 | 2019 | Edition 4 | Pages 25-29
Human-Robot-Collaboration in the Final Aircraft Assembly

Human-Robot-Collaboration in the Final Aircraft Assembly

Ein intelligentes Assistenzsystem für das mechanische Fügen in der manuellen Montage
Frederik Schmatz, Jens Meißner, Jan Sender, Wilko Flügge, Eugen Gorr
A newly developed hand guided collaborative robot system will be used for manual mechanical joining process in the final assembly of aircrafts. The tool can be moved quickly and precisely to reach all joining positions avoiding physical effort for the operator. Special focus was given on the integrated handling of the entire system. The interlinked sensory of all subsystems ensures a smart control of the system. A mobile device was implemented to increase the usability and to foster the employees’ acceptance of the solution. It enables significantly improved process documentation, reproducibility and transparency.
Industrie 4.0 Management | Volume 35 | 2019 | Edition 1 | Pages 19-22 | DOI 10.30844/I40M_19-1_S19-22
MES Integration from a User Perspective

MES Integration from a User Perspective

Eine praxisbezogene Analyse in produzierenden Unternehmen am Beispiel eines Laser-Assistenzsystems
Ralf Müller-Polyzou, Lucas Meyer, Anthimos Georgiadis
The interworking of Manufacturing Execution Systems (MES) and operating resources is a prerequisite for the flexible and versatile production in Smart Factories of Industry 4.0. This article describes a qualitative and quantitative analysis of an MES integration based on an industrial laser assistance system for worker guidance. It analyzes the situation and requirements from a user perspective with special consideration of implemented systems, interfaces, protocols as well as Plug & Produce. The study uses qualitative analysis results from opinion makers and quantitative analysis results from leading manufacturing companies among others from the automotive and aerospace industry. Thus, the study supports decision making for MES investments in Industry 4.0.
Industrie 4.0 Management | Volume 35 | 2019 | Edition 1 | Pages 31-34 | DOI 10.30844/I40M_19-1_S31-34
Digital Lean – The Crossroads-Model for Controlling Material Flows in Production and Logistics Systems

Digital Lean - The Crossroads-Model for Controlling Material Flows in Production and Logistics Systems

Erklärung und Auswahl von Steuerungsansätzen für Produktions- und Logistiksysteme in Zeiten der Digitalisierung
Carsten Feldmann, Ralf Ziegenbein
Methods for monitoring and controlling material flows in a production or logistics system should support objectives like costs and throughput-time. Lean focuses on decentral, demand-driven steering of activities. Advanced manufacturing concepts for Smart Factories rely on innovative digital technologies. Which method is the best fit for steering the material flow? The Crossroads-Model explains different approaches and supports the selection of a suitable method for corporate practice.
Industrie 4.0 Management | Volume 34 | 2018 | Edition 5 | Pages 33-38 | DOI 10.30844/I40M18-5_33-38
1 2 3 4