Smart Factory

The Core Principles of the Digital Twin

The Core Principles of the Digital Twin

Transformingorder processes and the automation pyramid
Wilmjakob Herlyn ORCID Icon
The digital twin [DT] is considered a key technology of Industry 4.0. Its basic concept is now being successfully applied in practice, as demonstrated by the commissioning of Mercedes' Factory56 in 2022. New identification technologies, tracking systems and communication solutions faciliate new ways of controlling production and managing material flows, particularly at the shop floor level. With precise technical data permanently available not only for products, but also for material availability and order fulfillment status, production processes can be managed more dynamically and efficiently. This is precisely where the concept of the DT comes into play, enabling the immediate use and evaluation of this data.Its relevance continues to grow, especially in the context of make-to-order production, the rising variety of product configurations, and the globalization of production and supply networks. This article introduces the basic concept of the DT and illustrates how it connects to ...
Industry 4.0 Science | Volume 41 | 2025 | Edition 3 | Pages 92-101
Computer Use in Industrial Business Processes

Computer Use in Industrial Business Processes

A systematic literature review of the last 40 years
Norbert Gronau ORCID Icon
The most important value-adding industrial business processes are product creation and order processing. For 40 years now, Industry 4.0 Science and its predecessor titles have supported the development and implementation of the software used in these industrial business processes. In honor of the journal’s 40th anniversary, a systematic literature review is carried out to identify trends that played a role in the past but no longer do today. The research provides some surprising insights into the topics that have been important in the last 40 years – as well as those that will remain relevant in the future.
Industry 4.0 Science | Volume 41 | 2025 | Edition 1 | Pages 8-14 | DOI 10.30844/I4SE.25.1.8
I4S 1/2025: 40 Years of Digital Transformation in Manufacturing

I4S 1/2025: 40 Years of Digital Transformation in Manufacturing

Key research questions for tomorrow's production and logistics
Digital transformation has been a central focus of scientific discussions for years. Questions relating to data-driven decisions, artificial intelligence and resilient supply chains are at the heart of current research. The articles in this issue explain key trends and present scientific findings and practical solutions - from automation and the circular economy to cloud computing.
Networked Learning Factories as Trailblazers

Networked Learning Factories as Trailblazers

Digital pioneering work for modern education
Julian Buitmann, Robert Holling ORCID Icon, Steffen Greiser ORCID Icon
Learning factories promote digital transformation through an interdisciplinary approach between lean management, Industry 4.0, energy efficiency, training center or research farm. SME centers are characterized by the on-site integration of small and medium-sized companies. Such a regional strategy, combined with learning factories, promotes a goal-oriented dialog between science and practice where students can put their theoretical knowledge to the test.
Industry 4.0 Science | Volume 40 | Edition 4 | Pages 16-23
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
Comparing Industry 4.0 Maturity Models

Comparing Industry 4.0 Maturity Models

Jochen Schumacher, Norbert Gronau ORCID Icon
In recent years, numerous maturity models have been developed with the aim of providing a clear indication of the progress each company has made in terms of Industry 4.0 development. However, not all models include all aspects of Industry 4.0. The models are also not equally practical. This article offers an in-depth comparison and assessment of the comprehensiveness of the ten most important Industry 4.0 maturity models.
Industry 4.0 Science | Volume 39 | 2023 | Edition 1 | Pages 16-33 | DOI 10.30844/I4SE.23.1.16
Decentralized Tact Time Control in Assembly

Decentralized Tact Time Control in Assembly

Simplifying robust control of assembly lines via the I4.0 box
Sander Lass, Tim Körppen
In theory, decentralized control approaches in the manufacturing context offer several advantages over monolithic centralized systems where all functions are combined into one or into several authorities. However, practical implementation requires adaptation of the general concept of decentralization to fit individual and specific use cases, especially with regard to their sensible scope. One such use case is the assembly of high-variation products. This article shows the appropriate combination of centralized and decentralized approaches can be leveraged to achieve better planning and increased throughput in manufacturing. With flexible cycle control for work stations and suitable assistance at the assembly workstation, the previous shop-floor oriented organization style can be transformed into a series-like manufacturing process. This is done using a multi-layered infrastructure that follows the Industry 4.0 paradigm of decentralized information processing through autonomous ...
Industry 4.0 Science | Volume 39 | 2023 | Edition 1 | Pages 34-40 | DOI 10.30844/I4SE.23.1.34
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
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
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