Manufacturing Systems

Intelligent Shopfloor Assistants

Intelligent Shopfloor Assistants

Increasing productivity through the use of generative AI
Eckart Uhlmann ORCID Icon, Julian Polte ORCID Icon, Christopher Mühlich ORCID Icon, Yassin Elsir
In modern production companies, a heterogeneous IT landscape often complicates day-to-day work. A promising antidote is the use of intelligent agents, which use generative AI for routine tasks and can therefore increase efficiency. Whether these intelligent systems can be successfully integrated into existing networks determines whether the flow of information can be improved and manual effort reduced.
Industry 4.0 Science | Volume 40 | 2024 | Edition 6 | Pages 64-71
Introduction of Machine Learning in Production

Introduction of Machine Learning in Production

An SME-specific, holistic guide
Manuel Savadogo, Malte Stonis ORCID Icon, Peter Nyhuis ORCID Icon
Machine learning offers a wide range of potential, especially in production, and is therefore becoming increasingly important. However, small and medium-sized businesses are lacking guidelines that are specifically tailored to their individual challenges to guide them step-by-step through the process. In conjunction with a potential analysis, the determination of relevant prerequisites and a maturity assessment, this article can serve as a guide for SMEs.
Industry 4.0 Science | Volume 40 | 2024 | Edition 6 | Pages 88-95
Setting Up Assembly Assistance Systems

Setting Up Assembly Assistance Systems

System for the efficient configuration of assembly instructions and assistance functions
Dennis Keiser, Dario Niermann ORCID Icon, Michael Freitag ORCID Icon
In industrial assembly, humans are working more closely with machines due to assembly assistance. However, despite their great potential, the implementation of digital systems is time-consuming, which entails high training requirements. Small and medium-sized businesses, in particular, are reaching their limits. A newly developed setup system is designed to facilitate the introduction and use of such assembly assistance systems and increase their acceptance.
Industry 4.0 Science | Volume 40 | 2024 | Edition 6 | Pages 32-39
Double Transformation in Mechanical and Plant Engineering

Double Transformation in Mechanical and Plant Engineering

Digitalization and sustainability for one-of-a-kind and small-batch manufacturers
Christoph Laroque ORCID Icon, Deike Gliem ORCID Icon, Sigrid Wenzel ORCID Icon
A decisive competitive factor for smaller and medium-sized manufacturers of one-of-a-kind and small batches is their products’ timely completion, delivery and commissioning. Precise logistics planning is just as important as production control. However, the processes are often characterized by uncertainties, e.g. due to local conditions at the customer or cooperation with suppliers. Digital shadows for data evaluation in real time offer a convincing solution.
Industry 4.0 Science | Volume 40 | 2024 | Edition 5 | Pages 10-17 | DOI 10.30844/I4SE.24.5.10
From Lean Production to the Sustainable Production System of the Future

From Lean Production to the Sustainable Production System of the Future

An innovation factory as a multi-stage learning factory
Markus Schneider, Christoph Müller
The typical problems of a medium-sized company, coupled with the new requirements for sustainability, harbor the potential for economic tension. Learning factories can counteract this: they simulate production processes and offer an environment where participants can develop knowledge and skills in a realistic production setting. Establishing an innovation factory not only increases productivity, but also significantly reduces land consumption.
Industry 4.0 Science | Volume 40 | 2024 | Edition 4 | Pages 78-84
Spare Part Production of Vehicle Gearbox Bearings

Spare Part Production of Vehicle Gearbox Bearings

A method using additive manufacturing
Norbert Babel, Tobias Empl, Raimund Kreis ORCID Icon, Peter Roider
Spare parts for older products are often difficult to obtain or cannot be produced in an economically viable way using conventional manufacturing techniques. This article examines whether damping elements for gearbox bearings (in/for the automotive sector) can be manufactured from thermoplastic polyurethanes (TPU) with the same or compatible properties as the original part alternatively using additive manufacturing.
Industry 4.0 Science | Volume 40 | 2024 | Edition 2 | Pages 16-22
Safeguarding Against Risks in the Wire Arc Additive Manufacturing Process

Safeguarding Against Risks in the Wire Arc Additive Manufacturing Process

Lennart Grüger ORCID Icon, Tim Sebastian Fischer, Ralf Woll, Johannes Buhl ORCID Icon
In this article, the potential risks in wire arc additive manufacturing are analyzed using failure mode and effects analysis. To achieve this, 186 possible causes of risk were analyzed and the five most critical risks were discussed in detail. Four significant risk factors were identified in the construction process. The fifth risk relates to the shielding gas flow. This is only one influencing factor among the welding parameters, which have strong interactions with each other. Therefore, their relationships should be analyzed on the basis of numerous tests.
Industry 4.0 Science | Volume 40 | 2024 | Edition 1 | Pages 63-69 | DOI 10.30844/I4SE.24.1.63
Sustainability in Industrial Manufacturing

Sustainability in Industrial Manufacturing

Resource-efficient circular economy through the use of a pellet 3D printer
Bruno Gallace, Michael Blug, Adrian Huwer ORCID Icon, Michael Mattern, Michael Wahl
In additive manufacturing – which is also known as 3D printing – plastic waste is produced, for example in the form of required support structures or faulty prints. One option for resource recirculation in additive manufacturing is direct use in a pellet 3D printer that incorporates fused granulate fabrication (FGF). The elimination of the filament production process step reduces the manufacturing time and the energy required for recirculation.
Industry 4.0 Science | Volume 40 | 2024 | Edition 1 | Pages 14-21
Efficient Production Simulation

Efficient Production Simulation

A method for software-supported collaboration between production and simulation experts
Marec Kexel, Walter Wincheringer
Production simulations involve considerable effort, among other things, due to the knowledge transfer between the domain expert and the simulation specialist. For small and medium-sized companies, this often represents an economic hurdle in the use of simulation. In this article, a method for a software- supported cooperation between the production expert and the simulation specialist is presented, which leads to a considerable reduction in effort. This means that the advantages of simulation can be used economically even with low optimization potentials.
Industrie 4.0 Management | Volume 39 | 2023 | Edition 6 | Pages 46-50 | DOI 10.30844/IM_23-6_46-50
Optimizing Production Processes with AI-based Knowledge Transfer

Optimizing Production Processes with AI-based Knowledge Transfer

How AI can secure human-oriented, experiential knowledge in the KI-eeper project
Nicole Ottersböck, Holger Dander ORCID Icon, Christian Prange ORCID Icon
Implicit experiential knowledge will be lost through the retirement of the babyboomer generation. This know-how is difficult to capture and transfer. The KI_eeper project aims to develop an efficient AI-based system that automatically identifies and stores knowledge in the work process. The resulting knowledge base will provide assistance to all employees. The system will be designed in cooperation with employees according to their needs to gain high user acceptance.
Industrie 4.0 Management | Volume 39 | 2023 | Edition 6 | Pages 51-54
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