automation

Automation of Production Planning and Control

Automation of Production Planning and Control

A deep dive into production control with intelligent agents
Jonas Schneider, Peter Nyhuis ORCID Icon, Matthias Schmidt
How can artificial intelligence (AI) automate production planning and control? This study examines its potential to enhance efficiency in modern production environments. The focus is on establishing a robust data infrastructure that integrates real-time, historical, and contextual data to create a solid basis for AI models. Reinforcement learning (RL) is applied to aid automation. A roadmap for implementation, focusing on practical application, is presented. This roadmap incorporates simulation-based training methods and outlines strategies for continuous improvement and adaptation of production processes.
Industry 4.0 Science | Volume 41 | 2025 | Edition 5 | Pages 86-93 | DOI 10.30844/I4SE.25.5.84
Bridging Automated and Traditional Approaches in Material Transport

Bridging Automated and Traditional Approaches in Material Transport

Why manual tugger train systems remain prevalent in intralogistics
Christoph S. Zoller, Wladimir Rempel, Justus Langer, Bonita Grzechca
The ongoing automation of production logistics through driverless transport systems (DTS) can significantly enhance the efficiency and quality of transport processes. Despite these advantages, many companies still choose manual tugger train systems for material supply. Semi-structured interviews with industry experts provide insight into the reasons behind these decisions, with particular emphasis factors that extend beyond purely economic assessment. The findings indicate that the lack of flexibility of driverless transport systems and the effort required for implementation effort are key reasons why manual transport solutions are often preferred in intralogistics.
Industry 4.0 Science | Volume 41 | 2025 | Edition 4 | Pages 60-66
I4S 4/2025: Smart Logistics

I4S 4/2025: Smart Logistics

Sustainable, resilient processes along the entire value chain
Logistics is entering a new era. Climate change and geopolitical uncertainties are shifting the focus to resilience and sustainability. The concept of smart logistics is gaining importance. But what exactly makes logistics smart, and how can it help us organize our societies and the economy? Approaches such as predictive analytics, demand analysis, and machine learning show why smart logistics is more than just a technological trend.
I4S 2/2025: The Future of Production with AI, Cobots and Virtual Worlds

I4S 2/2025: The Future of Production with AI, Cobots and Virtual Worlds

Technology needs innovative, value-adding business models
Artificial intelligence, collaborative robotics, and virtual worlds, such as the metaverse, are fueling visions for new forms of industrial value creation. However, innovation alone is not enough—given that these technologies only develop their full potential through intelligent business models. How can companies efficiently integrate AI-supported automation, cobots and digital twins into their processes?
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.
Improving Social Media Moderation with Generative Language Models

Improving Social Media Moderation with Generative Language Models

Study on the detection and correction of disinformation
Anton Schegolev, Maximilian Ambros ORCID Icon
Fake news are increasingly dominating the digital world. The question arises: Can modern technologies reverse this trend? The article highlights the potential of the GPT-4o language model for identifying fake news in online comments and news articles and for correcting false information. With impressive accuracy, the model shows how language technology can combat misinformation.
Industry 4.0 Science | Volume 40 | 2024 | Edition 6 | Pages 72-79 | DOI 10.30844/I4SE.24.6.72
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
Large Language Models (LLM) in Production

Large Language Models (LLM) in Production

An analysis of the potential for transforming production processes in modern factories
Pius Finkel ORCID Icon, Peter Wurster ORCID Icon, Robin Radler
The rapid development of generative artificial intelligence is opening up new avenues for the manufacturing industry amid a shortage of skilled workers. Large language models can potentially make production processes in medium- sized businesses more efficient. But how exactly is this potential measured? Key areas of application such as communication, training and knowledge management show why a lot depends on employee acceptance.
Industry 4.0 Science | Volume 40 | 2024 | Edition 6 | Pages 48-55 | DOI 10.30844/I4SE.24.6.48
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
ReThink! Smart Manufacturing 2024
Start 23.06.2024 - End 25.06.2024

ReThink! Smart Manufacturing 2024

Rethink! Smart Manufacturing helps leaders in the manufacturing industry to optimize, strengthen and redesign their businesses. At ReThink! Smart Manufacturing 2024, which will take place from June 23-25 in Berlin, visitors can discuss with up to 150 executives how the latest trends and technologies in smart manufacturing, such as factory automation, AI and robotics, are impacting every aspect of business. Take part in the event and secure your ticket today!
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