Cyber-Physical Systems

Derivation of MTM Analyses from Motion Capture Data

Derivation of MTM Analyses from Motion Capture Data

Evaluation of the procedure and comparison with a manual MTM analysis
Silas Pöttker ORCID Icon, Maria Neumann ORCID Icon, Martin Benter, Constantin Eckart ORCID Icon, Ulrike Wolf ORCID Icon, Peter Kuhlang, Hermann Lödding ORCID Icon
For around 15 years, German labor productivity per working hour has been increasing at significantly less than 1% per year. At the same time, more detailed productivity analyses reveal high potential in companies. The issue is that the required MTM analyses are complex and not yet employed as broadly and frequently as would be necessary. One solution is the use of digital technologies such as motion capture. These make it possible to carry out productivity analyses with little effort, as they provide data that accelerates the analysis. The MTMmotion® tool from the MTM ASSOCIATION e. V. was developed with the aim of carrying out valid and compliant MTM analyses using data provided by other technologies. This article compares the method developed for a motion capture system and MTMmotion® with a conventional MTM-1® analysis. The main result is that digital technologies can be used to create valid MTM analyses in early planning phases with little effort in order to make early ...
Industry 4.0 Science | Volume 41 | 2025 | Edition 5 | Pages 112-119 | DOI 10.30844/I4SE.25.5.108
Enabler for the Digital Twin

Enabler for the Digital Twin

Requirements for Technical Documentation 4.0
Christian Koch, Lukas Schulte, René Wöstmann, Jochen Deuse ORCID Icon
The increasing heterogeneity and complexity of industrial plant components from different manufacturers make it difficult to handle technical documentation consistently. In addition, the flexibility required for system changes challenges the long-term usability and legally compliant design of this documentation throughout the entire life cycle of cyber-physical production systems. This article contributes to the discussion on Technical Documentation 4.0 by systematically analyzing existing specifications and approaches and by proposing a concept for a holistic documentation framework.
Industry 4.0 Science | Volume 41 | 2025 | Edition 4 | Pages 76-85
Intelligent Digital Twins in Production

Intelligent Digital Twins in Production

Driving efficiency and accelerating agility in production planning
Cedric Kiener ORCID Icon, Steffen Schwarzer
Intelligent digital twins (IDT), as the next evolutionary stage of digital twins, have the potential to accelerate and optimize processes within companies. The intelligent twin presented here independently analyzes 3D CAD data and automatically conducts a physical simulation of the assembly. Utilizing the IDT optimized assembly, reduces production costs and accelerates the production planning process. This specific use case illustrates the broader possibilities and advantages of IDTs, offering valuable insights for their transferability.
Industry 4.0 Science | Volume 41 | 2025 | Edition 3 | Pages 84-90
Assembly in Transition

Assembly in Transition

Empirical results of digitalization
Mathias König ORCID Icon, Herwig Winkler ORCID Icon
Assembly is an important part of industrial production and is also characterized by a high proportion of manual work. Manufacturing companies have an intrinsic interest in increasing personnel productivity and preventing unit labor costs from rising. Many thus hope to gain economic benefits by implementing digitalization projects. The potential of digitalization in assembly must be exploited to achieve these goals.
Industry 4.0 Science | Volume 41 | 2025 | Edition 1 | Pages 42-49
Production of Circular Photovoltaic Systems

Production of Circular Photovoltaic Systems

The potential of digital technologies
Verena Luisa Aufderheide ORCID Icon
The circular economy (CE) promises a more sustainable use of resources by managing products in a cycle and striving for a transformation from a linear to a circular supply chain. In particular, digital technologies as enablers for the circular economy have been increasingly researched and applied in practice in recent years. This article describes which digital technologies offer potential for increasing circularity in the production of circular photovoltaic (PV) systems.
Industry 4.0 Science | Volume 40 | 2024 | Edition 1 | Pages 30-36
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
The Digital Supply Chain Becomes Decentralized Controlled

The Digital Supply Chain Becomes Decentralized Controlled

A Vision?
Klaus-Jürgen Meier
The introduction of digital technologies will provide completely new possibilities for the design and operation of supply chains in the future. A decisive step should be the decentralization of structures and processes inside firms which also shows effect on the cooperation between companies. It finally offers the opportunity to solve long-standing problems of supply chain management. When are companies ready to take this step? The technologies are.
Industrie 4.0 Management | Volume 37 | 2021 | Edition 2 | Pages 30-34
Lifecycle Monitoring of Intelligent Production Systems

Lifecycle Monitoring of Intelligent Production Systems

An Innovative Concept for the Implementation of Smart Maintenance
Eckart Uhlmann ORCID Icon, Eckhard Hohwieler, Claudio Geisert
Digitization of industrial production processes allows the introduction of datadriven business models using Cyber Physical Systems (CPS) and Industrial Internet of Things (IIoT). To ensure efficient manufacturing, production systems must be able to communicate and interact with their environment, to monitor wear conditions, and to selfadapt their behavior to a given situation. This article gives an overview about the historical development of intelligent production systems with focus on condition monitoring and predictive maintenance in an availability oriented business model.
Industrie 4.0 Management | Volume 35 | 2019 | Edition 5 | Pages 45-49
Work 4.0—How Digital Technologies Enable Flexible Work

Work 4.0—How Digital Technologies Enable Flexible Work

Flexibilization of work through relevant technologies and their resulting potentials
Erik Hunold
Digitization and related technologies extend the possibility of work design. As companies face the challenge of being able to respond to changing market conditions with agility, digital technologies are creating new ways to increase work flexibility in response to the need for better employee work-life balance. It is important to consider both the needs and requirements of employees and companies and to find satisfactory solutions for both sides. The present article describes how flexible work design is currently used in companies and how the technologies of digitization can be classified and brought together. Based on a structured literature analysis on the state of the art of the potential of flexible work, the article shows the synergy effects of cyber-physical systems, cloud computing and the Internet of Things as the basis for a consensual solution of the needs of companies and their employees.
Industrie 4.0 Management | Volume 35 | 2019 | Edition 3 | Pages 11-14
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
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