Open Access Articles

Within the concepts of Industry 4.0, the term “Smart Factory” stands for the creation of effective production environments through digitalization and cyber-physical systems. Most manufacturers plan to make their manufacturing systems more automated, flexible and adaptive. In the course of these efforts, intelligent materials are increasingly brought into focus. Combined actuator and sensory properties enable the construction of lightweight and compact multifunctional actuator-sensor systems that are operated in an energy-efficient, noise-free and emission-free manner. This makes them appropriate for building networked systems. Shape memory alloys (SMAs) and dielectric elastomers (DEs) are particularly suitable for building intelligent actuators, and are presented in this article alongside several use cases.

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.

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 ...

The need to sometimes respond very quickly to changes requires companies to have a high degree of flexibility and speed of reaction. Application system architectures, which usually consist of old and self-developed systems, often do not allow companies to meet these requirements. However, investment funds for new software are limited, so priorities must be set when it comes to replacing legacy systems. An adaptability analysis is an efficient analysis method for planning the renewal of the application system landscape. This article describes the procedure and results of an adaptability analysis, using the example of an internationally active automotive supplier.

The planning of logistics processes and their efficient implementation are decisive competitive factors for customized plant construction. On the construction site, however, the collection of logistics data is often neglected, preventing the project planner from building a reliable database. Related information gaps can be closed with the help of a digital shadow that collects logistics-relevant data (partially) automatically, stores them in a consistent manner and makes them available to project management. This article describes the first important results of a research project on information and communication processes in construction site logistics and explains their vital role in the development and use of a digital shadow.

Emergency organizations such as fire departments or technical relief organizations are expected to react very quickly – sometimes to unknown situations – and provide the appropriate assistance. Can principles used in these organizations be transferred to IT support, e.g. for ERP systems? An experiment in an IT service unit investigates this question – with surprising results.

Precise stochastic demand calculation is the key to successful material planning, i. e. to always have exactly the right quantity on hand. However, decision-makers are faced with the dilemma of which of the many forecasting methods they should use, adapted to the item properties as much as possible. This paper examines the optimization potential of a self-developed automatically optimizing forecasting approach based on ten common forecasting methods, which are evaluated using two case studies from the capital goods industry.

Digital twins (DT) for circular economy (CE) offer a promising approach as part of digital data ecosystems for more sustainable value creation. By mapping and analyzing product, component and material specific data along the li- fecycle, it is possible to address current challenges such as climate change and resource scarcity. Within Catena-X, specific solutions based on this cross-company exchanged data and information are developed. Here, the “R-Strategy Assistant” is presented. It is an application, which identifies the best CE-Strategy based on DT data at the end of a vehicle's life.

Resource-efficient businesses have become increasingly important for companies in recent years. Although this brings new potentials, the practical implementation in the form of suitable business models is accompanied by challenges. In this paper, we will examine which concepts and methods already exist for the development of circular and resource- efficient business models and show approaches and solutions from science and practice using the example of interdisciplinary research projects.

How can organisations successfully participate in interoperable and decentralised data ecosystems? To answer this question, this paper presents a process model using the transport logistics industry as an example, which methodically describes the collaborative and interdisciplinary development of services in the decentralised federated data ecosystem Gaia-X [6]. The model supports evaluation and decision-making processes within the development of decentralised data ecosystems in practice and helps IT decision-makers and participating stakeholders to identify the relevant communication flows in a use case. It can be used independently for specific use cases, data spaces and connector technologies and ensures that the communication and alignment of individual development statuses in a decentrally organised framework is comprehensible and understandable for the overall context.