Typeset

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 COVID-19 crisis had an unmistakable impact on the procurement situation in global supply chains, to which companies had to adapt quickly. The effects make it clear that to reduce risks, companies must address the structure and transparency of supply chains. The following article examines what knowledge the actors have and how digitalization can lead to further improvement. The results show that companies currently have little supply chain knowledge beyond their direct suppliers, but are increasingly able to obtain the supply chain data they require. At the same time, the results indicate that there is still potential to increase transparency and the use of data.

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 combination of product service systems and big data requires a change in the existing, traditional business models and a repositioning of the companies. Since these changes are often a challenge, this article uses the example of predictive maintenance to present the influences of big data and product service systems on the business models of medium-sized companies in mechanical and plant engineering. Based on a systematic literature review in combination with expert interviews, numerous practical business model implications were obtained, providing sound guidance for industry representatives.