Design

Professor Bernd Scholz-Reiter studied industrial engineering at the Technical University of Berlin. After several positions in Germany and abroad, he accepted the call to the University of Bremen in 2000, where he initially held the professorship of Planning and Control of Production Systems in the Department of Production Engineering. From 2002 to 2012, he also headed the Bremen Institute for Production and Logistics (BIBA). From 2012 to 2022, Bernd Scholz-Reiter was rector of the University of Bremen.

Following the success of subscription models such as Netflix or Spotify in the IT and multimedia sector, the implementation of Industry 4.0 is increasingly creating the conditions for offering comparable models in the industrial context. Accordingly, pioneers are offering subscription models for printing machines, compressors or locomotives, for example. Providers do not act alone, but are supported in the design and implementation of the subscription offer by various players such as financiers, insurance companies or digitization service providers. This creates what is known as a subscription ecosystem. This article sheds light on these ecosystems and shows to what extent which players can participate in industrial subscription models. Depending on customer acceptance of these models, a wide variety of companies have the opportunity to benefit from the subscription trend and to tap into new markets and customer groups

Based on theoretical-empirical findings presented in the article "Technology Acceptance of Robotic Process Automation (RPA) (Part 1)", this article presents the results of an empirical study on the acceptance of robotic process automation (RPA) using structural equation modeling. This survey was conducted in a finance department of the business unit "Smart Infrastructure - Digital Grid" of a global technology company distributed throughout Germany.

n the automotive industry, preventive quality actions are applied to ensure the quality of the end products. During production ramp-up the occurrence of nonconformities can be a critical issue. Nonconformities with new and innovative products can be especially challenging due to limited experience of previously unknown processes. To address this challenge, an IT application has been developed to capture the organization's existing knowledge and use this to support the problem- solving team in applying an enhanced 8D method.

Huge amounts of information are stored in the memory of every employee. How a product works, best practices in departments, customer-specific information, general market and competitive knowledge, etc. This expertise is a blind spot in most companies. So how do you make in-house know-how available? And in a time when many employees work remotely, in home offices, even across countries or continents?

Digital twins are an important part of the Industry 4.0 idea. They mirror physical goods in the digital world and enhance them with additional capabilities and functions for analysis, forecasting and decisionmaking. This paper contributes to the classification and assessment of Digital Twins using a multidimensional maturity model. The presented method "DT-Assess" enables an application-specific assessment of Digital Twins. The developed maturity model consists of seven categories with a total of 31 characteristics to be evaluated. The systematic evaluation in five application scenarios allows, for the first time, a classification of the respective "digital twin" implementation or concept with the aim of identifying further development options and weaknesses.

As a result of dynamic markets, industrial companies often reach their limits to remain competitive. Smart connected solutions (SCS) comprise data-based and service-oriented offerings to stay successful. This paper provides practice-oriented insights into SCS maturity, challenges in building SCS business models and recommendations for action for industrial companies.