Digitalisierung

In factory operations, measuring equipment is often used without automatic storage or further processing possibilities of the measured value. In this case, employees must capture and process the measured values manually. In this article, an approach for the optical detection and digitization of measured values with the help of machine learning methods is presented. This aims to reduce the workload of the employees, avoid reading errors and enable automated documentation.

Many departments have already recognized the enormous increase in efficiency and personnel relief from routine activities through process automation. These digital thought leaders have begun to automate office processes using new technologies such as Robotic Process Automation (RPA), low code in the Microsoft Power Platform or in SAP. However, the positive experiences often remain in individual departments. Due to the lack of a strategic superstructure, companies as a whole have not yet succeeded in systematically transferring the added values to all areas. The organizational solution for this is called a "Center of Automation". Sometimes it is enough for the team to consist of two members to bring an overarching, digital process mindset into a company. (Only in German)

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.

In the course of digitalization, more and more digital technologies are being used in various areas of logistics. The occupational field is changing and problem-solving and abstracting skills as well as competencies in dealing with IT systems and data are increasingly required. Based on a literature review, this article provides an overview of the current situation in the logistics working world. Effects of digitalization as well as requirements and future competencies in the working world 4.0 are highlighted. Finally, a guideline for the management level is derived in order to promote the acquisition of competencies. (Only in German)

A robust and resilient supply chain is a critical success factor for the competitiveness of manufacturing companies. However, today’s supply chain faces various challenges, such as higher complexities and increasing dynamics coming from megatrends (i. e. globalization and sustainability). The medium-sized drive technology industry, with its global supply chains and high customer requirements, is particularly affected by these challenges. Therefore, digitalization initiatives are crucial. This article analyzes current digitalization projects in the drive technology industry in order to identify relevant trends and fields of application. Synthesized from the industry's target picture for higher resilience/ flexibility, greater transparency and more sustainability along the supply chain, these provide guidance for medium-sized companies and their digitalization strategies. (Only in German)

The trend toward digitization o ers considerable potential; this is particularly true in supply chain management (SCM). However, not every technology is suitable for every company and its processes. This article presents a structured approach that supports companies in the selection process. The approach consists of several phases: Starting with the identi cation of business goals and ending with the selection of those technologies that seem most promising. Its applicability was tested in a research project at a logistics service provider. It is easily transferable to a concrete decision-making situation.

Manufacturing SMEs are structurally di erent from other companies and therefore have special requirments for Manufacturing Execution Systems (MES) and the associated software selection. Process models must therefore be adapted. For the identication of requirements, a systematic categorization based on existing models was performed. With the help of an existing market research platform, further selection steps were developed in order to provide a useful and easy-to-use tool for SMEs, which enables them to select efficiently sufficient MES-software according to their needs.