Autor: Sigrid Wenzel

The fischertechnik® Learning Factory 4.0 has proven to be a suitable experimental environment for testing digital twins. Depending on the targeted maturity stage, the functions of a digital twin range from status monitoring and forecasting to the operational control of production and logistics systems. To systematically classify these functions, this article presents a maturity model that serves as a framework for the development of a digital twin. Building on this, selected use cases are implemented in a test and development environment based on a system architecture with multi-layered logic structure. These initial implementations serve to highlight application purposes, relevant methods, and typical challenges and potentials in the transfer to real factory environments.

Despite the commercial availability of simulation tools, using of discrete-event simulation for complex production and logistics systems is becoming increasingly challenging. It requires extensive expertise, high data quality, and considerable time and financial resources. For many years, therefore, there has been high demand for methodological and organizational support for the conduction of simulation studies. This article is based on an analysis of relevant publications and aims to classify previous research on improving the use of simulation. It also raises the question of the need for assistance in applying discrete event simulation and identifies areas for action.

For a successful implementation as well as sustainable use and maintenance of digital twins for production and logistics systems, it is necessary to identify relevant use cases and master the associated challenges. This paper analyzes scientific literature on common applications and challenges in the implementation of digital twins for the planning and operation of production and logistics systems. To confirm the practical relevance of the results, the results of an empirical survey have also been included. The findings are used to derive key focus areas for the successful implementation and long-term use of digital twins in production and logistics.

A decisive competitive factor for smaller and medium-sized manufacturers of one-of-a-kind and small batches is their products’ timely completion, delivery and commissioning. Precise logistics planning is just as important as production control. However, the processes are often characterized by uncertainties, e.g. due to local conditions at the customer or cooperation with suppliers. Digital shadows for data evaluation in real time offer a convincing solution.

Small and medium-sized enterprises still face the challenge of shaping their digital transformation. Maturity models offer a way to capture the situation within a company and support the formation of an Industry 4.0 vision. This paper presents a methodology that companies can use to develop a roadmap for shaping digital transformation by enabling the transfer of this vision into concrete decision-making steps.

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.