Software

The digital twin has moved into the focus of manufacturing companies and has been identified by Gartner as a key technology [1]. In the automotive industry, VW uses the digital twin in the cloud to plan, control and optimize production at all 122 locations in the future [2]. The digital twin is also the basis and an integral part of new, digital business models and the digitization of production companies. This article gives an overview of the current state of the art and describes a flexible reference model for planning and optimizing production systems based on the digital twin. The focus is on the one hand on the optimization of static layouts and material flows and on the other hand on the optimization of dynamic material flows and the temporal organization of processes.

In this contribution, a method for the implementation of Industry 4.0 projects in production and logistics for small and medium-sized enterprises (SME) is described. This method takes various boundary conditions of SMEs into consideration and has been applied in different projects with SMEs within the “Mittelstand 4.0-Kompetenzzentrum Hamburg” initiative. The method focuses on an integration of new technologies into existing systems and the connection of newly generated data with known information flows.

Many large companies are increasingly facing the pressure to meet rapidly changing customer needs and to respond quickly to new technologies. These companies often suffer from coercive bureaucracy, that is, rule rigidity. For this reason, a huge increase in alternative working practices such as agile working has been noticed lately. While it was firstly found in small business start-ups, more and more traditional companies as DAX-companies have tried to use agile working practices selectively in their development departments. However, can agile working be so simply transferred to development of traditional products?

The interworking of Manufacturing Execution Systems (MES) and operating resources is a prerequisite for the flexible and versatile production in Smart Factories of Industry 4.0. This article describes a qualitative and quantitative analysis of an MES integration based on an industrial laser assistance system for worker guidance. It analyzes the situation and requirements from a user perspective with special consideration of implemented systems, interfaces, protocols as well as Plug & Produce. The study uses qualitative analysis results from opinion makers and quantitative analysis results from leading manufacturing companies among others from the automotive and aerospace industry. Thus, the study supports decision making for MES investments in Industry 4.0.

The large number of systems offered on the market makes a well-founded selection process necessary from the requirement survey to the final system selection. A comprehensive model that systematically supports and simplifies this process is the subject of this two-part article. The methodology goes beyond a questionnaire-based query and verifies system capabilities using structured case studies. The first part of the article [1] describes the process steps from the survey and collection of requirements of the customer to the system to their structuring in customer specifications. The present second part outlines the process steps of the system rough selection up to its fine selection. The individual selection steps are methodically supported by practical references as well as by the use of concrete tools. Using the described methodology selected systems can be objectively compared - a prerequisite for effective and efficient system selection for industrial companies.