digital factory

Although SMEs are not directly affected by the statutory reporting obligations for carbon accounting, as suppliers they are obliged to meet the requirements of sustainability reporting. In addition to a holistic life cycle analysis, this requires a high-quality database within production in order to determine the specific CO₂ footprint. A central element is the implementation of a Machine Carbon Footprint (MCF). This article aims to develop and implement an MCF focusing on its applicability for SMEs. For this purpose, data is recorded and visualized in real time on a machine tool. The measurement data is then processed, stored and visualized using open-source low-code platforms. Real-time data flows enable the precise determination of the production-specific carbon footprint and, in conjunction with order data, the Product Carbon Footprint.

The volatility of economic conditions and rapid technological progress require production sites to be constantly adapted and improved. This needs highly qualified factory planners who can use digital planning tools efficiently. The best qualifications emerge from closely interlinking the teaching of planning methods and the application of these methods in a planning project according to the principle of “learning by doing”.

The shortage of skilled labor is putting pressure on many manufacturing companies worldwide. While skilled labor is becoming scarcer in traditional industrialized economies, proper training is urgently needed in countries with high unemployment. But how to solve this challenge? Find out what makes learning factories so successful in this issue.

The world’s rising energy and raw material costs are a reason for many companies to reduce energy and resource waste in their own production. Based on this plan, the Federal Ministry of Education and Research (BMBF) initiated in 2009 the project EnHiPro. Until May, 2012 the Technische Universität Braunschweig and three other research partners developed a system to make the energy demand of machines tangible by utilizing smart metering strategies. For the analysis and visualization of the energy flows, the c4c Engineering company was brought into the team in order to engineer the EnyFlow app that makes the energy flows and states of machines transparent on an tablet PC.

Germany is known to have a very powerful and highly competitive industrial sector. In this context, the manufacturing sector accounts for around 50 % of German exports and is facing a variety of new challenges like an increasing international competitive pressure, more complex value adding networks and more volatile markets [1]. Constant innovation is going to be required and therefore flexible production systems are increasingly gaining in importance. This article discusses the results of a collaborative industry survey about flexible production systems, which have been conducted in the context of the European research project cPAS. On this basis, requirements and potential of an increasing horizontal integration between companies and production planning / runtime systems are discussed.

The layout planning represents a prime example of the interdisciplinary nature of factory planning. A comprehensive cooperation provides opportunities to involve ideas and experiences of as many people as possible, to exploit synergies, to realize a faster coordination of the planning status between the departments and thus improve the effectiveness and efficiency of the planning process. The development of more powerful computer technology and the increasing popularity of mobile devices (e.g. smartphones, tablet computers) provide new potentials and possibilities for the use of Augmented Reality (AR) in the application field of factory planning. This paper describes an approach for the application of AR in participative layout planning.

Ensuring healthy, safe and competitive work is a major challenge in industrial production particularly regarding the demographic change in Germany. Especially work systems with a high amount of manual tasks require appropriate solutions. The article discusses the potential of hybrid human-robot work systems in manufacturing focusing assembly tasks.

Increasingly complex and technology-driven markets require a broad knowledge and qualifications of professionals in manufacturing companies. The range of needs for long-term competitive knowledge adaptation is versatile. Especially in view of the forecasted lack of qualified young people, it is more important to sustainably educate existing staff. Thus it is necessary to create sustainable and innovative learning environments which provide the necessary knowledge, qualifications and skills. An adequate and consistent concept represents the advanced Learning Factory (aLF) and is discussed in this paper.