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The fifth generation of mobile communication (5G) is a wireless technology developed to provide reliable, fast data transmission for industrial applications, such as autonomous mobile robots and connect cyber-physical systems using Internet of Things (IoT) sensors. In this context, private 5G networks enable the full performance of industrial applications built on dedicated 5G infrastructures. However, emerging wireless communication technologies such as 5G are a complex and challenging topic for training in learning factories, often lacking physical or visual interaction. Therefore, this paper aims to develop a real-time performance monitoring system of private 5G networks and different industrial 5G devices to visualise the performance and impact factors influencing 5G for students and future connectivity experts. Additionally, this paper presents the first long-term measurements of private 5G networks and shows the performance gap between the actual and targeted performance of private 5G networks.
Global, competitive markets which are characterised by mass customisation and rapidly changing customer requirements force major changes in production styles and the configuration of manufacturing systems. As a result, factories may need to be regularly adapted and optimised to meet short-term requirements. One way to optimise the production process is the adaptation of the plant layout to the current or expected order situation. To determine whether a layout change is reasonable, a model of the current layout is needed. It is used to perform simulations and in the case of a layout change it serves as a basis for the reconfiguration process. To aid the selection of possible measurement systems, a requirements analysis was done to identify the important parameters for the creation of a digital shadow of a plant layout. Based on these parameters, a method is proposed for defining limit values and specifying exclusion criteria. The paper thus contributes to the development and application of systems that enable an automatic synchronisation of the real layout with the digital layout.
It is expected that ongoing digitalisation will drive the merger between the manufacturing world and the internet world, possibly leading to a next industrial revolution, currently called “Industry 4.0”. The driving forces behind this development are new business opportunities and competition advantages arising from mass production customisation as well as rapid individual product development and manufacturing. Key factors of the development towards Industry 4.0 are discussed. Threats and opportunities arising from these developments for future production are discussed. Actual examples from real-time customized manufacturing of consumer products are given. As mechatronic systems and industrial robots are widely used in manufacturing and in particular in assembly, it is discussed how they can be connected to and used in digitalised industrial systems. Different examples of remote controlled systems are presented, like remote controlled KUKA robot for handling and quality control, PLC-controlled equipment, drive systems, FESTO handling system and others. The architecture of an assembly cell is presented, where industrial robots are set-up for batch-one production or can directly receive control / production information on-line and in real-time over the factory network. Methods for remote maintenance and monitoring of systems over the internet and production operator support over the internet are presented as well.
The market for indoor positioning systems for a variety of applications has grown strongly in recent years. A wide range of systems is available, varying considerably in terms of accuracy, price and technology used. The suitability of the systems is highly dependent on the intended application. This paper presents a concept to use a single low-cost PTZ camera in combination with fiducial markers for indoor position and orientation determination. The intended use case is to capture a plant layout consisting of position, orientation and unique identity of individual facilities. Important factors to consider for the selection of a camera have been identified and the transformation of the marker pose in camera coordinates into a selectable plant coordinate system is described. The concept is illustrated by an exemplary practical implementation and its results.