Autor: Michael Freitag

Wire ropes are used in different applications and human life often depend on their integrity. Therefore, technical personnel checks the tightropes on a regular basis but there are some difficulties in detecting damaged areas. Consequently, wire ropes are exchanged rather too early than too late causing avoidable extra costs. In this paper, the project MOBISTAR is presented that combines a magneto-inductive and an optical sensor to detect damages and a software based on Convolutional Neural Networks to evaluate those defects.

The targeted curing of glass fiber-reinforced plastics (GFRP) is important to ensure the advantageous material properties. The use of RFID for curing monitoring is a completely new approach. This paper presents an experiment in which an RFID transponder has been integrated into GFRP and the Received Signal Strength Indicator (RSSI) has been measured during the curing process. The result shows that the RSSI can be used as an indicator for curing GFRP. The advantages of RFID technology compared to conventional methods for cure monitoring are the wireless application as well as the benefit, which an integrated RFID transponder generates in the further product life.

New production technologies have inherent technical risks, but also established production technologies can not always be transferred to new products or components without problems. Accordingly, these technical risks must be taken into account when planning production systems. This paper presents an approach for the optimized allocation of development resources with regard to the technical risks of production technologies and processes. First, the production scenario is modeled and simulated using GRAMOSA. Then the simulation results are used for the optimized assignment of the development budget by means of mathematical optimization.

Logistic processes at seaports and inland terminals play an important role for finished vehicle logistics. High flexibility and reactivity are required to cope with frequent deviations from original operational planning. This paper describes a concept for developing tools and systems to optimize planning and control processes. This includes a simulation backed planning system and a control system for order allocation using mobile devices and their GPS as well as sensor data.

The economic operation of the offshore wind energy turbines is of fundamental importance for the industry. Due to the prevailing weather conditions at sea these operations require optimal plannung and control. This contribution presents the work process and information requirements of an offshore service company. Suitable industry 4.0 technologies are identified to increase information transparency for the supply chain. In conjunction with a cooperative planning and control instrument, a reliable basis of decison-making for the execution of service assignments can be provided. This constitutes a direct contribution to a reduction of operation costs for offshore service logistics.

Finished vehicle logistics is of particular importance for the automotive industry, because it is the link between manufacturer and customers. If problems occur during the distribution of a car, it becomes visible to the customer, unless the problems can be solved during the following processes. Process interfaces between companies are frequently causing issues. That is why a survey was executed in order to identify those issues at the interfaces between car manufacturers and logistics service providers.

Guaranteeing the quality of products and processes within supply chains is essential. Nevertheless, quality management is still restricted to production processes while logistics processes are normally not considered. IT infrastructures for exchanging quality data are often missing. Those needs can be addressed by using sensor systems in combination with a cross company exchange of sensor data based on EPCIS. In order to realise this approach, sensor systems, the EPCIS standard, decision support systems and business models need to be further developed.

Optical systems are a popular choice for quality inspection because they are not only contactless and precise but also comparably fast. Particularly in cases where a 100% quality inspection is required low measurement and evaluation time is of essential importance. With high production rates of several parts per second, manual inspection is not feasible anymore and the evaluation needs to be automatically carried out by algorithms. In this article we propose a fast method for anomaly detection in image data based on principal component analysis and filtering. The method shows competitive performance on a data set of challenging surface inspection.

The comprehensive digitalization of work environment constitutes major challenges in connection with new media and an extended human-computer interaction. In this context, service and maintenance proved to be an important field of application for this form of Industry 4.0. An adequate process execution and documentation has to be secured, even under challenging conditions, e.g. malfunctions on short notice, harsh working conditions or tight timeframes. These requirements as well as the increasing digitalization promote the application of Augmented Reality solutions in this area. With a focus on maintenance of wind energy turbines, this article describes the state of the art in relation to current solution approaches and development needs in connection with a process-oriented application of Augmented Reality. Therefore, current solutions that are already on the market are considered as well as results of the joint research project “AR Maintenance System”.

The increasing customization of products, which leads to higher numbers of product variants with smaller lot sizes, requires a high flexibility of manufacturing systems. These systems are subject to dynamic influences and need increasing effort for the generation of the production schedules and for the control of the processes. This paper presents an approach that addresses these challenges. First, scheduling is done by coupling an optimization heuristic with a simulation model to handle complex and stochastic manufacturing systems. Second, the simulation model is continuously adapted by real-time data from the shop floor. If, e.g., a machine goes down or a rush order appears, the simulation model and consequently the scheduling model is updated and the optimization heuristic adjusts an existing schedule or generates a new one. This approach uses real-time data provided by future cyber-physical systems to integrate scheduling and control and to manage the dynamics of highly flexible ...