Autor: Michael Lütjen

The complex dynamics of block warehouses pose major challenges to the manual stocktaking process. Frequent relocation of pallets, crates or pallet cages without fixed storage locations leads to a time-consuming and error-prone inventory process, wherein goods often have to be searched for and damages due to improper storage can occur. The use of (semi-)autonomous drones offers a promising solution to enable automated stocktaking, especially if these are appropriately equipped for optical goods detection.

Digital twins are an important part of the Industry 4.0 idea. They mirror physical goods in the digital world and enhance them with additional capabilities and functions for analysis, forecasting and decisionmaking. This paper contributes to the classification and assessment of Digital Twins using a multidimensional maturity model. The presented method "DT-Assess" enables an application-specific assessment of Digital Twins. The developed maturity model consists of seven categories with a total of 31 characteristics to be evaluated. The systematic evaluation in five application scenarios allows, for the first time, a classification of the respective "digital twin" implementation or concept with the aim of identifying further development options and weaknesses.

The COVID-19 pandemic has highlighted the additional challenges that events face in terms of appropriate crowd management. This paper is dedicated analyzing these challenges and existing approaches for the safe operation of events during pandemics. Based on this, an innovative framework is presented that uses intelligent crowd analysis and is applicable to an environment with volatile groups. In addition, the specifiv use case of trade fair events is considered in this framework.

3D printing has established itself as a production process and has also found its way into the fashion industry. Individualised shoes can be 3D printed, but this poses significant challenges for automated quality control, as defects are rare. Autoencoders enable to train a system with defect-free data so that detected deviations from this state can be evaluated as defects. Our research shows a ROC AUC score of 0.87, proving that this method is suitable for anomaly detection in 3D-printed shoes.

The use of LNG propulsion in ships has significant environmental benefits but also creates chal- lenges in handling. Due to safety regulations, the maintenance of the LNG ship systems requires a high degree of reliability and accuracy. Thus, this paper deals with the development and evaluation of an AR-assistance system. The system based on an Android smartphone enables users to access maintenance instructions and manuals and supports the work process step by step through context-sensitive virtualizations. Its evaluation was conducted as a combined quantitative and qualitative user study.

The food production process and raw material specific parameters significantly influence the quality of the final product. Furthermore, for products with several ingredients, complex parameter effects occur. This complexity causes the desire for a production control that considers these effects and orientates on final product quality. This article describes the state of the art and derives requirements form a case study in a delicatessen food production system. In summary, this paper presents a concept for production control with special consideration of the final product quality for the production of delicatessen salads.

The digital twin is well on the way to becoming an elementary part of the corporate world. Corporate leaders hope that these intelligent images of an increasingly dynamic corporate reality will significantly reduce complexity. Ideally, model-based analyses and (partially) automated decisions using methods of simulation technology and artificial intelligence based on optimized IoT data management can make their contribution to corporate agility. In addition to the definition of terms/concepts, the paper will discuss current challenges and present various examples of their application. Based on these ideas, a process model for the introduction of digital twins in terms of technology migration will be presented.

The food distribution of (deep) refrigerated goods is a steadily growing market segment that deals with sustainability in particular. Due to the high efficiency of the CEP service providers, a shipment as such is not necessarily worse than a shopping trip by car over several kilometers in town. A concrete approach to improve ecological sustainability in food delivery is the substitution of existing PE plastic bags filled with dry ice. The bags help to keep the dry ice together and protect the customer from burns. The following article analyzes ecological aspects of food shipment and conveys an understanding of current development concerning biodegradable plastic films. Due to special material properties of bio-based plastic films, the manufacturability of dry ice bags was investigated in a series of experiments. Dry ice bags were manufactured by means of the very precisely adjustable joining technology ultrasonic welding. Subsequent, load capacity of the dry ice bags was examined.

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.

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.