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The use of augmented reality (AR) in outbound logistics is associated with potentially strong stimuli for cost savings and throughput time. Nevertheless, the benefits of AR compared to conventional methods require a holistic analysis for investment decision making. Until now, research has only assessed case-study-related potentials and selected aspects of the technology. This paper answers the following research questions: How can the economic efficiency of AR in the packing process be quantified by utilizing a holistic model of value drivers? How can AR be technically implemented for packing processes in outbound logistics? What economic profit results from the use of AR technology in a case company’s packing process?
The presented model enables the investment decision to be supported based on economic value added (EVA), thereby providing an assessment of value drivers in packing systems. Cost drivers are identified on the basis of the Supply Chain Operations Reference (SCOR) process model. The technical and economic validation of the model was carried out by means of an empirical study: Expert interviews were conducted for validating the model elements. Data collection by a prototype at a mechanical-engineering company was used to calculate the value contribution. The mapping of cause-effect relationships within the framework of EVA driver trees has proven itself in both the expert interviews and the prototype validation. The field experiment at the case company demonstrated a positive value contribution of AR, in particular regarding employee productivity, length and variance of throughput time, quality aspects, volume utilization, and quantity of packing material used.
Adaptive laser resonators with deformable MOEMS mirrors under closed-loop control are discussed and experimental results are presented. The requirements for deformable mirrors and for closed-loop control systems of these mirrors are analyzed. Several deformable mirrors have been characterized and the results are presented. Currently available membrane mirrors deform under laser load and need further development before they can be used for aberration correction of solid state lasers above some tens of Watts. Nevertheless, the results are encouraging and the requirements are within reach of currently available technology. Finally, we demonstrate an Nd.YVO4-laser with a closed-loop adaptive resonator and more than 6 W of output power. The closed-loop system was able to compensate artificially introduced aberrations from a phase plate.
Gazelle: Ganzheitliche Regelung von Biogasanlagen zur Flexibilisierung und energetischen Optimierung
(2021)
Background: Modern healthcare devices can be connected to computer networks and many western healthcareinstitutions run those devices in networks. At the same time, cyber attacks are on the rise and there is evidence thatcybercriminals do not spare critical infrastructure such as major hospitals, even if they endanger patients. Intuitively,the more and closer connected healthcare devices are to public networks, the higher the risk of getting attacked.
Methods: To asses the current connectivity status of healthcare devices, we surveyed the field of German hospitalsand especially University Medical Center UMCs.
Results: The results show a strong correlation between the networking degree and the number of medical devices.The average number of medical devices is 25.150, with a median of networked medical devices of 3.600. Actual keyusers of networked medical devices are the departments Radiology, Intensive Care, Radio-Oncology RO, NuclearMedicine NUC, and Anaesthesiology in the group of UMCs. In the next five years, the usage of networked medicaldevices will increase significantly in the departments of Surgery, Intensive Care, and Radiology. We detected a strongcorrelation between the degree of connectivity and the likelihood of being attacked.The survey answers regarding the cyber security status reveal a lack of security basics in some of the inquiredhospitals. We did discover successful attacks in hospitals with separated or subsidiary departments. A fusion ofcompetencies on an organizational level facilitates the right behavior here. Most hospitals rated themselvespredominantly positively in the self-assessment but also stated the usefulness of IT security insurance.Conclusions:Concluding our results, hospitals are already facing the consequences of omitted measures within theirgrowing pool of medical devices. Continuously relying on historically grown structures without adaption and trustingmanufactures to solve vectors is a critical behavior that could seriously endanger patients.
In-depth analysis of customer journeys to broaden the understanding of customer behaviors and expectations in order to improve the customer experience is considered highly relevant in modern business practices. Recent studies predominantly focus on retrospective analysis of customer data, whereas more forward-directed concepts, namely predictions, are rarely addressed. Additionally, the integration of robotic process automation (RPA) to potentially increase the efficiency of customer journey analysis is not discussed in the current field of research. To fill this research gap, this paper introduces “customer journey mining”. Process mining techniques are applied to leverage digital customer data for accurate prediction of customer movements through individual journeys, creating valuable insights for improving the customer experience. Striving for improved efficiency, the potential interplay of RPA and customer journey mining is examined accordingly. The research methodology followed is based on a design science research process. An initially defined customer journey mining artifact is operationalized through an illustrative case study. This operationalization is achieved by analyzing a log file of an online travel agency functioning as an orientation for researchers and practitioners while also evaluating the initially defined framework. The data is used to train seven distinct prediction models to forecast the touchpoint a customer is most likely to visit next. Gradient-boosted trees yield the highest prediction accuracy with 43.1%. The findings further indicate technical suitability for RPA implementation, while financial viability is unlikely.
Camera based path planning for low quantity - high variant manufacturing with industrial robots
(2019)
The acquisition costs for industrial robots have been steadily decreasing in past years. Nevertheless, they still face significant drawbacks in the required effort for the preparation of complex robot tasks which causes these systems to be rarely present so far in small and medium-sized enterprises (SME) that focus mainly on small volume, high variant manufacturing. In this paper, we propose a camera-based path planning framework that allows the fast preparation and execution of robot tasks in dynamic environments which leads to less planning overhead, fast program generation and reduced cost and hence overcomes the major impediments for the usage of industrial robots for automation in SMEs with focus on low volume and high variant manufacturing. The framework resolves existing problems in different steps. The exact position and orientation of the workpiece are determined from a 3D environment model scanned by an optical sensor. The so retrieved information is used to plan a collision-free path that meets the boundary conditions of the specific robot task. Experiments show the potential and effectiveness of the the framework presented here by evaluating a case study.
Biogas Benchmark Münsterland
(2019)