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Integrating artificial intelligence (AI) into decision-making processes is key to improving organizational performance. However, trust in AI-based decision support systems (DSSs), similar to other information systems, is important for successful integration. A disruptive phenomenon, “algorithm aversion”, can impede AI trust and, thus, acceptance. Although AI recommendations outperform human recommendations in different decision-making fields, individuals underweight recommendations from AI-based DSSs compared to human decision-makers due to a lack of AI trust. We conducted a lab experiment to investigate the role of AI recommendations in workplace-related tasks, first focusing on the mediating effect of AI trust and the negative impact of algorithm aversion on decision-making performance and the moderating effect of technical competence. Second, we analyzed the ability of gamification to reduce this phenomenon. We provide evidence regarding how to enhance decision-making performance when AI recommendations are deployed and identify countermeasures against algorithm aversion to facilitate the adoption of AI-based DSSs.
Modellierung des Antriebsstrangs einer Textilmaschine zum Zweck der modellbasierten Steuerung
(2024)
Zur Produktion von gewirkten Textilien werden mehrere Nadeln auf eine Legebarre gesetzt, die durch Servoantriebe positioniert werden. Aufgrund der erzwungenen Bewegung kann der Antriebsstrang bei hohen Drehzahlen zur Schwingung angeregt werden. Die richtige Wahl der Steuerkurven ist daher eine sehr wichtige und anspruchsvolle Aufgabe, die durch ein Antriebsstrangmodell unterstützt werden soll. Dafür wird am Beispiel eines Teststands ein Modell des Antriebsstranges in MATLAB/Simulink® entwickelt. Für das Antriebsstrangmodell müssen eine geeignete Modellordnung und Modellparameter gewählt werden. Die unbekannten Modellparameter werden durch eine Parameteridentifikation ermittelt. Mit einer Validierung wird ein geeignetes Anregungsspektrum für die Bestimmung der Modellordnung und die Parameteridentifikation ermittelt.
Krisen gab es schon immer. Aktuell hat sich jedoch ein ganzes Spektrum an Krisen entfaltet – es gibt politische und militärische Krisen, es brechen Energiemärke und Lieferketten weg, wir sehen ganze Branchen gefährdet, auch die Gesundheit macht uns Sorgen, vom Klimawandel ganz zu schweigen. In den Veranstaltungen der Ringvorlesung „Krisen und Auswege“, die im Wintersemester 2022/2023 stattfand, wurden Phänomene, Konzepte und Lösungen aus vielfältiger Perspektive erschlossen und damit die Komplexität des Gegenstands aufgezeigt. Herausforderungen für Unternehmen und Privatpersonen wurden identifiziert sowie der Einfluss auf technologische und organisatorische Entwicklungswege dargelegt.
In dieser Publikation wurden die einzelnen Vorträge der Ringvorlesung von den Autorinnen zusammengefasst.
Im Sommer des Jahres 2022 hatte der Bayerische Landtag das neue Hochschulinnovationsgesetz (BayHIG) verabschiedet. Darin ist erstmals der Wissenstransfer als die dritte, neue Säule der Hochschulaufgaben enthalten.
Tatsächlich hat sich das IMI bereits seit 15 Jahren dem Wissenstransfer Hochschule - Wirtschaft verschrieben und zahlreiche Projekte mit unterschiedlichem Fokus erfolgreich durchgeführt. In der vorliegenden Publikation werden die bearbeiteten Themen im Wissenstransfer, die zahlreichen verschiedenen Veranstaltungsformate sowie die Drittmittelprojekte beleuchtet.
Der technische Fortschritt von IT-Systemen, wie zum Beispiel der sogenannten „Künstlichen Intelligenz“ (KI) oder den „Common Data Spaces“ (CDSs), bringt die Frage nach der Akzeptanz dieser Systeme mit sich. Sowohl die aktive (ökonomische) Akzeptanz in Form des Erwerbs und der Nutzung, als auch die passive (soziale) Akzeptanz in Form der Duldung der aktiven Nutzung durch Dritte, sind für den Erfolg von IT-Systemen ausschlaggebend. Eine geringe Akzeptanz der Systeme und ein mangelndes Vertrauen in dieselben wird in einen Zusammenhang gebracht: Man fragt nach der Gestaltung „zuverlässiger und vertrauenswürdiger Systeme“, da diese besonders akzeptiert werden.
In diesem Beitrag werden „Vertrauen“ und dessen Zusammenhang mit „Zuverlässigkeit“ und „Verstehen“ im Kontext von IT-Systemen erörtert.
We report on laser drilling borehole arrays using ultrashort pulsed lasers with a particular focus on reducing the inadvertent heat accumulation across the workpiece by optimizing the drilling sequence. For the optimization, evolutionary algorithms are used and their results are verified by thermal simulation using Comsol and experimentally evaluated using a thermal imaging camera. To enhance process efficiency in terms of boreholes drilled per second, multi-spot approaches are employed using a spatial light modulator. However, as higher temperatures occur across the workpiece when using simultaneous multi-spot drilling as compared to a single-spot process, a subtle spatial distribution and sequence of the multi-spot approach has to be selected in order to limit the
resulting local heat input over the processing time. Different optimization approaches based on evolutionary algorithms aid to select those drilling sequences which allow for the combination of a high efficiency of multi-spot profiles, a low-generated process temperature and a high-component quality. In particular, using a 4 x 4 laser spot array allows for the drilling of 40,000 boreholes in less than 76 s (526 boreholes/s) with a reduced temperature increase by about 35%, as compared to a single spot process when employing an optimized drilling sequence.
Multi-Bessel Beams Generated by an Axicon and a Spatial Light Modulator for Drilling Applications
(2023)
We report on an optical setup to generate multi-Bessel beam profiles combining a refractive axicon and a spatial light modulator. Based on their particular beam profile, Bessel beams offer advantageous properties for micro drilling processes and internal volume processing, especially for transparent materials. In addition, the laser power of industrial, ultrashort pulsed lasers has increased significantly over the last few years, offering the possibility for highly efficient processes using multi-spot profiles. Our optical concept combines the dynamic possibilities of beam splitting using a spatial light modulator with the benefits of Bessel beams, which facilitates multi-Bessel beam processing. Beside the simulation and experimental evaluation of the generated multi-Bessel beams, we exemplify the applicability of the developed module for the perforation of thin metal foils by micro drilling.
We report on a comprehensive study of the mechanical properties of maraging steel
body-centred cubic lattice structures fabricated by a hybrid additive manufacturing technology that combines laser powder bed fusion with in situ high-speed milling. As the mechanical properties of additive manufactured components are inferior to, e.g., cast components, surface modifications can improve the mechanical behaviour. Different hybrid additive manufacturing technologies have been designed using additive and subtractive processes, improving process quality. Following this, mechanical testing is performed with respect to static tensile properties and dynamic stress, hardness, and porosity, comparing specimens manufactured by laser powder bed fusion only to those manufactured by the hybrid approach. In addition, the influence of different heat-treatment techniques on the mechanical behaviour of the lattice structures is investigated, namely solution and aging treatment as well as hot isostatic pressing. Thus, the influence of the superior surface quality due to the hybrid approach is evaluated, leading to, e.g., an offset of about 14–16% for the static testing of HIP lattice structures. Furthermore, the dynamic load behaviour can be improved with a finished surface, heading to a shift of the different zones of fatigue behaviour in the testing of hybrid-built specimens.
Axicon generated Bessel beams are a popular tool for high aspect ratio precision laser drilling. Spot diameter and working distance are given by the geometric parameters of the axicon and the wavelength used. Thus, it is difficult to manipulate the beam shape of a Bessel beam for a given setup. Spatial light modulators (SLMs) overcome limitations in flexibility. However, due to the limited phase shift of SLMs, only Bessel beams with flat cone angles and large focal length can be generated. In this contribution, an approach for generating Bessel beams with a shorter, but tunable focal length is presented. A physical axicon was combined with an SLM. A holographic image of a negative axicon is put on the SLM to generate a ring beam, which is focused by a subsequent physical axicon to get a small focal diameter. Thus, different sized high aspect ratio micro holes can be drilled without using any moving components.
In recent years, the demand for sustainable and degradable materials and electronic devices has increased significantly.
Among a range of biodegradable polymers, poly(lactic acid) (PLA) is a good alternative to conventional petrol-based polymers because of its attractive mechanical properties and its easy processability. Recently, PLA has also been described as a promising dielectric material with piezoelectric and electret properties. We expect that PLA—after further optimization— will play an important role as a material for environmentally friendly sensors in the future, where first applications such as air filters and pressure sensors have already been proposed. However, degradation under normal ambient conditions is very slow, and an accelerated and controllable degradation process is highly desirable for any type of PLA-based sensors.
Enzymatic hydrolysis with embedded enzymes has been proposed as an approach to accelerate and control degradation. In this work, we investigate the properties of PLA in terms of dielectric and mechanical properties with a focus on its ability to store charges after the enzyme proteinase K (Trit. album) has been incorporated. Results reveal that proteinase K has a positive effect on the charge stability of solvent-cast PLA electrets after complete evaporation of the solvent. Furthermore, we observed a concentration-dependent acceleration of mass loss in a Tris-HCl buffer. A fast degradation within only one day occurred at a concentration of 6 wt% proteinase K.
Two different control concepts for the automatic track guidance of forklifts are
proposed. Both approaches are based on Reinforcement Learning (RL), a method of Artificial
Intelligence (AI), and are able to take into account time-variant parameters, such as the vehicle velocity, and to reduce the influence of the path curvature, the most important disturbance variable of lateral vehicle control. In the first approach, both, the path curvature and the vehicle velocity signal, are provided to the controller in addition to the state variables of the controlled system. By varying the corresponding parameters in the training process, both signals can be considered and the control parameters can be optimized accordingly. In the second approach, several controllers (multi-model concept) considering the path curvature are used and the varying vehicle velocity is taken into account using a gain-scheduling concept. Considering time-variant vehicle parameters and the influence of the disturbance variable during operation, a stable track guidance is guaranteed within the whole speed range of the industrial trucks.
Rechtswidrigkeit einer Vorkaufssatzung zur Sicherung städtebaulicher Entwicklung, Urteilsbesprechung
(2000)
Schuldrecht BT
(2022)
BGB AT
(2023)
Schuldrecht AT
(2023)