Elektronik und Informatik
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A Context and Augmented Reality BPMN and BPMS Extension for Industrial Internet of Things Processes
(2022)
In the context of Industry 4.0, smart factories enable a new level of highly individualized and very efficient production, driven by highly automated processes and connected Industrial Internet of Things (IIoT) devices. Yet the IIoT process context, crucial for operational process enactment, cannot be readily represented in processes as currently modeled. Despite automation progress, manual tasks performed by humans (such as maintenance) remain, and while complicated tasks can be supported by Augmented Reality (AR) devices, they remain insufficiently integrated into global production processes. To seamlessly integrate process automation, IIoT context, and AR, this paper contributes BPMN-CARX, a Context and Augmented Reality eXtension (CARX) for BPMN (Business Process Model and Notation) and the CARX Framework, which enables AR and IIoT context integration with existing Business Process Management Systems (BPMSs). An Industry 4.0 case study demonstrates its feasibility and applicability.
A Systematic Literature Review of Medical Chatbot Research from a Behavior Change Perspective
(2020)
Can one 3D print a laser?
(2020)
DEKXTROSE: An Education 4.0 Mobile Learning Approach and Object-Aware App Based on a Knowledge Nexus
(2020)
The exponential growth in knowledge coupled with the decreasing knowledge half-life creates a challenging situation for educational programs - particularly those preparing software engineers for their very dynamic high-technology field. Teachers in high technology education areas are challenged in selecting and making relevant knowledge intuitively accessible to students, especially with regard the highly dynamic digital and software technologies. This paper contributes a knowledge nexus-based multimedia approach aligned with Higher Education 4.0 for creating learning apps on mobile devices that support multiple didactic models, leverage intrinsic curiosity and motivation, support gamification, and enable digital collaboration. Object recognition is used to trigger learning paths, and various didactic methods are supported via workflow-like learning flows to support group or team-based learning. A prototype app was realized to demonstrate its feasibility and an empirical evaluation in software engineering shows the didactic potential and advantages of the approach, which can be readily generalized and applied to the arts, sciences, etc.
DEKXTROSE: An Education 4.0 Mobile Learning Approach and Object-Aware App Based on a Knowledge Nexus
(2020)
The exponential growth in knowledge coupled with the decreasing knowledge half-life creates a challenging situation for educational programs - particularly those preparing software engineers for their very dynamic high-technology field. Teachers in high technology education areas are challenged in selecting and making relevant knowledge intuitively accessible to students, especially with regard the highly dynamic digital and software technologies. This paper contributes a knowledge nexus-based multimedia approach aligned with Higher Education 4.0 for creating learning apps on mobile devices that support multiple didactic models, leverage intrinsic curiosity and motivation, support gamification, and enable digital collaboration. Object recognition is used to trigger learning paths, and various didactic methods are supported via workflow-like learning flows to support group or team-based learning. A prototype app was realized to demonstrate its feasibility and an empirical evaluation in software engineering shows the didactic potential and advantages of the approach, which can be readily generalized and applied to the arts, sciences, etc.
Design and Implementation of a Plug-In Repetitive Controller for a High Precision Axis System
(2021)
Software design patterns and the abstractions they offer can support developers and maintainers with program code comprehension. Yet manually-created pattern documentation within code or code-related assets, such as documents or models, can be unreliable, incomplete, and labor-intensive. While various Design Pattern Detection (DPD) techniques have been proposed, industrial adoption of automated DPD remains limited. This paper contributes a hybrid DPD solution approach that leverages a Bayesian network integrating developer expertise via rule-based micropatterns with our machine learning subsystem that utilizes graph embeddings. The prototype shows its feasibility, and the evaluation using three design patterns shows its potential for detecting both design patterns and variations.
Nowadays, businesses with focus on consumer-products are challenged by short production cycles, high pricing pressure, and the need to deliver new features and services in a regular interval. Currently, businesses are tackling these challenges by automating their business pro- cesses, while yet trying to be flexible by introducing methods for process variability modeling. However, for larger processes and variability models, it becomes difficult to consider, maintain, and optimize all process variations in the various execution contexts. In software development, highly agile requirements are usually tackled with a flexible microservice architecture. Nonetheless, the fast-changing service landscape is often not fully reflected in the underlying business processes, leading to inefficiency and loss of profit. With this work, we extend our framework for process variability modeling with concepts of Microflows, allowing agile business process modeling and orchestration while utilizing the full flexibility of underlying microservices. In addition, we present a case study, showing how this approach is used in the context of an IoT application
Improved Direct Power Control Applied to Parallel Active Filtering Based on Fuzzy Logic Controller
(2018)
Industry 4.0 production comprises complicated highly automated processes. However, human activities are also a crucial component of these processes, e.g., for machine main- tenance. Task assignment of human resources in this domain is challenging, as many factors have to be taken into account to ensure effective and efficient activity execution and satisfy special conditions (like worker safety). To overcome the limita- tions of current Business Process Management (BPM) Systems regarding activity resource assignment, this contribution provides a BPM-integrated approach that applies fuzzy sets for activity assignment. Our findings suggest that this approach can be easily applied to complex production scenarios, while providing efficient performance even with a large number of concurrent activity assignment requests. Additionally, our evaluation shows its potential for improved work distribution which can lead to cost savings in Industry 4.0 production processes.
Learning for E-Learning
(2020)
Leveraging Augmented Reality to Support Context-Aware Tasks in Alignment with Business Processes
(2021)
The seamless inclusion of Augmented Reality (AR) with Business Process Management Systems (BPMSs) for Smart Factory and Industry 4.0 processes remains a challenge. Towards this end, this paper contributes an approach integrating context-aware AR into intelligent business processes to support and guide manufacturing personnel tasks and enable live task assignment optimization and support task execution quality. Our realization extends two BPMSs (Camunda and AristaFlow) and various AR devices. Various AR capabilities are demonstrated via a simulated industrial case study.
Linking Intrusion Detection System Information and System Model to Redesign Security Architecture
(2020)
Additive manufacturing of optical elements out of polymer allow new design concepts for optics. The parts are built up layer by layer. Unlike polymer binding with glass particles with its sintering process no secondary step is necessary for polymer printing to create the final part. With more and more printers and transparent materials available, this technology becomes more and more relevant for prototyping or custom optics. Therefor a deep understanding of the optical effects in the part is desirable. Key property of optical elements is the refractive index. The materials for polymer printing are most commonly resins that cure under UV-exposure and show lower refractive indices in liquid phase than cured. Assuming a dependency of the refractive index on the grade of polymerization and therefor the UV-exposure, the layering process of additive manufacturing causes variations of the refractive index within the part. Using the Scanning Focused Refractive Index Microscopy, the distribution of the refractive index within and between the layers is analyzed. The analysis includes comparisons between raw parts after printing and parts after UV post curing. Additionally, layer free samples from a Continuous Liquid Interface Printing System are examined for the homogeneity of the refractive index distribution. The purpose of the presentation is to give a detailed insight into the optical effects occurring at the layer interfaces of elements created by additive manufacturing. Possible use cases of the refractive index distributions within the part are also discussed.