Refine
Year of publication
- 2020 (66) (remove)
Document type
- Conference Proceeding (66) (remove)
Has full text
- No (66)
Keywords
- Industry 4.0 (5)
- Machine learning (5)
- Poster (3)
- Assembly line (2)
- Blockchain (2)
- Force amplification mechanisms (2)
- Human factors (2)
- Human-robot collaboration (2)
- Manufacturing (2)
- Piezoelectric actuator (2)
- Reference model (2)
- Selective laser melting (2)
- Smart contracts (2)
- Virtual reality (2)
- 2D (1)
- 3D (1)
- ABE (1)
- AR work instruction (1)
- Ablation depth (1)
- Acceptance (1)
- Accessibility (1)
- Acute respiratory distress syndrome (1)
- Additive manufacturing (1)
- Anomalieerkennung (1)
- Anomalous behaviour (1)
- Anomaly detection (1)
- Asset value (1)
- Atmospheric measurements (1)
- Atomic layer deposition (1)
- Attribute-based encryption (1)
- Augmentation (1)
- BPM body of knowledge (1)
- Belts (1)
- Business process management (1)
- COVID-19 pneumonia (1)
- Cancer (1)
- Care sector (1)
- Characters (1)
- Circular groove (1)
- Cloud computing environment (1)
- Cognitive disabilities (1)
- Coils (1)
- Constitutional undercooling (1)
- Container (1)
- Container virtualization (1)
- Context-Awareness (1)
- Convolutional generative adversarial network (1)
- Convolutional neural network (1)
- Corrosion (1)
- Current measurement (1)
- Current transformers (1)
- DHT (1)
- Data science (1)
- Dataset (1)
- Digital divide (1)
- Digitized agreements (1)
- Distributed data validation network (1)
- Docker (1)
- Education technology (1)
- Electrical impedance tomography (1)
- Electrostatic actuator (1)
- Electrostatic inchworm (1)
- Endoscopic video (1)
- Engineering asset management (1)
- Event detection (1)
- Evidential clustering (1)
- Exploratory approach (1)
- Feature extraction (1)
- Finite difference time domain (FDTD) (1)
- Formative measurement model (1)
- Health care (1)
- Huang-Hilbert transform (1)
- Image classification (1)
- Inchworm motor (1)
- Intellectual disabilities (1)
- IoT (1)
- Knowledge improvement (1)
- LSTM (1)
- Laser (1)
- Laser focus point (1)
- Lung nodule (1)
- Maintenance (1)
- Maschinelles Lernen (1)
- Mass spectrometry (1)
- Medical devices (1)
- Mental workload (1)
- Microstructure (1)
- Microwave imaging (1)
- Mixed-methods (1)
- Monitoring (1)
- Multiple degree of freedom actuator (1)
- NILM (1)
- Neural network (1)
- Neuronale Netze (1)
- Nonintrusive load monitoring (1)
- Ontologies (1)
- Optical fiber sensors (1)
- Optical fibers (1)
- Optical sensors (1)
- P2P (1)
- P2P communication (1)
- Participative change management (1)
- Particle measurements (1)
- Performance evaluation (1)
- Picosecond laser single point ablation (1)
- Polyimides (1)
- Potentiodynamic polarization (1)
- Power engineering (1)
- Predictive maintenance (1)
- Presence (1)
- Privacy preserving communication (1)
- Privacy protection (1)
- Product development (1)
- Quality control (1)
- Quantitative & qualitative methods (1)
- Requirements (1)
- Research design (1)
- Research discourses (1)
- Resource Discovery (1)
- SWRL rules (1)
- Security monitoring (1)
- Sensor fusion (1)
- Service technician (1)
- Si3N4 (1)
- Silicon (1)
- Simulation (1)
- Smart grid (1)
- Smart meter (1)
- Sociotechnical system (1)
- Spontaneous breathing (1)
- Steel surface damage (1)
- Stick slip motor (1)
- Substrates (1)
- Surface treatment (1)
- Surgical tool detection (1)
- System call tracing (1)
- Thermodynamics (1)
- Thorax (1)
- Tidal volume measurement (1)
- Time constant (1)
- Titanium alloys (1)
- Touch user interface (1)
- Touchless user interface (1)
- Trend analysis (1)
- Ultra-wideband (UWB) (1)
- Uncanny valley (1)
- Under-water laser-machining (1)
- User experience (1)
- Validierung Medizinprodukte (1)
- Voice user interface (1)
- Vortrag (1)
- Wearables (1)
- Working environment (1)
- mHealth (1)
The digital transformation of companies is expected to increase the digital interconnection between different companies to develop optimized, customized, hybrid business models. These cross-company business models require secure, reliable, and traceable logging and monitoring of contractually agreed information sharing between machine tools, operators, and service providers. This paper discusses how the major requirements for building hybrid business models can be tackled by the blockchain for building a chain of trust and smart contracts for digitized contracts. A machine maintenance use case is used to discuss the readiness of smart contracts for the automation of workflows defined in contracts. Furthermore, it is shown that the number of failures is significantly improved by using these contracts and a blockchain.
Machine learning applications, like machine condition monitoring, predictive maintenance, and others, become a state of the art in Industry 4.0. One of many machine learning algorithms are decision trees for the decision-making process. A new approach for creating distributed decision trees, called node based parallelization, is presented. It allows data to be classified through a network of industrial devices. Each industrial device is responsible for a single classification rule. Also, nodes that react incorrectly, for example, due to an attack, are taken into account using a variety of methods to remain the decision-making process correct and robust.
Corrosion is a process that needs to be viewed carefully in context with the examined metals or alloys as well as the ambient conditions (e.g. electrolyte composition). Additive manufacturing processes with their formation a of microscale melt and rapid solidification of that melt can lead to microstructures that can differ extremely from conventional manufacturing processes in terms of their homogeneity and distribution of (alloying) elements. Therefore, process–related local inclusions can be formed with higher amounts of certain alloying elements than their surroundings which result in different chemical potentials. Corrosion experiments performed with additive manufactured parts (e.g. made of pure titanium or titanium alloys) show the release of potentially unwanted alloy constituents, which in turn can affect the long–term behavior of the part negatively. As part of the investigations it is shown what kind of influence the additive manufacturing process can have on such built parts and how subsequently applied treatments like machining or heat treatment can alter the properties of the material and produced component. Different methods like metallography or potentiodynamic polarization with subsequent mass spectrometric analyses were eventually performed to investigate the mentioned material properties and behaviour.
Investigation of Long-Term Stability of Hybrid Systems-in-Foil (HySiF) for Biomedical Applications
(2020)
Additive Manufacturing is a highly innovative and pioneering process that offers among others a high degree of flexibility and complexity in terms of the part design or the possibility to integrate various functions in a single part. Therefore, it possesses great chances to establish itself as a significant method within the entire field of manufacturing processes in the near future. The used materials and their thermodynamic behavior determine the resulting properties of parts built in this way, but also by the generated microstructure. Regarding the whole process with its formation of a microscale melt and ongoing rapid solidification a variety of different microstructures can be created, which in turn can affect the mechanical as well as chemical properties and the long–term behavior to a great extent. Furthermore, it can be seen that different metals and alloys in combination with the process conditions can result in different and/or fluctuating qualities of the manufactured components. Nonetheless, additive manufacturing can lead to a noticeably enhancement of materials or products that were manufactured and processed with traditional methods so far and open new possibilities and perspectives in the research and development sector. However, this means that it is crucial to adapt currently used tests and methods to the new properties and manufacturing process.