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Analysis of Big Data Streams to obtain Braking Reliability Information for Train Protection systems
(2017)
The first and last mile of a railway journey, in both freight and transit applications, constitutes a high effort and is either non-productive (e.g. in the case of depot operations) or highly inefficient (e.g. in industrial railways). These parts are typically managed on-sight, i.e. with no signalling and train protection systems ensuring the freedom of movement. This is possible due to the rather short braking distances of individual vehicles and shunting consists. The present article analyses the braking behaviour of such shunting units. For this purpose, a dedicated model is developed. It is calibrated on published results of brake tests and validated against a high-definition model for low-speed applications. Based on this model, multiple simulations are executed to obtain a Monte Carlo simulation of the resulting braking distances. Based on the distribution properties and established safety levels, the risk of exceeding certain braking distances is evaluated and maximum braking distances are derived. Together with certain parameters of the system, these can serve in the design and safety assessment of driver assistance systems and automation of these processes.
This study reviews the practice of brake tests in freight railways, which is time consuming and not suitable to detect certain failure types. Public incident reports are analysed to derive a reasonable brake test hardware and communication architecture, which aims to provide automatic brake tests at lower cost than current solutions. The proposed solutions relies exclusively on brake pipe and brake cylinder pressure sensors, a brake release position switch as well as radio communication via standard protocols. The approach is embedded in the Wagon 4.0 concept, which is a holistic approach to a smart freight wagon. The reduction of manual processes yields a strong incentive due to high savings in manual
labour and increased productivity.
Rare event simulation to optimise maintenance intervals of safety critical redundant subsystems
(2018)
Towards inclusion of the freight rail system in the industrial internet of things - Wagon 4.0
(2017)
As researchers continue to seek the expansion of the material base for additive manufacturing, there is a need to focus attention on the Ni–Cu group of alloys which conventionally has wide industrial applications. In this work, the G-NiCu30Nb casting alloy, a variant of the Monel family of alloys with Nb and high Si content is, for the first time, processed via the laser powder bed fusion process (LPBF). Being novel to the LPBF processes, optimum LPBF parameters were determined, and hardness and tensile tests were performed in as-built conditions and after heat treatment at 1000 °C. Microstructures of the as-cast and the as-built condition were compared. Highly dense samples (99.8% density) were achieved after varying hatch distance (80 µm and 140 µm) with scanning speed (550 mm/s–1500 mm/s). There was no significant difference in microhardness between varied hatch distance print sets. Microhardness of the as-built condition (247 HV0.2) exceeded the as-cast microhardness (179 HV0.2.). Tensile specimens built in vertical (V) and horizontal (H) orientations revealed degrees of anisotropy and were superior to conventionally reported figures. Post heat treatment increased ductility from 20% to 31% (V), as well as from 16% to 25% (H), while ultimate tensile strength (UTS) and yield strength (YS) were considerably reduced.
The laser beam-submerged arc hybrid welding method originates from the knowledge that, with increasing penetration depth, the laser beam process has a tendency to pore formation in the lower weld regions. The coupling with the energy-efficient submerged-arc process improves degassing and reduces the tendency to pore formation. The high deposition rate of the SA process in combination with the laser beam process offers, providing the appropriate choice of weld preparation, the possibility of welding plates with a thickness larger than 20° mm in a single pass, and also of welding thicker plates with the double-sided single pass technique.
Electron beam plasma measurement was realised by means of DIABEAM system invented by ISF RWTH Aachen. The Langmuir probe method is used for measurement. The relative simplicity of the method and the possibility of dispersion of high power on the probe allow its application for the investigation of high-power electron beams. The key element of the method is a rotating thin tungsten wire, which intersects the beam transversely on its axis and collects part of the current by itself. The signals, which are registered in the DIABEAM as a voltage, were taken in the form of amplitude. The conversion of the probe current into the distribution along the beam radius was realised using the Abel’s method. A voltage-current characteristic was built for the beam current. The local electron density as well as the electron temperature, the floating potential and the plasma potential were measured and calculated by means of this characteristic.
Bead-on-plate butt joints of 2.5 mm hot rolled DP600/DP600 and 1.2 mm cold rolled TRIP700/TRIP700 steel sheets were performed using 6 kW CO2 laser beam welding. The welding speed ranged from 1.5 to 3.0 and from 2.1 to 3.9 m/min in DP/DP and TRIP/TRIP steel weldments respectively. A top surface helium gas was used as a shielding gas at a flow rate of 20 l/min. Metallographic examinations and transverse tensile testing (DIN EN 895: 1995) were carried out to characterize the weldments. The formability of base metals and weldments were investigated by standard Erichsen test (DIN EN ISO 20482). It was found that the uniaxial plastic behavior of both DP600 and TRIP700 base metals was in agreement with Swift and modified Mecking–Kocks models respectively. In a perpendicular tensile test to the weld line, all specimens were fractured at the base metal however the strengths were somewhat higher than those of base metal. There was a significant reduction in formability caused by welding of both DP/DP and TRIP/TRIP steel weldments and the formability has been improved with the increase of the welding speed.
Shielding gas influences on laser weldability of tailored blanks of advanced automotive steels
(2010)
The effects of shielding gas types and flow rates on CO2 laser weldability of DP600/TRIP700 steel sheets were studied in this work. The evaluated shielding gases were helium (He), argon (Ar) and different mixtures of He and Ar. Weld penetration, tensile strength and formability (Erichsen test) of laser welds were found to be strongly dependent upon the shielding gas types. The ability of shielding gas in removing plasma plume and thus increasing weld penetration is believed to be closely related to ionization potential and atomic weight which determine the period of plasma formation and disappearance. It was found that the higher helium shielding gas flow rate, the deeper weld penetration and the lower weld width.
Numerical and experimental investigation of tensile behavior of laser beam welded TRIP700 steel
(2011)
In this research work, a statistical analysis of the CO2 laser beam welding of dual phase (DP600)/transformation induced plasticity (TRIP700) steel sheets was done using response surface methodology. The analysis considered the effect of laser power (2–2.2 kW), welding speed (40–50 mm/s) and focus position (−1 to 0 mm) on the heat input, the weld bead geometry, uniaxial tensile strength, formability limited dome height and welding operation cost. The experimental design was based on Box–Behnken design using linear and quadratic polynomial equations for predicting the mathematical models. The results indicate that the proposed models predict the responses adequately within the limits of welding parameters being used and the welding speed is the most significant parameter during the welding process.
Generally, the quality of a weld joint is directly influenced by the welding input parameter settings. Selection of proper process parameters is important to obtain the desired weld bead profile and quality. In this research work, numerical and graphical optimization techniques of the CO2 laser beam welding of dual phase (DP600)/transformation induced plasticity (TRIP700) steel sheets were carried out using response surface methodology (RSM) based on Box–Behnken design. The procedure was established to improve the weld quality, increase the productivity and minimize the total operation cost by considering the welding parameters range of laser power (2–2.2 kW), welding speed (40–50 mm/s) and focus position (−1 to 0 mm). It was found that, RSM can be considered as a powerful tool in experimental welding optimization, even when the experimenter does not have a model for the process. Strong, efficient and low cost weld joints could be achieved using the optimum welding conditions.
The aim of this work was to perform a detailed investigation of the use of Selective Laser Melting (SLM) technology to process eutectic silver-copper alloy Ag 28 wt. % Cu (also called AgCu28). The processing occurred with a Realizer SLM 50 desktop machine. The powder analysis (SEM-topography, EDX, particle distribution) was reported as well as the absorption rates for the near-infrared (NIR) spectrum. Microscope imaging showed the surface topography of the manufactured parts. Furthermore, microsections were conducted for the analysis of porosity. The Design of Experiments approach used the response surface method in order to model the statistical relationship between laser power, spot distance and pulse time.
We present a new Min-Max theorem for an optimization problem closely connected to matchings and vertex covers in balanced hypergraphs. The result generalizes Kőnig’s Theorem (Berge and Las Vergnas in Ann N Y Acad Sci 175:32–40, 1970; Fulkerson et al. in Math Progr Study 1:120–132, 1974) and Hall’s Theorem (Conforti et al. in Combinatorica 16:325–329, 1996) for balanced hypergraphs.
The potential of SMART climbing robot combined with a weatherproof cabin for rotor blade maintenance
(2016)
This paper presents the laser-based powder bed fusion (L-PBF) using various glass powders (borosilicate and quartz glass). Compared to metals, these require adapted process strategies. First, the glass powders were characterized with regard to their material properties and their processability in the powder bed. This was followed by investigations of the melting behavior of the glass powders with different laser wavelengths (10.6 µm, 1070 nm). In particular, the experimental setup of a CO2 laser was adapted for the processing of glass powder. An experimental setup with integrated coaxial temperature measurement/control and an inductively heatable build platform was created. This allowed the L-PBF process to be carried out at the transformation temperature of the glasses. Furthermore, the component’s material quality was analyzed on three-dimensional test specimen with regard to porosity, roughness, density and geometrical accuracy in order to evaluate the developed L-PBF parameters and to open up possible applications.
Adapting augmented reality systems to the users’ needs using gamification and error solving methods
(2021)
Animations of virtual items in AR support systems are typically predefined and lack interactions with dynamic physical environments. AR applications rarely consider users’ preferences and do not provide customized spontaneous support under unknown situations. This research focuses on developing adaptive, error-tolerant AR systems based on directed acyclic graphs and error resolving strategies. Using this approach, users will have more freedom of choice during AR supported work, which leads to more efficient workflows. Error correction methods based on CAD models and predefined process data create individual support possibilities. The framework is implemented in the Industry 4.0 model factory at FH Aachen.
While bringing new opportunities, the Industry 4.0 movement also imposes new challenges to the manufacturing industry and all its stakeholders. In this competitive environment, a skilled and engaged workforce is a key to success. Gamification can generate valuable feedbacks for improving employees’ engagement and performance. Currently, Gamification in workspaces focuses on computer-based assignments and training, while tasks that require manual labor are rarely considered. This research provides an overview of Enterprise Gamification approaches and evaluates the challenges. Based on that, a skill-based Gamification framework for manual tasks is proposed, and a case study in the Industry 4.0 model factory is shown.
Virtual Reality (VR) offers novel possibilities for remote training regardless of the availability of the actual equipment, the presence of specialists, and the training locations. Research shows that training environments that adapt to users' preferences and performance can promote more effective learning. However, the observed results can hardly be traced back to specific adaptive measures but the whole new training approach. This study analyzes the effects of a combined point and leveling VR-based gamification system on assembly training targeting specific training outcomes and users' motivations. The Gamified-VR-Group with 26 subjects received the gamified training, and the Non-Gamified-VR-Group with 27 subjects received the alternative without gamified elements. Both groups conducted their VR training at least three times before assembling the actual structure. The study found that a level system that gradually increases the difficulty and error probability in VR can significantly lower real-world error rates, self-corrections, and support usages. According to our study, a high error occurrence at the highest training level reduced the Gamified-VR-Group's feeling of competence compared to the Non-Gamified-VR-Group, but at the same time also led to lower error probabilities in real-life. It is concluded that a level system with a variable task difficulty should be combined with carefully balanced positive and negative feedback messages. This way, better learning results, and an improved self-evaluation can be achieved while not causing significant impacts on the participants' feeling of competence.
Gamification applications are on the rise in the manufacturing sector to customize working scenarios, offer user-specific feedback, and provide personalized learning offerings. Commonly, different sensors are integrated into work environments to track workers’ actions. Game elements are selected according to the work task and users’ preferences. However, implementing gamified workplaces remains challenging as different data sources must be established, evaluated, and connected. Developers often require information from several areas of the companies to offer meaningful gamification strategies for their employees. Moreover, work environments and the associated support systems are usually not flexible enough to adapt to personal needs. Digital twins are one primary possibility to create a uniform data approach that can provide semantic information to gamification applications. Frequently, several digital twins have to interact with each other to provide information about the workplace, the manufacturing process, and the knowledge of the employees. This research aims to create an overview of existing digital twin approaches for digital support systems and presents a concept to use digital twins for gamified support and training systems. The concept is based upon the Reference Architecture Industry 4.0 (RAMI 4.0) and includes information about the whole life cycle of the assets. It is applied to an existing gamified training system and evaluated in the Industry 4.0 model factory by an example of a handle mounting.
Assistance systems have been widely adopted in the manufacturing sector to facilitate various processes and tasks in production environments. However, existing systems are mostly equipped with rigid functional logic and do not provide individual user experiences or adapt to their capabilities. This work integrates human factors in assistance systems by adjusting the hardware and instruction presented to the workers’ cognitive and physical demands. A modular system architecture is designed accordingly, which allows a flexible component exchange according to the user and the work task. Gamification, the use of game elements in non-gaming contexts, has been further adopted in this work to provide level-based instructions and personalised feedback. The developed framework is validated by applying it to a manual workstation for industrial assembly routines.
Digital twins are seen as one of the key technologies of Industry 4.0. Although many research groups focus on digital twins and create meaningful outputs, the technology has not yet reached a broad application in the industry. The main reasons for this imbalance are the complexity of the topic, the lack of specialists, and the unawareness of the twin opportunities. The project "Digital Twin Academy" aims to overcome these barriers by focusing on three actions: Building a digital twin community for discussion and exchange, offering multi-stage training for various knowledge levels, and implementing realworld use cases for deeper insights and guidance. In this work, we focus on creating a flexible learning platform that allows the user to select a training path adjusted to personal knowledge and needs. Therefore, a mix of basic and advanced modules is created and expanded by individual feedback options. The usage of personas supports the selection of the appropriate modules.
In the Laser Powder Bed Fusion (LPBF) process, parts are built out of metal powder material by exposure of a laser beam. During handling operations of the powder material, several influencing factors can affect the properties of the powder material and therefore directly influence the processability during manufacturing. Contamination by moisture due to handling operations is one of the most critical aspects of powder quality. In order to investigate the influences of powder humidity on LPBF processing, four materials (AlSi10Mg, Ti6Al4V, 316L and IN718) are chosen for this study. The powder material is artificially humidified, subsequently characterized, manufactured into cubic samples in a miniaturized process chamber and analyzed for their relative density. The results indicate that the processability and reproducibility of parts made of AlSi10Mg and Ti6Al4V are susceptible to humidity, while IN718 and 316L are barely influenced.
The manufacturing share of laser powder bed fusion (L-PBF) increases in industrial application, but still many process steps are manually operated. Additionally, it is not possible to achieve tight dimensional tolerances or low surfaces roughness. Hence, a process chain has to be set up to combine additive manufacturing (AM) with further machining technologies. To achieve a continuous workpiece flow as basis for further industrialization of L-PBF, the paper presents a novel substrate system and its application on L-PBF machines and post-processing. The substrate system consists of a zero-point clamping system and a matrix-like interface of contact pins to be substantially connected to the workpiece within the L-PBF process.