Fachbereich Maschinenbau und Mechatronik
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- Additive Manufacturing (3)
- SLM (3)
- additive manufacturing (3)
- Additive manufacturing (2)
- LPBF (2)
- fused filament fabrication (2)
- rapid tooling (2)
- 316L (1)
- 3D nonlinear finite element model (1)
- 802.15.4 (1)
- AM implementation (1)
- Assembly (1)
- Balanced hypergraph (1)
- Bluetooth (1)
- Brake set-up (1)
- Braking curves (1)
- Data-driven models (1)
- Distributed Control Systems, (1)
- Driver assistance system (1)
- Duality (1)
- Effective modal mass (1)
- Eutectic Silver Copper alloy (1)
- Factory Planning (1)
- Freight rail (1)
- Fused Filament Fabrication (1)
- Gamification (1)
- Hall’s Theorem (1)
- Human factors (1)
- Hybrid Manufacturing (1)
- Hypergraph (1)
- Industrial Automation Technology, (1)
- Industry 4.0 (1)
- Koenig’s Theorem (1)
- Level system (1)
- Manufacturing Process Chains (1)
- Matching (1)
- Natural frequency (1)
- Operational Control (1)
- PROFINET (1)
- Polyetheretherketone (PEEK) (1)
- Porositat (1)
- Prediction of molecular features (1)
- Process Parameters (1)
- Protein structure complexity (1)
- Quantitative structure activity relationship (1)
- Rapid Tooling (1)
- Residual Stresses (1)
- Response Surface Method (1)
- SOA (1)
- Scalar parameters (1)
- Selective Laser Melting (SLM) (1)
- Shape and surface properties (1)
- Shunting (1)
- Suspension bridge (1)
- Technology Planning (1)
- Tensile Strength (1)
- Thermal conductivity (1)
- Thin shell finite elements (1)
- Tool Making (1)
- User study (1)
- Vertex cover (1)
- Virtual reality (1)
- Welding (1)
- Wireless Networks (1)
- adaptive systems (1)
- assistance system (1)
- batch reproducibility (1)
- biopharmaceutical production process (1)
- cobald chrome (1)
- compression behavior (1)
- crystallization (1)
- cyber-physical production systems (1)
- dental bridges (1)
- digital factory (1)
- downstream processing design (1)
- environmental correlation (1)
- event-based simulation (1)
- experiment quality (1)
- factory planning (1)
- fluorescent protein carrier (1)
- gamification (1)
- greenhouse cultivation (1)
- hybrid model validation (1)
- industrial agents (1)
- infill strategy (1)
- interviews (1)
- manufacturing (1)
- manufacturing data model (1)
- manufacturing flexibility (1)
- manufacturing management (1)
- multi-agent systems (1)
- plant molecular farming (1)
- polyetheretherketone (1)
- polyetheretherketone (PEEK) (1)
- production planning and control (1)
- production systems (1)
- scan strategy (1)
- service-oriented architectures (1)
- technology planning (1)
- thematic analysis (1)
Additive Manufacturing (AM) is a topic that is becoming more relevant to many companies globally. With AM's progressive development and use for series production, integrating the technology into existing production structures is becoming an important criterion for businesses. This study qualitatively examines the actual state and different perspectives on the integration of AM in production structures. Seven semi-structured interviews were conducted and analyzed. The interview partners were high-level experts in Additive Manufacturing and production systems from industry and science. Four main themes were identified. Key findings are the far-reaching interrelationships and implications of AM within production structures. Specific AM-related aspects were identified. Those can be used to increase the knowledge and practical application of the technology in the industry and as a foundation for economic considerations.
The fourth industrial revolution is on its way to reshape manufacturing and value creation in a profound way. The underlying technologies like cyber-physical systems (CPS), big data, collaborative robotics, additive manufacturing or artificial intelligence offer huge potentials for the optimization and evolution of production systems. However, many manufacturing companies struggle to implement these technologies. This can only in part be attributed to the lack of skilled personal within these companies or a missing digitalization strategy. Rather, there is a fundamental incompatibility between the way current production systems and companies (Industry 3.0) are structured across multiple dimensions compared to what is necessary for industry 4.0. This is especially true in manufacturing systems and their transition towards flexible, decentralized and autonomous value creation networks. This paper shows across various dimensions these incompatibilities within manufacturing systems, explores their reasons and discusses a different approach to create a foundation for Industry 4.0 in manufacturing companies.
Establishing high-performance polymers in additive manufacturing opens up new industrial applications. Polyetheretherketone (PEEK) was initially used in aerospace but is now widely applied in automotive, electronics, and medical industries. This study focuses on developing applications using PEEK and Fused Filament Fabrication for cost-efficient vulcanization injection mold production. A proof of concept confirms PEEK’s suitability for AM mold making, withstanding vulcanization conditions. Printing PEEK above its glass transition temperature of 145 °C is preferable due to its narrow process window. A new process strategy at room temperature is discussed, with micrographs showing improved inter-layer bonding at 410°C nozzle temperature and 0.1 mm layer thickness. Minimizing the layer thickness from 0.15 mm to 0.1 mm improves tensile strength by 16%.
In the face of the current trend towards larger and more complex production tasks in the SLM process and the current limitations in terms of maximum build space, the welding of SLM components to each other or to conventionally manufactured parts is becoming increasingly relevant. The fusion welding of SLM components made of 316L has so far been rarely investigated and if so, then for highly specialised laser welding processes. When welding with industrial gas welding processes such as MIG/MAG or TIG welding, distortions occur which are associated with the resulting residual stresses in the components. This paper investigates process-side influencing factors to avoid resulting residual stresses in SLM components made of 316L. The aim is to develop a strategy to build up SLM components as stress-free as possible in order to join them as profitably as possible with a downstream welding process. For this purpose, influencing parameters such as laser power, scan speed, but also scan vector length and different scan patterns are investigated with regard to their influence on residual stresses.
Transgenic plants have the potential to produce recombinant proteins on an agricultural scale, with yields of several tons per year. The cost-effectiveness of transgenic plants increases if simple cultivation facilities such as greenhouses can be used for production. In such a setting, we expressed a novel affinity ligand based on the fluorescent protein DsRed, which we used as a carrier for the linear epitope ELDKWA from the HIV-neutralizing antibody 2F5. The DsRed-2F5-epitope (DFE) fusion protein was produced in 12 consecutive batches of transgenic tobacco (Nicotiana tabacum) plants over the course of 2 years and was purified using a combination of blanching and immobilized metal-ion affinity chromatography (IMAC). The average purity after IMAC was 57 ± 26% (n = 24) in terms of total soluble protein, but the average yield of pure DFE (12 mg kg−1) showed substantial variation (± 97 mg kg−1, n = 24) which correlated with seasonal changes. Specifically, we found that temperature peaks (>28°C) and intense illuminance (>45 klx h−1) were associated with lower DFE yields after purification, reflecting the loss of the epitope-containing C-terminus in up to 90% of the product. Whereas the weather factors were of limited use to predict product yields of individual harvests conducted for each batch (spaced by 1 week), the average batch yields were well approximated by simple linear regression models using two independent variables for prediction (illuminance and plant age). Interestingly, accumulation levels determined by fluorescence analysis were not affected by weather conditions but positively correlated with plant age, suggesting that the product was still expressed at high levels, but the extreme conditions affected its stability, albeit still preserving the fluorophore function. The efficient production of intact recombinant proteins in plants may therefore require adequate climate control and shading in greenhouses or even cultivation in fully controlled indoor farms.
Chromatography is the workhorse of biopharmaceutical downstream processing because it can selectively enrich a target product while removing impurities from complex feed streams. This is achieved by exploiting differences in molecular properties, such as size, charge and hydrophobicity (alone or in different combinations). Accordingly, many parameters must be tested during process development in order to maximize product purity and recovery, including resin and ligand types, conductivity, pH, gradient profiles, and the sequence of separation operations. The number of possible experimental conditions quickly becomes unmanageable. Although the range of suitable conditions can be narrowed based on experience, the time and cost of the work remain high even when using high-throughput laboratory automation. In contrast, chromatography modeling using inexpensive, parallelized computer hardware can provide expert knowledge, predicting conditions that achieve high purity and efficient recovery. The prediction of suitable conditions in silico reduces the number of empirical tests required and provides in-depth process understanding, which is recommended by regulatory authorities. In this article, we discuss the benefits and specific challenges of chromatography modeling. We describe the experimental characterization of chromatography devices and settings prior to modeling, such as the determination of column porosity. We also consider the challenges that must be overcome when models are set up and calibrated, including the cross-validation and verification of data-driven and hybrid (combined data-driven and mechanistic) models. This review will therefore support researchers intending to establish a chromatography modeling workflow in their laboratory.
Proteins are important ingredients in food and feed, they are the active components of many pharmaceutical products, and they are necessary, in the form of enzymes, for the success of many technical processes. However, production can be challenging, especially when using heterologous host cells such as bacteria to express and assemble recombinant mammalian proteins. The manufacturability of proteins can be hindered by low solubility, a tendency to aggregate, or inefficient purification. Tools such as in silico protein engineering and models that predict separation criteria can overcome these issues but usually require the complex shape and surface properties of proteins to be represented by a small number of quantitative numeric values known as descriptors, as similarly used to capture the features of small molecules. Here, we review the current status of protein descriptors, especially for application in quantitative structure activity relationship (QSAR) models. First, we describe the complexity of proteins and the properties that descriptors must accommodate. Then we introduce descriptors of shape and surface properties that quantify the global and local features of proteins. Finally, we highlight the current limitations of protein descriptors and propose strategies for the derivation of novel protein descriptors that are more informative.
The thermal conductivity of components manufactured using Laser Powder Bed Fusion (LPBF), also called Selective Laser Melting (SLM), plays an important role in their processing. Not only does a reduced thermal conductivity cause residual stresses during the process, but it also makes subsequent processes such as the welding of LPBF components more difficult. This article uses 316L stainless steel samples to investigate whether and to what extent the thermal conductivity of specimens can be influenced by different LPBF parameters. To this end, samples are set up using different parameters, orientations, and powder conditions and measured by a heat flow meter using stationary analysis. The heat flow meter set-up used in this study achieves good reproducibility and high measurement accuracy, so that comparative measurements between the various LPBF influencing factors to be tested are possible. In summary, the series of measurements show that the residual porosity of the components has the greatest influence on conductivity. The degradation of the powder due to increased recycling also appears to be detectable. The build-up direction shows no detectable effect in the measurement series.
In times of short product life cycles, additive manufacturing and rapid tooling are important methods to make tool development and manufacturing more efficient. High-performance polymers are the key to mold production for prototypes and small series. However, the high temperatures during vulcanization injection molding cause thermal aging and can impair service life. The extent to which the thermal stress over the entire process chain stresses the material and whether it leads to irreversible material aging is evaluated. To this end, a mold made of PEEK is fabricated using fused filament fabrication and examined for its potential application. The mold is heated to 200 ◦C, filled with rubber, and cured. A differential scanning calorimetry analysis of each process step illustrates the crystallization behavior and first indicates the material resistance. It shows distinct cold crystallization regions at a build chamber temperature of 90 ◦C. At an ambient temperature above Tg, crystallization of 30% is achieved, and cold crystallization no longer occurs. Additional tensile tests show a decrease in tensile strength after ten days of thermal aging. The steady decrease in recrystallization temperature indicates degradation of the additives. However, the tensile tests reveal steady embrittlement of the material due to increasing crosslinking.
Manufacturing companies across multiple industries face an increasingly dynamic and unpredictable environment. This development can be seen on both the market and supply side. To respond to these challenges, manufacturing companies must implement smart manufacturing systems and become more flexible and agile. The flexibility in operational planning regarding the scheduling and sequencing of customer orders needs to be increased and new structures must be implemented in manufacturing systems’ fundamental design as they constitute much of the operational flexibility available. To this end, smart and more flexible solutions for production planning and control (PPC) are developed. However, scheduling or sequencing is often only considered isolated in a predefined stable environment. Moreover, their orientation on the fundamental logic of the existing IT solutions and their applicability in a dynamic environment is limited. This paper presents a conceptual model for a task-based description logic that can be applied to factory planning, technology planning, and operational control. By using service-oriented architectures, the goal is to generate smart manufacturing systems. The logic is designed to allow for easy and automated maintenance. It is compatible with the existing resource and process allocation logic across operational and strategic factory and production planning.
Traditional vulcanization mold manufacturing is complex, costly, and under pressure due to shorter product lifecycles and diverse variations. Additive manufacturing using Fused Filament Fabrication and high-performance polymers like PEEK offer a promising future in this industry. This study assesses the compressive strength of various infill structures (honeycomb, grid, triangle, cubic, and gyroid) when considering two distinct build directions (Z, XY) to enhance PEEK’s economic and resource efficiency in rapid tooling. A comparison with PETG samples shows the behavior of the infill strategies. Additionally, a proof of concept illustrates the application of a PEEK mold in vulcanization. A peak compressive strength of 135.6 MPa was attained in specimens that were 100% solid and subjected to thermal post-treatment. This corresponds to a 20% strength improvement in the Z direction. In terms of time and mechanical properties, the anisotropic grid and isotropic cubic infill have emerged for use in rapid tooling. Furthermore, the study highlights that reducing the layer thickness from 0.15 mm to 0.1 mm can result in a 15% strength increase. The study unveils the successful utilization of a room-temperature FFF-printed PEEK mold in vulcanization injection molding. The parameters and infill strategies identified in this research enable the resource-efficient FFF printing of PEEK without compromising its strength properties. Using PEEK in rapid tooling allows a cost reduction of up to 70% in tool production.
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.
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.
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.
The fourth industrial revolution introduces disruptive technologies to production environments. One of these technologies are multi-agent systems (MASs), where agents virtualize machines. However, the agent's actual performances in production environments can hardly be estimated as most research has been focusing on isolated projects and specific scenarios. We address this gap by implementing a highly connected and configurable reference model with quantifiable key performance indicators (KPIs) for production scheduling and routing in single-piece workflows. Furthermore, we propose an algorithm to optimize the search of extrema in highly connected distributed systems. The benefits, limits, and drawbacks of MASs and their performances are evaluated extensively by event-based simulations against the introduced model, which acts as a benchmark. Even though the performance of the proposed MAS is, on average, slightly lower than the reference system, the increased flexibility allows it to find new solutions and deliver improved factory-planning outcomes. Our MAS shows an emerging behavior by using flexible production techniques to correct errors and compensate for bottlenecks. This increased flexibility offers substantial improvement potential. The general model in this paper allows the transfer of the results to estimate real systems or other models.
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.
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.
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 maintenance of wind turbines is of growing importance considering the transition to renewable energy. This paper presents a multi-robot-approach for automated wind turbine maintenance including a novel climbing robot. Currently, wind turbine maintenance remains a manual task, which is monotonous, dangerous, and also physically demanding due to the large scale of wind turbines. Technical climbers are required to work at significant heights, even in bad weather conditions. Furthermore, a skilled labor force with sufficient knowledge in repairing fiber composite material is rare. Autonomous mobile systems enable the digitization of the maintenance process. They can be designed for weather-independent operations. This work contributes to the development and experimental validation of a maintenance system consisting of multiple robotic platforms for a variety of tasks, such as wind turbine tower and rotor blade service. In this work, multicopters with vision and LiDAR sensors for global inspection are used to guide slower climbing robots. Light-weight magnetic climbers with surface contact were used to analyze structure parts with non-destructive inspection methods and to locally repair smaller defects. Localization was enabled by adapting odometry for conical-shaped surfaces considering additional navigation sensors. Magnets were suitable for steel towers to clamp onto the surface. A friction-based climbing ring robot (SMART— Scanning, Monitoring, Analyzing, Repair and Transportation) completed the set-up for higher payload. The maintenance period could be extended by using weather-proofed maintenance robots. The multi-robot-system was running the Robot Operating System (ROS). Additionally, first steps towards machine learning would enable maintenance staff to use pattern classification for fault diagnosis in order to operate safely from the ground in the future.
Improving the Mechanical Strength of Dental Applications and Lattice Structures SLM Processed
(2020)
To manufacture custom medical parts or scaffolds with reduced defects and high mechanical characteristics, new research on optimizing the selective laser melting (SLM) parameters are needed. In this work, a biocompatible powder, 316L stainless steel, is characterized to understand the particle size, distribution, shape and flowability. Examination revealed that the 316L particles are smooth, nearly spherical, their mean diameter is 39.09 μm and just 10% of them hold a diameter less than 21.18 μm. SLM parameters under consideration include laser power up to 200 W, 250–1500 mm/s scanning speed, 80 μm hatch spacing, 35 μm layer thickness and a preheated platform. The effect of these on processability is evaluated. More than 100 samples are SLM-manufactured with different process parameters. The tensile results show that is possible to raise the ultimate tensile strength up to 840 MPa, adapting the SLM parameters for a stable processability, avoiding the technological defects caused by residual stress. Correlating with other recent studies on SLM technology, the tensile strength is 20% improved. To validate the SLM parameters and conditions established, complex bioengineering applications such as dental bridges and macro-porous grafts are SLM-processed, demonstrating the potential to manufacture medical products with increased mechanical resistance made of 316L.
Tribological performance of biodegradable lubricants under different surface roughness of tools
(2019)
For smaller railway operators or those with a diverse fleet, it can be difficult to collect sufficient data to improve maintenance programs. At the same time, new rules such as entity in charge of maintenance – ECM – regulations impose an additional workload by requiring a dedicated maintenance management system and specific reports. The RailCrowd platform sets out to facilitate compliance with ECM and similar regulations while at the same time pooling anonymised fleet data across operators to form virtual fleets, providing greater data insights.
This work demonstrates how the interaction between particle image velocimetry (PIV) and robotics can massively increase measurement efficiency. The interdisciplinary approach is shown using the complex example of an automated, large scale, industrial environment: a typical automotive wind tunnel application. Both the high degree of flexibility in choosing the measurement region and the complete automation of stereo PIV measurements are presented. The setup consists of a combination of three robots, individually used as a 6D traversing unit for the laser illumination system as well as for each of the two cameras. Synchronised movements in the same reference frame are realised through a master-slave setup with a single interface to the user. By integrating the interface into the standard wind tunnel management system, a single measurement plane or a predefined sequence of several planes can be requested through a single trigger event, providing the resulting vector fields within minutes.
In this paper, a brief overview on the demands of large scale industrial PIV and the existing solutions is given. Afterwards, the concept of RoboPIV is introduced as a new approach. In a first step, the usability of a selection of commercially available robot arms is analysed. The challenges of pose uncertainty and importance of absolute accuracy are demonstrated through comparative measurements, explaining the individual pros and cons of the analysed systems. Subsequently, the advantage of integrating RoboPIV directly into the existing wind tunnel management system is shown on basis of a typical measurement sequence. In a final step, a practical measurement procedure, including post-processing, is given by using real data and results. Ultimately, the benefits of high automation are demonstrated, leading to a drastic reduction in necessary measurement time compared to non-automated systems, thus massively increasing the efficiency of PIV measurements.
The rail business is challenged by long product life cycles and a broad spectrum of assembly groups and single parts. When spare part obsolescence occurs, quick solutions are needed. A reproduction of obsolete parts is often connected to long waiting times and minimum lot quantities that need to be purchased and stored. Spare part storage is therefore challenged by growing stocks, bound capital and issues of part ageing. A possible solution could be a virtual storage of spare parts which will be 3D printed through additive manufacturing technologies in case of sudden demand. As mechanical properties of additive manufactured parts are neither guaranteed by machine manufacturers nor by service providers, the utilization of this relatively young technology is impeded and research is required to address these issues. This paper presents an examination of mechanical properties of specimens manufactured from stainless steel through the selective laser melting (SLM) process. The specimens were produced in multiple batches. This paper interrogates the question if the test results follow a normal distribution pattern and if mechanical property predictions can be made. The results will be put opposite existing threshold values provided as the industrial standard. Furthermore, probability predictions will be made in order to examine the potential of the SLM process to maintain state-of-the-art mechanical property requirements.
This paper presents the results of an eigenvalue analysis of the Fatih Sultan Mehmet Bridge. A high-resolution finite element model was created directly from the available design documents. All physical properties of the structural components were included in detail, so no calibration to the measured data was necessary. The deck and towers were modeled with shell elements. A nonlinear static analysis was performed before the eigenvalue calculation. The calculated natural frequencies and corresponding mode shapes showed good agreement with the available measured ambient vibration data. The calculation of the effective modal mass showed that nine modes had single contributions higher than 5 % of the total mass. They were in a frequency range up to 1.2 Hz. The comparison of the results for the torsional modes especially demonstrated the advantage of using thin shell finite elements over the beam modeling approach.
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.
We prove characterizations of the existence of perfect ƒ-matchings in uniform mengerian and perfect hypergraphs. Moreover, we investigate the ƒ-factor problem in balanced hypergraphs. For uniform balanced hypergraphs we prove two existence theorems with purely combinatorial arguments, whereas for non-uniform balanced hypergraphs we show that the ƒ-factor problem is NP-hard.
An equitable graph coloring is a proper vertex coloring of a graph G where the sizes of the color classes differ by at most one. The equitable chromatic number is the smallest number k such that G admits such equitable k-coloring. We focus on enumerative algorithms for the computation of the equitable coloring number and propose a general scheme to derive pruning rules for them: We show how the extendability of a partial coloring into an equitable coloring can be modeled via network flows. Thus, we obtain pruning rules which can be checked via flow algorithms. Computational experiments show that the search tree of enumerative algorithms can be significantly reduced in size by these rules and, in most instances, such naive approach even yields a faster algorithm. Moreover, the stability, i.e., the number of solved instances within a given time limit, is greatly improved.
Since the execution of flow algorithms at each node of a search tree is time consuming, we derive arithmetic pruning rules (generalized Hall-conditions) from the network model. Adding these rules to an enumerative algorithm yields an even larger runtime improvement.
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.
Today, the assembly of laser systems requires a large share of manual operations due to its complexity regarding the optimal alignment of optics. Although the feasibility of automated alignment of laser optics has been shown in research labs, the development effort for the automation of assembly does not meet economic requirements – especially for low-volume laser production. This paper presents a model-based and sensor-integrated assembly execution approach for flexible assembly cells consisting of a macro-positioner covering a large workspace and a compact micromanipulator with camera attached to the positioner. In order to make full use of available models from computer-aided design (CAD) and optical simulation, sensor systems at different levels of accuracy are used for matching perceived information with model data. This approach is named "chain of refined perception", and it allows for automated planning of complex assembly tasks along all major phases of assembly such as collision-free path planning, part feeding, and active and passive alignment. The focus of the paper is put on the in-process image-based metrology and information extraction used for identifying and calibrating local coordinate systems as well as the exploitation of that information for a part feeding process for micro-optics. Results will be presented regarding the processes of automated calibration of the robot camera as well as the local coordinate systems of part feeding area and robot base.
The radio-based wireless data communication has made the realization of new technical solutions possible in many fields of the automation technology (AT). For about ten years, a constant disproportionate growth of wireless technologies can be observed in the automation technology.
However, it shows that especially for the AT, conventional technologies of office automation are unsuitable and/or not manageable. The employment of mobile services in the industrial automation technology has the potential of significant cost and time savings. This leads to an increased productivity in various fields of the AT, for example in the factory and process automation or in production logistics. In this paper technologies and solutions for an automation-suited supply of mobile wireless services will be introduced under the criteria of real time suitability, IT-security and service orientation.
Emphasis will be put on the investigation and development of wireless convergence layers for different radio technologies, on the central provision of support services for an easy-to-use, central, backup enabled management of combined wired / wireless networks and on the study on integrability in a Profinet real-time Ethernet network.
Selective laser melting of metals: desktop machines open up new chances even for small companies
(2012)
Additive manufacturing (AM) of metal parts by using Selective Laser Melting (SLM) has become a powerful tool mostly in the area of automotive, aerospace engineering and others. Especially in the field of dentistry, jewelry and related branches that require individualized or even one-of-a-kind products, the direct digital manufacturing process opens up new ways of design and manufacturing. In these fields, mostly small and medium sized businesses (SME) are operating which do not have sufficient human and economic resources to invest in this technology. But to stay competitive, the application of AM can be regarded as a necessity. In this situation a new desktop machine (Realizer SLM 50) was introduced that cost about 1/3 of a shop floor SLM machine and promises small quality parts. To find out whether the machine really is an alternative for SMEs the University of Applied Science, Aachen, Germany, designed, build and optimized typical parts from the dentistry and the jewelry branches using CoCr and silver material, the latter being new with this application. The paper describes the SLM procedure and how to find and optimize the most important parameters. The test is accompanied by digital simulation in order to verify the build parameters and to plan future builds. The procedure is shown as well as the resulting parts made from CoCr and silver material.
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.
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.
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.
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.
Numerical and experimental investigation of tensile behavior of laser beam welded TRIP700 steel
(2011)
The objectives of the present work are to characterize the Gas Metal Arc Welding process of DP 600 sheet steel and to summarize the modelling techniques. The time-temperature evolution during the welding cycle was measured experimentally and modelled with the softwaretool SimWeld. To model the phase transformations during the welding cycle dilatometer tests were done to quantify the parameters for phase field modelling by MICRESS®. The important input parameters are interface mobility, nucleation density, etc. A contribution was made to include austenite to bainite transformation in MICRESS®. This is useful to predict the microstructure in the fast cooling segments. The phase transformation model is capable to predict the microstructure along the heating and cooling cycles of welding. Tensile tests have shown the evidence of failure at the heat affected zone, which has the ferrite-tempered martensite microstructure.
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.
This paper aims to evaluate the formability of tailor welded blanks of dual phase (DP600)/transformation induced plasticity (TRIP700) steel sheets. In this work, bead on plate butt joints of 2·5 mm DP600 and 1·2 mm TRIP700 steel sheets were performed using CO2 laser beam welding. Microhardness measurements and transverse tensile testing were carried out to characterise the welds. The formability of base metals and welds were investigated by standard Erichsen test. In a perpendicular tensile test to the weld line, all specimens were fractured at the TRIP base metal, and the strengths were somewhat higher than those of base metal. There was a significant reduction in formability caused by welding of the DP600/TRIP700 steel sheets, and the formability increased with increasing welding speed.
Thermodynamic relations between component activities and gas solubilities in binary metallic systems
(1985)
Thermohydrodynamic analysis of thrust-bearing with circular pads running on bubbly oil (BTHD-theory)
(1985)
An increasing amount of popular articles focus on making models and sculptures by 3D Printing thus making more and more even private users aware of this technology. Unfortunately they mostly draw an incomplete picture of how our daily life will be influenced by this new technology. Often this is caused by a very technical point of view based on not very representative examples. This article focuses on the peoples needs as they have been structured by the so-called Maslow pyramid. Doing so, it underlines that 3D Printing (called Additive Manufacturing or Rapid Prototyping as well) already touches all aspects of life and is about to revolutionize most of them.
Although Selective Laser Melting (SLM) process is an innovative manufacturing method, there are challenges such as inferior mechanical properties of fabricated objects. Regarding this, buckling deformation which is caused by thermal stress is one of the undesired mechanical properties which must be alleviated. As buckling deformation is more observable in hard to process materials, silver is selected to be studied theoretically and experimentally for this paper. Different scanning strategies are utilized and a Finite Element Method (FEM) is applied to calculate the temperature gradient in order to determine its effect on the buckling deformation of the objects from experiments.
During the development process of a complex technical product, one widely used and important technique is accelerated testing where the applied stress on a component is chosen to exceed the reference stress, i.e. the stress encountered in field operation, in order to reduce the time to failure. For that, the reference stress has to be known. Since a complex technical product may fail regarding numerous failure modes, stress in general is highly dimensional rather than scalar. In addition, customers use their products individually, i.e. field operation should be described by a distribution rather than by one scalar stress value. In this paper, a way to span the customer usage space is shown. It allows the identification of worst case reference stress profiles in significantly reduced dimensions with minimal loss of information. The application example shows that even for a complex product like a combustion engine, stress information can be compressed significantly. With low measurement effort it turned out that only three reference stress cycles were sufficient to cover a broad range of customer stress variety.
Additive Manufacturing of metal parts by Selective Laser Melting has become a powerful tool for the direct manufacturing of complex parts mainly for the aerospace and medical industry. With the introduction of its desktop machine, Realizer targeted the dental market. The contribution describes the special features of the machine, discusses details of the process and shows manufacturing results focused on metal dental devices.