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Production supermarkets are a system to ensure high-frequency, demand-oriented, in-plant production supply with low lot sizes. The paper presents methods to design and dimension these systems using qualitative design criteria and quantitative approaches based on well-known analytical methods for conventional order picking systems. The methods help to design layout, provision type and path strategy and to derive space consumption and the number of supermarket employees required to fulfill a defined demand.
By simultaneous laser beam melting (SLBM), different polymer powders can be processed to multi-material parts, which offers the potential to enlarge the field of application for conventional LBM. In a SLBM process, a powder bed consisting of different polymers and therefore with different melting and crystallization temperatures is deposited. Besides the use of infrared emitters for preheating the lower melting polymer, a CO2 laser distributes the necessary preheating temperature of the higher melting polymer. In the last step, a thulium fibre laser distributes the energy necessary for melting the two preheated powders simultaneously. In order to analyze the temperature gradients of the process on the powder surface and in deeper layers, a high-resolution thermal imaging system and thermocouples are used.
Least squares pose estimation of cylinder axes from multiple views using contour line features
(2015)
In this paper, a new method for a minimum-error pose estimation of cylinder axes based on apparent contour line features from multiple views is presented. Novel model equations for both single and particularly multiple views are derived, and based upon these, an iterative algorithm for least squares fitting the model to imaged cylinder contour line features is introduced. The good performance and fast convergence of the proposed algorithm is shown by solving exemplary fitting problems.
Modeling, identification and control of an antagonistically actuated joint for telerobotic systems
(2015)
Within this paper a modeling, identification and control technique for an antagonistically actuated joint consisting of two pneumatically actuated muscles is presented. The antagonistically actuated joint acts as a test bench for control architectures which are going to be used to control an exoskeleton within a telerobotic system. A static and dynamic model of the muscle and the joint is derived and the parameters of the models are identified using a least-squares algorithm. The control architecture, consisting of a inner pressure and an outer position controller is presented. The pressure controller is evaluated using switching valves compared against proportional valves.
Manual tasks in industrial production are often monotonous, leading to a decrease in concentration and motivation of the worker and thus to deficiencies in the products. With quality as well as performance requirements getting more and more stringent, workers need additional support by their work environment. We developed a novel approach providing worker assistance and inline quality assurance for manual workplaces. The prototypical system Smart Workbench (SWoB) uses a multimodal sensor interface consisting of a 3D depth sensor in combination with a 2D camera to control quality aspects of the product and track the work progress. The bidirectional flow of information is handled via an image processing driven gestural interface and the displaying of advice directly on the work surface. In this paper the developed system is introduced and the current state of evaluating its industrial usage with a manual quality control and packaging task reported.
Tightness is often the main requirement for quasi-simultaneous laser transmission welds. However, remaining gaps cannot be detected by the used set-path monitoring. By using a pyrometer in combination with a 3D-scanner, weld seam interruptions can be localized precisely while welding, due to temperature deviations along the weld contour. To analyze the temperature signal in correlation to the progress of gap-bridging, T-joint samples with predefined gaps are welded. The set-path is measured synchronously. Additionally, the temperature distribution and the influence of the thermal expansion of the polymers are studied by a thermo-mechanical FEM-process simulation. On top of that, the melt blow-out of the welded samples is analyzed using μCT-measurements. The experiments have shown that closing of a gap can be identified reliably by the temperature signal and that the squeezed melt flow into the gap and the thermal expansion in the gap zone accelerates gap-bridging. Furthermore the inserted heat can be adapted in the fault zone, in order to avoid thermal damage.
Parameterization Process of the Maxwell Model to Describe the Transient Force Behavior of a Tire
(2017)
The present technical article deals with the modeling of dynamic tire forces, which are relevant during interactions of safety relevant Advanced Driver Assistance Systems (ADAS). Special attention has been paid on simple but effective tire modeling of semi-physical type. In previous investigations, experimental validation showed that the well-known first-order Kelvin-Voigt model, described by a spring and damper element, describes good suitability around fixed operation points, but is limited for a wide working range. When aiming to run vehicle dynamics models within a frequency band of excitation up to 8 Hz, these models deliver remarkable deviations from measured tire characteristics. To overcome this limitation, a nonlinear Maxwell spring-damper element was introduced which is qualified to model the dynamic hardening of the elastomer materials of the tire. However, the advantage of a more realistic description of the transient behavior leads to a more complex parametrization process. Therefore, in the proposed article attention is paid to describe the identification process including defined maneuvers to parameterize the tire model, where the accuracy of the parameter strongly depends on the quality of the available input data from measurement. In order to study this important aspect of parameterization, the reference data from simulation of the full physical tire model FTire is applied like a “virtual measurement” of specified testing maneuvers. The procedure of simulation by means of the enhanced first order dynamics model is implemented by the semi-physical tire model TMeasy. Finally, the improvements of the extended model are discussed and an outlook for future work is given.
This paper discusses modeling and nonlinear control of a joint antagonistically actuated by two pneumatic, artificial muscles. A single model of the whole system is obtained by a combined physical and phenomenological modeling approach. The combined model for the joint, the muscles and the proportional valves results in a nonlinear, affine-in-control system description. The model is used to derive control laws for an input/output linearization approach to linearize the plant. Modeling and parametrization errors are covered via an outer control loop consisting of a state-feedback which is extended by an additional feedback of error integral. Extensive experimental results show the quality of the model and the performance of the respective control laws.
Seamless human-robot collaboration depends on high non-verbal behaviour recognition rates. To realize that in real-world manufacturing scenarios with an ecological valid setup, a lot of effort has to be invested. In this paper, we evaluate the impact of spontaneous inputs on the robustness of human-robot collaboration during gesture-based interaction. A high share of these spontaneous inputs lead to a reduced capability to predict behaviour and subsequently to a loss of robustness. We observe body and hand behaviour during interactive manufacturing of a collaborative task within two experiments. First, we analyse the occurrence frequency, reason and manner of human inputs in specific situations during a human-human experiment. We show the high impact of spontaneous inputs, especially in situations that differ from the typical working procedure. Second, we concentrate on implicit inputs during a real-world Wizard of Oz experiment using our human-robot working cell. We show that hand positions can be used to anticipate user needs in a semi-structured environment by applying knowledge about the semi-structured human behaviour which is distributed over working space and time in a typical manner.
An effective way to reduce greenhouse gas emissions (GHGs) is to use rurally produced straight jatropha oil as a substitute for diesel fuel. However, the different physical and chemical properties of straight vegetable oils (SVOs) require a customized setup of the combustion engine, particularly of the injection timing and quantity. Therefore, this study demonstrates the differences in the injection and combustion processes of jatropha oil compared to diesel fuel, particularly in terms of its compatibility with exhaust gas recirculation (EGR).
A 2.2 l common-rail diesel engine with a two-stage turbocharging concept was used for testing. To examine the differences in injection rate shaping of diesel fuel and jatropha oil, the injector was tested with an injection rate analyzer using both the fuels. To investigate the combustion process, the engine was mounted at an engine test bench and equipped with a cylinder pressure indication system. All limited emissions, as well as fuel consumption, were measured.
Various injection strategies, boost and rail pressure levels were tested at different EGR rates in terms of their impact on the combustion process. EGR in particular offers a great potential in the case of jatropha oil combustion due to its oxygen content. In addition, the investigation of injection rate shaping in combination with cylinder pressure analysis allowed a detailed thermodynamic evaluation of the combustion process. Ignition delay (ID) was also analyzed using a new method to calculate the start of combustion (SOC)
This article discusses the relevance of the motion behavior and adaptation of a collaborative robot for human-robot cooperation. Two experiments on cooperative assembly are shown. First, a human-human experiment with defined test conditions evaluates the aspects of distance, nearest body part, and predictability as significant. Second, a human-robot experiment shows that fixed trajectories and conservative dynamic parameters lead to a quick gain of confidence of the participants. Besides, the data shows that a realistic use case with complex tasks is key to evaluate the impact of motion parameters.
In smart manufacturing environments robots collaborate with human operators as peers. They even share the same working space and time. An intuitive interaction with different input modalities is decisive to reduce workload and training periods for collaboration. We introduce our interaction system that is able to recognize gestures, actions and objects in a typical smart working scenario. As key aspect, this article considers an empirical investigation of input modalities (touch, gesture), individual differences (performance, recognition rate, previous knowledge) and boundary conditions (level of automation) on user experience. Therefore, answers from 31 participants within two experiments are collected. We show that the arrangement of the human-robot collaboration (input modalities, boundary conditions) has a significant effect on user experience in real-world environments. This effect and the individual differences between participants can be measured utilizing recognition rates and standardized usability questionnaires.
The purpose of this study was to develop a user-friendly presentation of surface-EMG data in near-time for intraoperative nerve-monitoring. We have built a novel surface-EMG probe as a diagnostic device to investigate innervation patterns of sphincter muscles in further clinical diagnostic studies. S-EMG data were recorded from 20 healthy volunteers from the orbicularis oris muscles. We developed an automated analysis based on correlation in order to find phase inversions and thus innervation zones automatically. We compared our automated analysis with manual, visual analysis. Both techniques were reviewed for variance and showed reproducible results. Data from automated analysis were compared to visually analyzed data showing high consistency. Based on our automated analysis, we created an intuitive visualization of all measurements per person. We displayed the quality and quantity of the phase inversions found in a subject thus allowing for simple identification of innervation zones. We conclude that our set-up showed sufficient reliability for detection of motoric endplate activity and can be used for further clinical neurophysiological studies.
Quasi-simultaneous laser transmission welding is preferably used for packaging sensors and electronics. In order to protect the components from moisture, a hermetic encapsulation is needed. However, local weld seam interruptions cannot be identified with the commonly used set-path monitoring. By using a pyrometer, coaxially integrated into a 3D-scanner, gaps between the joining partners can be allocated on basis of the measured temperature. However, the scattering of the heat radiation, especially caused by the fiber reinforcement of the plastics, leads to a reduction of the accessible heat radiation, which makes the identification of gaps considerably more difficult. The herein used experimental setup is characterized by a small detection spot and only by a slight weakening of the heat radiation inside the scanner. Hence, for welding PA6-GF30, the detection of small sized gaps is possible, even if a glass fiber content of 30 percent (wt.) and a weld seam width with approximately 1 mm are given.
Dynamical Investigation of Crawling Motion System based on a Multistable Tensegrity Structure
(2018)
The basic idea of this article is the utilization of the multistable character of a compliant tensegrity structure to control the direction of motion of a crawling motion system. A crawling motion system basing on a two-dimensional tensegrity structure with multiple stable equilibrium states is considered. This system is in contact with a horizontal plane due to gravity. For a selected harmonic actuation of the system small oscillations around the given equilibrium state of the tensegrity structure occur and the corresponding uniaxial motion of the system is evaluated. A change of the equilibrium state of the tensegrity structure yields to novel configuration of the entire system. Moreover, the motion behavior of the novel configuration is totally different although the actuation strategy is not varied. In particular, the direction of motion changes. Therefore, this approach enables a uniaxial bidirectional crawling motion with a controllable direction of motion using only one actuat or with a selected excitation frequency.
This paper deals with the locomotion by tilting sequences of shape-variable compliant tensegrity structures. The shape of these structures is controlled by manipulating their prestress state. The tensegrity structure is tilting as consequence of a suitable variation of its shape. By multiple repetition of such tilting sequences a motion is generated. Quasi-static considerations for the considered structures are presented in order to estimate the actuation parameters. For a proper number of actuators this quasi-static approach enables an analytical calculation of the actuation parameters of the structure in order to control the geometrical configuration as required. As an example a two-dimensional tensegrity structure which is in contact with a horizontal plane due to gravity is considered. By successive tilting sequences a uniaxial motion results. The excitation of the structure is calculated for a given change of shape with the quasi-static analysis. The according results are compared with transient dynamic simulations. Qualitative conclusions about the motion behavior and the usability of the quasi-static approach are given.
The development of biomimetic robots has gained research interest in the last years as it may both help under-standing processes of motion execution in biological systems as well as developping a novel generation of intelligent and energy efficient robots. However, exact model generation that builds up on observations and robot design is very time intensive. In this paper we present a novel pipeline for co-development of biomimetic hardware and simulation models based on biological Computer Tomography (CT) data. For this purpose we exploit State of the Art rapid prototyping technologies such as 3D Printing and the Neurorobotics Platform for musculoskeletal simulations in virtual environments. The co-development integrates both advantages of virtual and physical experimental models and is expected to increase development speed of controllers that can be tested on the simulated counterpart before application to a printed robot model. We demonstrate the pipeline by generating a one year old infant model as a musculoskeletal simulation model and a print-in-place 3D printed skeleton as a single movable part. Even though we hereonly introduce the initial body generation and only a first testsetup for a modular sensory and control framework, we can clearly spot advantages in terms of rapid model generation and highly biological related models. Engineering costs are reducedand models can be provided to a wide research community for controller testing in an early development phase.
Collaboration between robots and humans requires communicative skills on both sides. The robot has to understand the conscious and unconscious activities of human workers. Many state-of-the-art activity recognition algorithms with high performance rates on existing benchmark datasets are available for this task. This paper re-evaluates appropriate architectures in light of human work activity recognition for working cells in industrial production contexts. The specific constraints of such a domain is elaborated and used as prior knowledge. We utilize state-of-the-art algorithms as spatiotemporal feature encoders and search for appropriate classification and fusion strategies. Furthermore, we combine keypoint-based with appearance-based approaches to a multi-stream recognition system. Due to data protection rules and the high effort of data annotation within industrial domains only small datasets are available that reflect production aspects. Therefore, we use transfer learning approaches to reduce the dependency on data volume and variance in the target domain. The resulting recognition system achieves high performance for both singular person action and human-object interaction.
The rope curve line of a tensioned rope can be described by means of the catenary curve. Opposed to that, the curved line of a free bent rope cannot be described by an analytical function. Practical applications of free bending are for example at tail ropes at the bottom of shaft in rope drives with traction sheaves. The question whether the maximum diameter of rope loop is small enough for the diameter of the shaft is highly interesting. In [1] a method was presented to calculate the curved line of free bent ropes numerically by help of energy methods. An analytical description of rope curve line would be very helpful. Beginning with the structure of a rope curve line of tensioned rope (catenary curve) and considering the influence of bending stiffness, the structure of an analytical equation for the curve line of a free bent rope will be developed. The main focus of this paper is to develop and to describe the structure of such an analytical equation. To get a first idea about the values of the constants in that analytical equation a few test results were evaluated. But these equations consider the static rope behavior only. Due to dynamic effects in the rope while running through the loop at the bottom of a shaft, pendulousness of the tail rope occurs.
Mobile cranes are regularly operated in regions which experience ultra deep operating temperatures of down to -60?C (-76?F). In safety regulated work environments crane operations will be suspended simply because the lowest wire rope working temperature stated in the applicable standards is -40?C/F. Examples of ultra deep temperature wire rope application are shown in Figure 1.1 and 1.3. It should be noted that this paper is written in conjunction with a paper written by the co-author Ulrich Briem titled “Fatigue Behaviour of Rope Wires”, presented and published in unison with this one. In order to analyze the behaviour under ultra deep temperature conditions, tests on wire rope as well as on rope wires were carried out. In the following, static tensile and bending test results with rope and rope wires will be reported, which were carried out in conditions of down to -95?C (-139?F) as well as at room temperature. The conclusion is that the results of these tests can be adopted to crane wire rope as well.
Towards Magneto-Sensitive Elastomers Based End-Effectors for Gripping Application Technologies
(2019)
Nowadays, the demands in engineering systems become more challenging and the use of conventional materials for certain applications is not suitable. This issue encourages the investigation of novel and innovative materials in soft robotics field. A promising approach is the consideration of magneto-sensitive elastomers (MSE). These materials enable a useful adaptability responding to their mechanical properties. By applying a static magnetic field, the static and dynamic characteristics can be tuned. However, currently the knowledge about the correlations are not satisfying and the resulting material properties can only be predicted approximately with the use of time-expensive simulations regarding to the nano scale. Therefore, feasible material simulations of the description of the mechanical behavior are necessary. In this paper experimental studies of the influence of a static magnetic field on the mechanical properties and shape adaptability of MSE are presented. Furthermore, based on these results a simulation for the material behavior is executed. These results can be implemented into further simulations for various MSE exemplars.
Rodents use their mystacial vibrissae, e.g., to recognize the shape or determine the surface texture of an object. The vibrissal sensory system consists of two components: the hair shaft and the follicle-sinus complex (FSC). Both components affect the collection of information, but the impacts of the different properties are not completely clear. Borrowing the natural example, the goal is to design a powerful artificial sensor. The influence of a continuous visco-elastic support is analyzed for an artificial sensor following hypotheses about the FSC. Starting with a theoretical treatment of this scenario, the vibrissa is modeled as an Euler-Bernoulli bending beam with a partially continuous visco-elastic support. The numerical simulations are validated by experiments. Using a steel strip as a technical vibrissa and a magneto-sensitive elastomer (MSE) as representation of the artificial continuous visco-elastic support, FSC respectively, the first resonance frequency is determined.
In this work, a tensegrity structure with spatially curved members is applied as rolling locomotion system. The actuation of the structure allows a variation of the originally cylindrical shape to a conical shape. Moreover, the structure is equipped with internal movable masses to control the position of the center of mass of the structure. To control the locomotion system a reliable actuation strategy is required. Therefore, the kinematics of the system considering the nonholonomic constraints are derived in this paper. Based on the resulting insight in the locomotion behavior a feasible actuation strategy is designed to control the trajectory of the system. To verify this approach kinematic analyses are evaluated numerically. The simulation data confirm the path following due to an appropriate shape change of the tensegrity structure. Thus, this system enables a two-dimensional rolling locomotion. The use of mechanically compliant tensegrity structures in mobile robots is an attractive research topic, due to the possibility to adjust their mechanical properties reversibly during locomotion. In this paper rolling locomotion of mobile robots based on simple tensegrity structures, consisting of three compressed spatially curved members connected to a continuous net of prestressed tensional members, is discussed. Planar locomotion of these robots is induced by the movement of internal masses. The movement direction can be changed by changing the robot's shape between a cylinder and a truncated cone. The paper focuses on the description of the kinematics of these systems with respect to the shape change.
Independent component analysis (ICA), as a data driven method, has shown to be a powerful tool for functional magnetic resonance imaging (fMRI) data analysis. One drawback of this multivariate approach is, that it is naturally not convenient for analysis of group studies. Therefore various techniques have been proposed in order to overcome this limitation of ICA. In this paper a novel ICA based work-flow for extracting resting state networks from fMRI group studies is proposed. An empirical mode decomposition (EMD) is used to generate reference signals in a data driven manner, which can be incorporated into a constrained version of ICA (cICA), what helps to overcome the inherent ambiguities. The results of the proposed workflow are then compared to those obtained by a widely used group ICA approach. It is demonstrated that intrinsic modes, extracted by EMD, are suitable to serve as references for cICA to obtain typical resting state patterns, which are consistent over subjects. This novel processing pipeline makes it transparent for the user, how comparable activity patterns across subjects emerge, and also the trade-off between similarity across subjects and preserving individual features can be well adjusted and adapted for different requirements in the new work-flow.
The automotive industry employs many different kinds of axle suspension systems at modern passenger cars. Important criteria are costs, space requirements, kinematic properties, and compliance attributes. This paper illustrates that in particular the kinematic properties of a suspension system have a significant influence on the dynamics of vehicles. As a consequence, the kinematics of a suspension system must be modeled very precisely and nonlinear. Typical kinematical features of a suspension system are discussed by analyzing the most common double wishbone axle suspension system. The influence of the axle kinematics on vehicle dynamics is finally demonstrated by simulation results generated with a fully nonlinear and three-dimensional multibody vehicle model.
This paper presents a multi-mode motion system based on a compliant tensegrity structure with multiple stable equilibrium configurations. The motion system is in contact to an arbitrarily shaped rigid ground due to gravity. The movement is realized by changing successively between different equilibrium states. Depending on the strategy of changing the equilibrium configuration, different motion types occur. The reachable area of the motion system can be enlarged by adapting the motion type depending on the given environmental characteristics. Furthermore, the efficiency of the motion can be improved by choosing the most suitable motion mode. Theoretical studies regarding the change of the equilibrium states are introduced. Moreover, simulation results for the different motion modes tilting, vibration driven and jumping are illustrated. The resulting motion characteristics emphasize the advantageous adaptability of the motion system regarding to varying environmental conditions.
Often, the operating range of mobile robots is limited by environ- mental circumstances like obstacles or gaps. Therefore, an adaptation of the motion principle is required to enable an operating continuation of such robots. A jumping motion is a promising approach. This motion type allows to cross gaps or to overcome obstacles where common motion principles which bases on wheels or legs fail. However, especially during landing large forces occur as a consequence of the impact with the ground. This issue encourages the use of compliant tensegrity structures which feature a great shock resistance. In this paper a tensegrity structure with multiple equilibrium configurations is considered. The two-dimensional structure is equipped with two actuators to vary the prestress of the system. The tensegrity structure is in contact to a horizontal plane due to gravity. Two actuation strategies are derived. Beside varying the prestress state of the structure, a jump can be realized by changing the equilibrium configuration. Both actuation strategies and the corresponding motion characteristics are evaluated by numeric simulations. The results emphasize the advantageous properties of tensegrity structures for a jumping motion system. In particular, the multistabilty of the structure allows a simple actuation strategy for a reliable jumping motion.
Soccer is one of the most popular sports all around the world. It is an injurious type of sport with a focus on lower extremities and high psychological pressure during matches. The stressor is linked with injuries and an increased musculoskeletal loading. This study investigates the influence of cognitive stress on the load profile of the knee joint. Twelve professional youth soccer players performed highly dynamic runs with and without additional cognitive stress. The runs were analysed with a musculoskeletal simulation software. The data analysis shows no difference in knee joint reaction loading under additional mental stress compared to the baseline. Yet running times are significantly lower in the baseline. While there is no increase in the joint loads, the running times indicate an altered movement behaviour when the subjects are exposed to additional mental demand.
To identify the sound quality of fuel injection systems as a frontloading measure, a system test bench has been developed that simulates the structure and airborne noise emission. The setup of the system test bench includes an assembly of the acoustical relevant engine parts and an encapsulated drive for the high-pressure pump. A specific control unit enables a high variability for the operation strategy of the injection system.
The focus of this study is on the development of a methodology to analyze and optimize the sound quality of gasoline direct injectors in critical operation points by suitable active means. For this, the injection parameters in engine idle have been identified and subsequently transferred to the system test bench. Additionally, the injection parameters have been optimized acoustically and the impacts on the key functions regarding injection rating and shot-to-shot scattering of the injected fuel mass are discussed.
Virtual reality is a powerful tool for industrial applications. The article at hand addresses designers of industrial virtual environments. It summarizes key aspects to design immersive and coherent virtual environments. Furthermore, relevant influencing factors for a high quality virtual environment and tools to quantify this quality are presented. So far, a methodology to design, evaluate, and transfer knowledge from virtual environments into reality has been missing and is of high value for industrial applications. The proposed methodical approach includes the steps application analysis, technology selection and integration, design of virtual environment, evaluation of simulator quality, as well as discussion of the real-world validity. The method is shown on the example of a virtual human-robot working cell used to analyze the human perception of robot behavior during mutual assembly processes. The quality of the virtual environment is evaluated to be adequate for those purposes and the transfer of knowledge gained in virtuality on a corresponding real-world application is discussed. To the best of our knowing a system like the presented one, including full-body tracking, finger tracking, a virtual avatar and a head-mounted display has not been used for industrial use cases and human-robot cooperation before.
The increasing global competition demands continuous optimization of products and processes from companies in the process industry. Where conventional methods of Lean Management and Six Sigma reach their limits, new opportunities and challenges arise through increasing connectivity in the Industrial Internet of Things and machine learning. The majority of industrial projects do not reach the deployment or are isolated solutions, as the structures for data integration, training, deployment and maintenance of models are not established. This paper presents the conception of a reference architecture for machine learning in the process industry to support companies in implementing their own specific structures. The focus is on the development process and an exemplary implementation in the brewing industry.
The ability to synchronize expectations among human-robot teams and understand discrepancies between expectations and reality is essential for human-robot collaboration scenarios. To ensure this, human activities and intentions must be interpreted quickly and reliably by the robot using various modalities. In this paper we propose a multimodal recognition system designed to detect physical interactions as well as nonverbal gestures. Existing approaches feature high post-transfer recognition rates which, however, can only be achieved based on well-prepared and large datasets. Unfortunately, the acquisition and preparation of domain-specific samples especially in industrial context is time consuming and expensive. To reduce this effort we introduce a weakly-supervised classification approach. Therefore, we learn a latent representation of the human activities with a variational autoencoder network. Additional modalities and unlabeled samples are incorporated by a scalable product-of-expert sampling approach. The applicability in industrial context is evaluated by two domain-specific collaborative robot datasets. Our results demonstrate, that we can keep the number of labeled samples constant while increasing the network performance by providing additional unprocessed information.
Laser transmission welding is a well-known joining technology for thermoplastics, providing reliable and hermetical sealing without adhesives or particle formation. The main advantages of laser-based energy input - high precision, no additional adhesive and no particle emission - are essential for medical and optical applications. To obtain sufficient absorption in visually transparent polymers, thulium fibre lasers emitting in the polymers’ intrinsic absorption spectrum are used. Optics with high numerical aperture provide large intensity gradients inside the specimen, enabling selective fusing in the joining zone. Although the basic feasibility has already been demonstrated, the welding process lacks stability and productivity.
Aim of this work is the determination of optimized settings for a fast and reliable welding process. Thus, the interplay of process parameters as well as their impact on the seam are analysed by thermal simulations. Calculated settings are verified by welding tests with COC, PA6 and PETG, using a fixed-focus optics and a 3D laser scanner with up to 200 mm/s feed rate.
Thermo-mechanical simulation offers great opportunities to optimize welding processes of plastics. For realistic simulation, the temperature dependent mechanical properties need to be implemented from ambient temperature to temperatures above the flow temperature. Standard test methods are insufficient for characterization in the entire temperature range because close to the flow temperature the material is too soft for tensile tests and too stiff for rheometry. Therefore, an optimization strategy is developed, that determines unknown material parameters by testing in welding simulations. The unknown parameters are iteratively adjusted to minimize the mismatch between computed and measured set-paths. Thus, important process characteristics are calculated realistically, enabling the computer aided assessment of the weld quality.
This paper describes the development of a tilting locomotion system based on a compliant tensegrity structure with multiple stable equilibrium configurations. A tensegrity structure featuring 4 stable equilibrium states is considered. The mechanical model of the structure is presented and the according equations of motion are derived. The variation of the length of selected structural members allows to influence the prestress state and the corresponding shape of the tensegrity structure. Based on bifurcation analyses a reliable actuation strategy to control the current equilibrium state is designed. In this work, the tensegrity structure is assumed to be in contact with a horizontal plane due to gravity. The derived actuation strategy is utilized to generate tilting locomotion by successively changing the equilibrium state. Numerical simulations are evaluated considering the locomotion characteristics. In order to validate this theoretical approach a prototype is developed. Experiments regarding to the equilibrium configurations, the actuation strategy and the locomotion characteristics are evaluated using image processing tools and motion capturing. The results verify the theoretical data and confirm the working principle of the investigated tilting locomotion system. This approach represents a feasible actuation strategy to realize a reliable tilting locomotion utilizing the multistability of compliant tensegrity structures.
In this paper a novel approach to realize a uniaxial bidirectional vibration driven motion system with controllable direction of motion is investigated. The considered motion system bases on a tensegrity structure with multiple stable equilibrium configurations. The structure is in contact with a horizontal plane due to gravity and the actuation is realized by the harmonic change of the length of a selected member. Beside varying the actuation parameters, the direction of motion can be controlled by changing the equilibrium configuration of the tensegrity structure. In this paper the topology of the tensegrity structure and the parameter values are chosen appropriately to provide two symmetric equilibrium configurations. A change of the equilibrium state yields a novel configuration of the entire motion system which is symmetric to the original state. Utilizing the symmetry of the system the same actuation yields an opposite motion. This approach represents a reliable opportunity to control the direction of motion by changing the equilibrium state for constant actuation parameters. This paper focuses on the parameter selection and the design of the actuation of the vibration driven motion system. The working principle of the vibration driven motion system is verified by numerical simulations. This contribution represents the theoretical investigation for the further development of a prototype.
In this paper compliant multistable tensegrity structures with discrete variable stiffness are investigated. The different stiffness states result from the different prestress states of these structures corresponding to the equilibrium configurations. Three planar tensegrity mechanisms with two stable equilibrium configurations are considered exemplarily. The overall stiffness of these structures is characterized by investigations with regard to their geometric nonlinear static behavior. Dynamical analyses show the possibility of the change between the equilibrium configurations and enable the derivation of suitable actuation strategies.
Digital twins are arousing great interest in both science and industry. There are a large number of papers that demonstrate and evaluate the potential of Digital Twins in different application areas. However, it must be noted that there is still no uniform definition of Digital Twins. This paper first examines the concept of Digital Twins and highlight how they differ in level, compared with other digital models. The focus of this paper lies in the conceptual development of a digital twin in order picking systems. The described approach in the paper aims at supporting the operational control in order picking systems. Both the architectural structure and the functions, e.g. the simulation, are described in detail. Overall, this thesis shows the benefits of Digital Twins. However, some functional extensions are still needed before the full potential can be achieved.
The minitrack contains contributions with a focus on modeling and decision making in manufacturing and logistics in the context of Industry 4.0.
Cyber-physical systems integrate the real world and the virtual world. For example, customer decisions and supply disruptions which directly influence manufacturing and logistics systems require immediate decisions in terms of planning and controlling the manufacturing and logistics systems. In order to immediately respond to these dynamics, models must have the capability to support decision making in manufacturing as well as in internal and external logistics in real-time. Two of the Mintrack papers describe concepts and models for digital twins. One paper provides an adaptive scheduling framework for solving multi-objective hybrid flow shop scheduling problems and one paper investigates matrix production systems and with their requirements and impacts on logistics planning.
Maintenance strategies of drivetrains either focus on cases of failure or act preventively. The case of failure of a single element within a drivetrain can lead to the failure of the whole machinery or even an entire production line. A maintenance strategy, which focuses only on the case of failure, holds therefore economic risks. A preventive maintenance strategy can lead to replacements of intact components, because one strictly relies on fix maintenance intervals. The useful life of these replaced components is not fully utilized. A further development is the combination of one or two maintenance strategies mentioned above with condition monitoring (CM) in addition. CM monitors crucial components of the machinery. If CM indicates first signs of maloperation, unusual signals or amplitudes, one can initiate maintenance. The significance of a CM relies on the amount, placement and positioning of sensors. In reality, placement and positioning is restricted by design space and operation conditions. Current Research at HSA aims on the development of a predictive maintenance strategy, which combines CM with a realtime-capable digital twin. The latter bases on a multibody system and can be considered as a virtual CM. Within this, the CM provides boundary conditions and realtime validation for the digital twin. The virtual CM suffers no restrictions such as design space and operation conditions. It is able to predict the behavior of the drivetrain at any time, at any place, in any resolution. The data provided by the virtual CM can be used to reevaluate maximum utilization of components and therefore it can be used to set up a predictive maintenance strategy. To investigate the possibilities of this predicitve maintenance strategy further, a drivetrain test bench has been developed at HSA from scratch. The main component is a modular, three-stage gearbox which allows different setups of parameters in which e.g. center distance, bearing concepts and transmission ratio can be changed and modified. Several high fidelity sensors provide CM in realtime. The Paper will focus on the comparison of real and virtual signals and shows first results of validations in frequency domain.
This work presents a novel concept to develop mobile robots enabling crawling locomotion in tubular environment. Chain-like systems are designed by serial cascading a uniform tensegrity module. Inspired by the movement of worms in nature, an undulating shape change of the system is targeted to generate locomotion. The shape changeability of an exemplary tensegrity module due to internal actuation is examined in simulations and experiments. A prototype consisting of these tensegrity modules is manufactured and the locomotion principle is verified in experiments. Comparing to existing prototypes this approach enables an enhanced compliance due to the modular assembly of tensegrity structures.
A feasible possibility to develop planar reconfigurable mechanisms is introduced in this work. Applying the tensegrity principle to common four-bar linkages allows a controllable change between two configurations of the mechanism. These two states correspond to different working spaces which vary regarding to the kinematic and mechanical properties. Therefore, the reconfiguration of the mechanism enables two different operation modes. Hence, this kind of mechanism enables the advantageous properties of conventional linkages with an additional enhanced adaptability of the kinematic and mechanic behavior. Beside the conceptual design of such tensegrity-based mechanisms, a reconfigurable four-bar parallel linkage is considered exemplarily. Numerical simulations are evaluated focusing on the kinematic behavior and the structural mechanics of this mechanism. Especially the reconfiguration of the mechanism by changing between two different working spaces is considered. The simulation results clarify the benefit of utilizing the tensegrity principle in mechanism theory. Adding only a few members to the original linkage enables a reconfigurable mechanism with comparable complexity.
Ergonomic workplaces lead to fewer work-related musculoskeletal disorders and thus fewer sick days. There are various guidelines to help avoid harmful situations. However, these recommendations are often rather crude and often neglect the complex interaction of biomechanical loading and psychological stress. This study investigates whether machine learning algorithms can be used to predict mechanical and stress-related muscle activity for a standardized motion. For this purpose, experimental data were collected for trunk movement with and without additional psychological stress. Two different algorithms (XGBoost and TensorFlow) were used to model the experimental data. XGBoost in particular predicted the results very well. By combining it with musculoskeletal models, the method shown here can be used for workplace analysis but also for the development of real-time feedback systems in real workplace environments.
Blood flow in channels of varying diameters <500μm exhibits strong non-linear effects. Multiphase finite volume approaches are feasible, but still computationally costly. Here, the feasibility of applying convolutional neural networks for blood flow prediction in artificial lungs is investigated. Training targets are precomputed using an Eulerian two-phase approach. To match with experimental data, the interphase drag and lift, as well as intraphase shear-thinning are adapted. A recursively branching regression network and convolution/deconvolution networks with plain skip connections and densely connected skips are investigated. A priori knowledge is incorporated in the loss functional to prevent the network from learning non-physical solutions. Inference from neural networks is approximately six orders of magnitude faster than the classical finite volume approach. Even if resulting in comparably coarse flow fields, the neural network predictions can be used as close to convergence initial solutions greatly accelerating classical flow computations.
The laminated steel core of transformers is one of the main sources of the generated sound, as it is excited by different electromagnetic effects during its normal operation. If the core is excited in its eigenfrequencies, the sound generated by a transformer will increase significantly. Therefore, knowledge of the core’s eigenmodes and -frequencies in an early design stage can decrease expenses by avoiding costly modifications that might be required to avoid the sound levels exceeding the specified values after the final factory acceptance test. The current study focuses on developing a core resonance model to determine the eigenmodes and -frequencies of a transformer core. The core’s geometry was simplified to a connected-beam structure and a numerical-based approach was applied. The accuracy of the developed model was validated against finite element method (FEM), using ANSYS on a reference core model.
In the context of production and factory planning, the expansion of the factory must already be taken into account during initial planning. This results in an increase in planning complexity, as the involved planners have to know the expansion stages of the factory in the different time periods and have to evaluate concept modifications across all time periods. This paper presents an idea for a planning tool, which takes expansion stages into consideration. The data model contains all relevant information to generate a simulation model of the factory in an almost automated way. The aim is to enable factory planners to quickly investigate concept changes with the help of simulation, for example, to identify bottlenecks.
Simulation Based Approach for Reconfiguration and Ramp up Scenario Analysis in Factory Planning
(2022)
Structural changes in production entail a potential economic risk for manufacturing companies. It is necessary to identify a suitable strategy for the reconfiguration process and to continue to meet the demand during the change in the factory structure and ramp-up phase. A simulation offers the possibility to analyze different ramp-up scenarios for the factory structure and to select a suitable concept for the reconfiguration process. A discrete event simulation approach is presented that can be used to evaluate variants of structural changes and serves as a basis for deciding on a reconfiguration strategy. This approach is demonstrated using a specific production step of a plant producing hydrogen electrolyzers, the results and generalized conclusions are discussed.
During the factory acceptance test, the sound levels are measured. If the measured sound levels exceed pre-specified values, modifications on the transformer’s active part and/or tank need to be conducted. Tank resonance, if occurs, at twice main power frequency and its higher harmonics is one of the main reasons of amplifying the generated sound levels. Therefore, it is preferable to know already in the design stage about the occurrence of the tank resonance and propose reliable tank solutions. The current study presents a newly developed model for calculating the mode shapes and its corresponding eigenfrequencies of the tank.
This paper briefly presents the challenges for order control and release of multi-zone order picking systems. On the one hand, the order control must ensure that all orders are processed on time, and on the other hand, the space requirements (buffer) and the utilisation of the zones must be considered.
Within the framework of a case study, different strategies for order release were developed. The paper shortly describes the ideas of the strategies and presents results of a case-based simulative evaluation of the strategies. The findings of the simulation study are the basis for the development of a digital twin for the operational control of multi-zone picking systems.
Decision-making in supply chain management is complex because of the relations between planning tasks from different stages and planning levels. Uncertainties such as unpredictable supplier lead times and supply chain disruptions further complicate decision-making. Considering the case study of a company in printed circuit board assembly, a three-level concept is proposed that includes a decision support system. The global single-source supply network is characterized by highly variable lead times. Hence, the company maintains high inventory levels to prevent running out of stock. The decision support system considers the purchasing and scheduling decision problems in an integrated way. The prototypical implementation of the purchasing algorithm uses a genetic algorithm that recommends reorder days and order quantities using a simulation model. In addition, it evaluates the risks of the recommended solution by calculating the probability of stockouts for each order cycle.
To evaluate the performance of a ropeway in an urban environment, simulations of the dynamic passenger transport characteristics are required. Therefore, a modular simulation model for urban ropeway networks was developed, which can be flexibly adapted to any city and passenger volume. This simulation model was used to analyze the ropeway network concept of the German city Regensburg and to determine the expected operating conditions. The passenger volume, different types of persons, their occurrence probability and their destination distribution is depending on the location and daytime and can be defined for each individual station. In an initial analysis, the number of passengers currently occurring in bus traffic were projected onto the ropeway network. To enable climate-friendly and efficient operation, different strategies were developed to significantly reduce the number of gondolas. The best fitting strategies resulted in significant cost savings while passenger comfort, as represented by queue time, remained unchanged.
The Twistbeam axle suspension is a cheap and robust layout for rear axles at front wheel driven midsize cars. Appropriate models have to take the elastic deformation of the torsion beam into account. A Finite Element approach requires detailed informations of the material properties and the shape which are usually only available in the final production stage. This paper presents a lumped mass model which can easily be integrated into a multibody vehicle model and can be used in the early stage of development. An approximation by the design kinematics further reduces the complexity of the model and considers only the kinematic properties of the Twistbeam suspension. Simulations using a nonlinear and three-dimensional vehicle model with different maneuvers, such as steady-state cornering, step steer input, and driving straight ahead on random road, demonstrate the performance and, in particular, the difference of the presented Twistbeam suspension models.
The TMeasy is a tyre model suitable for vehicle handling analyses and enables easy parametrisation. Recently, a convenient interface to Modelica was implemented by DLR to support the TMeasy also for vehicle modelling in multi-physical domains. This paper focuses especially on the particular problem of reliable reproduction of the tyre’s bore torque which occurs during parking manoeuvres. It outlines the theory behind it, discusses the Modelica interface implementation, and presents the results of parameter identification which were achieved based on real experiments with DLR’s research platform ROboMObil.
Due to the complexity and the number of factors involved in factory layout planning, computers were identified as an efficient tool to support the process. However, so far no method for computer-aided layout planning has gained wide acceptance in practical application. One reason for this is that in present approaches either the user or the computer designs the layout, neglecting either the qualitative or the quantitative goals. To bridge this gap, this article introduces a concept for human-computer-integration based on evaluative feedback and inverse reinforcement learning. A key element of the concept is the interactive planning process in which user and computer alternately design and improve the layout until a satisfactory layout is found. The user evaluates the layouts according to qualitative criteria, adjusts them intuitively and specifies objectives and restrictions in an explorative way. The computer on the other hand – in form of a reinforcement algorithm – generates possible layouts and incorporates the user’s feedback into its policy. This synergy is expected to generate better results than an expert or an algorithm alone could. Furthermore, in the context of learning factories, it encourages critical thinking and allows students to develop a deeper understanding of the factors that contribute to efficient manufacturing processes. Both an architecture for the implementation is proposed and the requirements for the user interface are specified.
Internal transport systems are an essential part of intralogistics in production and distribution facilities. These are characterized by a variety of technologies as well as a multitude of interactions with other processes, such as warehouse, picking, and production processes. Therefore, resource planning and control of these systems is complex, especially for discontinuous conveyors. In this task, users can be supported by Digital Twins for decision-making, as they are suitable for investigating both future system states and possible actions. However, relevant use cases that are generally applicable across sectors as well as a generic system architecture for Digital Twins for resource planning and process control of in-plant transport systems have not yet been sufficiently investigated. In this paper, use cases are presented, relevant functions defined, and, finally, a generic functional and a logical reference architecture described. This is conducted with the design science in information systems research method together with a Systems Engineering approach. The use cases are determined at industrial partners of the research project TwInTraSys, which explores Digital Twins for the planning and control of internal transport systems. They are generalized and, thus, also applicable to other production and distribution facilities in different sectors. Further, the reference architecture can provide a basis for the successful implementation of the Digital Twin.
In the treatment of hand injuries in the context of orthopedic care, movable wrist hand orthoses are used in numerous instances. Early motion therapy is in most cases advantageous for adequate, rapid and successful long-term healing of the hand. Conventional dynamic wrist hand orthoses can only be used for movement therapy to a limited extent since they represent the wrist as a simple rotating joint and neglect the complexity of the hand movement possibilities. In this paper, a preliminary concept for dynamic wrist hand orthoses based on prestressed compliant structures is presented. The distinctive feature of this concept lies in the enabling of multiaxial motion capabilities of the human hand without applying conventional joints. According to the concept the wrist region is surrounded by a prestressed compliant structure. Besides the derivation and description of the concept, a first three-dimensional computer-aided design is shown. Additionally, the necessary steps in the development of such a novel dynamic wrist orthosis are discussed.
In the treatment of hand injuries in the context of orthopedic care, movable hand orthoses are used in many cases. Early motion therapy is in most cases advantageous for adequate, rapid, and successful long-term healing of the hand. Conventional mobile hand orthoses can only be used for movement therapy to a limited extent since they represent the wrist as a simple rotating joint and neglect the complexity of the movement possibilities of the hand. In this paper, a novel concept for movable hand orthoses based on prestressed compliant structures is presented. The advantage with this concept is that it replicates the multiaxial motion capabilities without the need for conventional joints. Besides the derivation and description of the concept, a first three-dimensional CAD design is shown. Additionally, the next planned steps in the development of such a novel dynamic hand orthosis are described.
Surgical Smoke is generated during the cauterization of tissue with high-frequency (HF) devices and consists of 95% water vapor and 5% cellular debris. When the coagulation tweezers, which are supplied with HF voltage by the HF device, touch tissue, the electric circuit is closed, and smoke is generated by the heat. In-vivo investigations are performed during tracheotomies where surgical smoke is produced during coagulation of tissue. Furthermore, in-vitro parametric studies to investigate the particle number and size distribution and the spatial distribution of surgical smoke with laser light sheet technique are conducted. With higher power of the HF device, the particles generated are larger in size and the total number of particles generated is also higher. Adding artificial saliva to the tissue shows even higher particle counts. The study by laser light sheet also confirms this. The resulting characteristic size distribution, which may include viruses and bacterial components, confirms considering the risk arising from surgical smoke. Furthermore, the experiments will provide the database for further numerical investigations.
High Spatial Resolution Tomo-PIV of the Trachea Focussing on the Physiological Breathing Cycle
(2023)
Investigations of complex patient-specific flow in the nasopharynx requires high resolution numerical calculations validated by reliable experiments. When building the validation base and the benchmark of computational fluid dynamics, an experimental setup of the nasal airways was developed. The applied optical measurement technique of tomo-PIV supplies information on the governing flow field in three dimensions.
This paper presents tomo-PIV measurements of the highly complex patient-specific geometry of the human trachea. A computertomographic scan of a person’s head builds the basis of the experimental silicone model of the nasal airways. An optimised approach for precise refractive index matching avoids optical distortions even in highly complex non-free-of-sight 3D geometries. A linear-motor-driven pump generates breathing scenarios, based on measured breathing cycles. Adjusting of the CCD cameras‘ double-frame-rate PIV-Δt enables the detailed analysis of flow structures during different cycle phases. Merging regions of interest enables high spatial resolution acquisition of the flow field.
It is generally known that project-based learning is a very important part of engineering education to connect theoretical knowledge with practical work. Students learn to apply their knowledge to real-world challenges as it is the case in their later professional life. If students are not used to project work or the scientific topic is new and relatively complex, they may be overwhelmed. The consequence is that students achieve poor results, are frustrated, and therefore learning success is low. Semi-structured projects are introduced that combine the advantages of structured experiments with projects. The project work is structured into several parts with detailed descriptions of the tasks. In the end, students get similar results to doing a free project, but the success rate is higher due to higher guidance. Therefore, these semi-structured projects are seen to be an appropriate method to guide students to learn how to do project work. The feedback from most students is very positive. Some students with no previous lab experience complained about the project work and wished for more guidance to become familiar with lab work. In sum, the student feedback is encouraging to develop semi-structured projects further.
Theoretical considerations on a 2D compliant tensegrity joint in context of a biomedical application
(2023)
In this paper, a two-dimensional compliant tensegrity joint was investigated for potential biomedical applications such as orthotics or exoskeletons. The structure consists of two compressed members connected by five compliant tensioned members. The concept is based on the tensegrity principle, which allows the realization of dynamic orthoses without conventional hinge joints. Another advantage is the adaptability to the individual needs of the patient through a suitable design of the structure and the careful selection of the characteristics of the elements. Using geometric nonlinear analysis, the mechanical behavior of the structure was investigated, focusing on mechanical compliance. The main objective was to determine the influence of the initial length and stiffness of the tensioned members and the influence of the magnitude of external forces on the overall stiffness of the movable member of the structure. The results highlight the significant impact of member parameters on the structure's stiffness and movability under varying load magnitudes. The research laid the foundation for future development of dynamic orthoses based on this structure.
Um die Leistungsfähigkeit von nachgiebigen Robotersystemen („Soft Robotics“) zu verbessern, werden immer neue Möglichkeiten zur Realisierung dieser Systeme gesucht. In vielen Anwendungen ist der Einsatz von mechanisch vorgespannten nachgiebigen Strukturen in diesen Systemen von Vorteil. Die Steifigkeit dieser Strukturen kann gezielt und gegebenenfalls reversibel variabel eingestellt werden. Die Formveränderung kann nur durch wenige Aktuatoren erzeugt werden.
Nachgiebige Tensegrity-Strukturen, die auf hochelastischen Materialien basieren, entsprechen einer speziellen Klasse von mechanisch vorgespannten Strukturen. Sie werden durch druck- und zugbelastete Segmente gebildet, wobei die druckbelasteten Segmente untereinander nicht direkt verbunden sind. Die resultierende Form dieser Strukturen wird durch ihre Vorspannung bestimmt. Weiche Roboter, die auf diesen Strukturen basieren, bieten mehrere vorteilhafte Eigenschaften, wie z. B. Faltbarkeit/Entfaltbarkeit, geringe Masse, hohes Festigkeits-Gewichts-Verhältnis und stoßdämpfende Fähigkeiten [1]. Diese Strukturen haben eine ausgeprägte Fähigkeit, sowohl ihre Form als auch ihre Steifigkeit zu verändern. In den letzten Jahren hat das Interesse an der Erforschung von Robotersystemen, die auf diesen Strukturen basieren, zugenommen. Aktuelle Arbeiten konzentrieren sich auf die Entwicklung von mobilen Robotern [2]–[7] und Manipulatoren, die auf diesen Strukturen basieren [8]–[10]. Tensegrity-Manipulatoren werden typischerweise durch Kaskadierung von gleichartigen elementaren Einheiten gebildet, die nach dem Tensegrity-Prinzip untereinander verbunden werden. Die elementaren Einheiten sind entweder selber konventionelle Tensegrity-Strukturen oder einteilige planare bzw. räumliche Strukturen. In klassischen Tensegrity-Manipulatoren werden starre Drucksegmente und nicht elastische Zugsegmente verwendet. Die Formänderung dieser Systeme wird durch Änderung der Längen ausgewählter Zugsegmente realisiert. Dem gegenübergestellt können nachgiebige Tensegrity-Manipulatoren realisiert werden, indem die Zugsegmente der Struktur eine hohe Nachgiebigkeit aufweisen. Um die mechanische Nachgiebigkeit und Formänderungsfähigkeit von diesen nachgiebigen Manipulatoren zusätzlich
zu erhöhen, ist auch der Einsatz von Tensegrity-Strukturen auf der Basis nachgiebiger Drucksegmente denkbar.
Im vorliegenden Beitrag werden zwei nachgiebige Tensegrity-Manipulatoren vorgestellt und in Hinblick auf ihre mechanischen Eigenschaften und Formänderungsfähigkeit gegenübergestellt. Sie unterscheiden sich in ihrer Topologie, in der Art der Aktuierung und auch in der mechanischen Nachgiebigkeit. Die mechanische Nachgiebigkeit des ersten Systems beruht auf der Elastizität der Zugsegmente, die Drucksegmente sind starr. Die elementaren Einheiten bilden einteilige Strukturen. Das zweite System beruht auf elementaren Einheiten, die selbst räumliche Tensegrity-Strukturen sind. In diesem System sind sowohl die Zug- als auch die Drucksegmente nachgiebig. Die Aktuierung des ersten Systems erfolgt durch Längenänderung der Zugsegmente. Im zweiten System wird die Formänderung des Gesamtsystems durch Änderung der Form der nachgiebigen Drucksegmente realisiert. Die theoretischen Untersuchungen erfolgen unter Anwendung
der statischen geometrisch nichtlinearen FE-Methode. Mit diesen Untersuchungen wird die Formveränderungsfähigkeit der beiden Systeme unter Variation ihrer Vorspannung untersucht und gegenübergestellt. Die experimentellen Untersuchungen an zwei Demonstratoren bestätigen die theoretischen Ergebnisse und zeigen die Anwendbarkeit von Systemen auf Basis dieser Strukturen als Manipulatoren auf.
In diesem Beitrag erfolgt die theoretische Untersuchung einer zweidimensionalen nachgiebigen Tensegrity-Struktur in Hinsicht auf ihre potenzielle Eignung als Basisstruktur für eine dynamische Handorthese. Translatorische und rotatorische relative Bewegungsmöglichkeiten zwischen den Drucksegmenten der Struktur sind möglich, da diese Segmente durch nachgiebige Zugsegmente miteinander verbunden sind. Die Form der Struktur und ihre Vorspannung in einer statisch stabilen Gleichgewichtskonfiguration werden mit Hilfe der Minimierung des Kräfte- und Momentenungleichgewichts, der Betrachtung der potentiellen Energie der Struktur und einem Ansatz mittels statischer Finite-Elemente-Methode (FEM) in Abhängigkeit der Segmentparameter untersucht.
This paper presents a comprehensive analysis of a three-dimensional compliant tensegrity joint structure, examining its actuation, kinematics, and response to external loads. The study investigates a baseline configuration and two asymmetric variants of the joint. The relationship between the shape parameter and the parameters of the tensioned segments is derived, enabling the mathematical description of cable lengths for joint actuation. Geometric nonlinear static finite element simulations are performed to analyze the joint's response under various load conditions. The results reveal the joint's range of motion, the effect of different stiffness configurations, and its deformation behavior under external forces. The study highlights the asymmetric nature of the joint and its potential for targeted motion restriction. These findings advance the general understanding of the behavior of the considered tensegrity joint and provide valuable insights for their design and application in soft robotic systems.
One major goal of production system design is to decide on space requirements in the plant. In this phase, detailed information about the supply chain network (e.g. which suppliers deliver which parts) is often unavailable. Nevertheless, typical decisions in supply chain management, like the definition of replenishment processes and quantities or make-or-buy decisions, impact space requirements and the capital investment in raw materials and should therefore be considered in factory and production planning. This research article proposes a simulation approach for a production simulation in which raw material replenishment is integrated to evaluate the capital investment and space requirements for raw materials.
Preliminary considerations on the form-finding of a tensegrity joint to be used in dynamic orthoses
(2024)
The rope curve line of a tensioned rope can be described by means of the catenary curve. Opposed to that, the curved line of a free bent rope cannot be described by an analytical function. Practical applications of free bending are for example at tail ropes at the bottom of shaft in rope drives with traction sheaves. The question whether the maximum diameter of rope loop is small enough for the diameter of the shaft is highly interesting. In [1] a method was presented to calculate the curved line of free bent ropes numerically by help of energy methods. An analytical description of rope curve line would be very helpful. Beginning with the structure of a rope curve line of tensioned rope (catenary curve) and considering the influence of bending stiffness, the structure of an analytical equation for the curve line of a free bent rope will be developed. The main focus of this paper is to develop and to describe the structure of such an analytical equation. To get a first idea about the values of the constants in that analytical equation a few test results were evaluated. But these equations consider the static rope behavior only. Due to dynamic effects in the rope while running through the loop at the bottom of a shaft, pendulousness of the tail rope occurs.