Defects like folds can arise using forging for the production of long flat pieces made of aluminium. A special defect is the formation of inner folds. These can be seen in the grain flow. Inner folds have a negative effect on the dynamic properties of the forged part. As a production process, forging can be divided into single-directional and multi-directional forging. The formation of inner folds was observed at the single-directional forging. By using the multi-directional forging, a forming operation working from different directions, the forming can be set variably. Thus the development of folds can be prevented. A newly developed method can help in the selection of the forming process and in determining an appropriate tool geometry. Here especially the area is adapted, where the development of inner folds occur. Therefore a calculation model was developed. It integrates a computer-aided identification of the inner folds. Using this model, a correction of the parametrically constructed forging tool is possible.
multidirectional-forging, long flat pieces, aluminium, fibre orientation
Process monitoring and the resulting increase in quality through AI are attracting increasing attention in large parts of the manufacturing industry. The possibilities of inline process monitoring of cross-wedge rolling are being investigated as part of the research of the Collaborative Research Center 1153. The aim is to develop a monitoring system that enables inline process control in order to compensate process deviations that occur during the forming process. Therefore, an algorithm is developed that can detect and classify process deviations within a few seconds and while the process is still running. An AI-based image recognition algorithm was applied as part of this research work. The process data was collected as part of a sensitivity study of the process parameters. A parameter study was used to determine optimized hyperparameters for AI modeling that enable a high prediction accuracy. The challenge of the necessary speed of the prediction was tested and validated. The evaluation of the algorithm including the generation of a picture requires 270 ms on average and is therefore fast enough to be used as preparation for process control. The investigations revealed a possibility for data augmentation that significantly increases the predictive accuracy of the models. Leave-One-Out Cross-Validation (LOOCV) was used to conclude the overall performance of the model.
Cross-wedge rolling, Hybrid components, Process monitoring, AI-based image recognition
This article examines how force sensors must be positioned to detect incorrect positioning of forging blanks. For this purpose, simulative investigations are carried out on a die. Positions for possible sensor placement are applied in a grid pattern. The recorded force values of the respective sensors are analyzed to identify those sensors that are particularly suitable for reliably detecting incorrect positioning.
industry 4.0, digitalisation, process monitoring
Aim: We explore the use of the Open Research Knowledge Graph (ORKG) as such an infrastructure by demonstrating how engineers can utilize the ORKG in innovative ways for communication and (re-)use.
Method: For a use case from the Collaborative Research Center 1153 “Tailored Forming”, we collect, extract, and analyze scientific knowledge on 10 Tailored Forming Process Chains (TFPCs) from five publications in the ORKG. In particular, we semantically describe the TFPCs, i.a., regarding their steps, manufacturing methods, measurements, and results. The usefulness of the data extraction topics, their organization, and the relevance of the knowledge described is examined by an expert consultation with 21 experts.
Results: Based on the described knowledge, we build and publish an ORKG comparison as a detailed overview for communication. Furthermore, we (re-)use the knowledge and answer eight competency questions asked by two domain experts. The validation shows a clear agreement of the 21 experts regarding the examined usefulness and relevance.
Conclusions: Our use case shows that the ORKG as a ready-to-use infrastructure with services supports researchers, including engineers, in sustainably organizing FAIR scientific knowledge. The direct use of the ORKG by engineers is feasible, so the ORKG is a promising infrastructure for innovative ways of communicating and (re-)using FAIR scientific knowledge in engineering sciences, thus advancing this research field.
Tailored forming, scientific knowledge, communication, knowledge graph
As the number of product variants continues to grow, the need for flexibility in intralogistics is becoming increasingly apparent. One potential solution to this challenge is the use of cellular automated guided vehicles, which can be variably interconnected depending on the size of the product to be transported. This article presents an optimization model for solving a vehicle routing problem for cellular automated guided vehicles. Furthermore, a recursive method is presented that determines an optimal transport sequence based on the solution of the model. The optimization model is implemented in a specially developed model environment and solved for a dynamic, illustrative use case. Subsequently, logistical target variables are evaluated in order to assess the solution of the optimization model. The exemplary application of the optimization model demonstrates the feasibility of modeling cellular transportation with automated guided vehicles and evaluating its performance based on logistical target variables.
AGV, cellular transport units, optimization model, simulation, logistical target values
This work explores the challenges of fully automating in-house goods transport in environments where industrial trucks like forklift trucks remain necessary due to undefined load carrier positions and shapes. Imitation Learning (IL) is identified as a promising solution for vehicle control in repetitive tasks, yet its application in intralogistics is challenging by the dynamic complexity of industrial trucks and the large dimensional space involved. A Robot Operating System 2 (ROS2) framework is introduced, enabling the acquisition of driving data from both simulation environments and real-world demonstrators. The study also presents a network architecture combining a Convolutional Neural Network (CNN) with a Long Short-Term Memory (LSTM) network, facilitating end-to-end learning from spatial and temporal image data. The framework's effectiveness is evaluated using a dataset of expert driving maneuvers to assess the generalization potential of the IL-trained network in vehicle control in different scenarios. The research aims to demonstrate the utility of the proposed framework for data acquisition and validate IL as a control approach for industrial trucks that require generalization.
Imitation Learning, industrial truck automation, intralogistics, ROS2, load handling
Constantly increasing production volumes and new challenges in production environmentswith the same amount of space are forcing manufacturing companies to deal with the planning of production layouts. The problem often is a non-existent or outdated production layout plan. Autonomous multicopters can help by simplifying layout capture. That's why a voxel-based simulation is investigated to develop and train path planning algorithms with and without artificial intelligence. First, the temporal behavior and the resource utilization of the simulation is investigated. Then, the time factor of simulation is compared to real time and what advantages companies and developers have when using it.
UAS, digital twin, simulation, voxel-based, layout design
It was investigated how a grain refinement can be introduced into a cylindrical rolled piece by means of cross rolling in a flat-jaw design. For this purpose, a non-round shape was rolled in and out again. A theoretical preliminary investigation was used to define a suitable parameter field for experimental evaluation. Metallographic investigations showed that cross-rolling had a positive effect on the microstructure, and IPH will inform the client immediately if it becomes apparent that the estimated costs will be exceeded. The execution of work that leads to the estimated expenditure being exceeded shall only take place after consultation with the client.
Cross-Wedge Rolling, fine grain
A major advantage of flashless precision forging is the saving of resources by avoiding excess material. Especially materials with good flow properties, such as aluminum, sometimes lead to the formation of thin flash. Seals have been developed and experimentally tested to prevent thin flash, i.e. the flow of material into tool gaps. The study presented shows the effectiveness of different sealing materials and the ideal sealing geometry.
thin flash, Sealing concept, precision forging, forming technology, process optimization
It was investigated how a grain refinement can be introduced into a cylindrical rolled part with cross rolling in a flatjaw design. For this purpose, a non-circular shape was rolled in and out again. A theoretical preliminary investigation was used to define a suitable parameter field for experimental evaluation. Metallographic investigations showed that cross rolling had a positive effect on the microstructure.
process design, forming technology
This article examines the use of point clouds as a geometric data basis for factory planning and compares different mapping techniques for generating these point clouds. Data and information acquisition is a crucial step in factory planning and thus in developing efficient production processes. In this context, different mapping techniques are analysed: photogrammetry (using drones and action cameras) and LiDAR scans (performed both from drones and from the ground).
The methodology and results of this investigation are discussed in detail, highlighting the advantages and disadvantages of each mapping technique. The focus is on comparing the generated point clouds in terms of completeness, recognisability and geometric tolerance. This comparison provides valuable insights into which technique is best suited for the data acquisition of factory planning. The outlook of this paper includes the further development of recording techniques, particularly with regard to autonomously flying drones. In the future, these could enable more efficient and precise data acquisition for factory planning and thus further strengthen the basis for optimising production processes.
Drone, Photogrammetry, LiDAR, Point cloud, Factory planning, Data acquisition
Around half of the currently 30,000 active wind turbines in Germany will reach the end of their service life by 2030, which is generally defined by the manufacturer as 20 years of operation. The most common strategy for the subsequent use of a wind farm is repowering, provided this is (legally) possible at the respective location. One option for dealing with old turbines is to resell them. At the time of repowering, in Germany after an average of around 17 years, the wind turbines usually still have a remaining operating time of several years before critical parts such as generators fail.
This article presents a machine learning model for predicting the resale value of used wind turbines. This model can be used to approximately predict the resale value of comparable wind turbines based on certain input parameters such as the power output or the age of the wind turbines. The model was trained using an adjusted data set from an online trading platform for wind turbines. The necessary pre-processing steps such as the removal of extreme outlier values and the addition or replacement of missing or incorrect wind turbinespecific data from a second data source using a self-developed matching algorithm are presented. Finally, the prediction accuracy of different ML algorithms is tested using test data to find the best method for predicting the resale value of wind turbines.
Renewable energies, wind turbines, resale values, machine learning, data science
The article addresses a method for generating project schedules for factory relocations based on a planned layout concept in reorganisation projects. The layout is modelled in a cell grid with cells of uniform edge length. The factory objects are arranged in this grid for both the actual and the target layout state. Further input parameters relate to the required time and personnel resources according to several operations. A two-stage optimisation algorithm is presented, which first checks a given solution for layout feasibility and then generates and solves a project scheduling problem on this basis. Accordingly, elements of the facility layout problem are integrated into a resource constrained project scheduling problem. The process steps of generating and evaluating of the project schedule are further embedded in a genetic algorithm, which successively improves the solution. The project schedules for relocation are evaluated through a combination of the resulting project duration and the downtimes of all factory objects. The aim of the optimisation is to minimise both objective values considering a weighting factor. The article concludes by validating the method using a practical example.
factory planning, relocation planning, reorganisation, project scheduling, project planning
Increasing the service life and process reliability of systems plays an important role in terms of sustainable and economical production. Especially in the field of energy-intensive bulk forming, low scrap rates and long tool lifetimes are business critical. This article describes a modular method for AI-supported process monitoring during hot forming within a screw press. With this method, the following deviations can be detected in an integrated process: the height of the semi-finished product, the positions of the die and the position of the semi-finished product. The method was developed using the CRISP-DM standard. A modular sensor concept was developed that can be used for different screw presses and dies. Subsequently a hot forming-optimized test plan was developed to examine individual and overlapping process deviations. By applying various methods of artificial intelligence, a method for process-integrated detection of process deviations was developed. The results of the investigation show the potential of the developed method and offer starting points for the investigation of further process parameters.
Process monitoring, Wear, Hot forming, Predictive maintenance, Quality management
Wear due to thermal and mechanical stresses is one of the major causes of forging die failure. The assessment of die condition and the associated die life is usually based on experience. This paper presents a method to objectively predict the remaining life of a forging die. With this method a prediction based on optical measurements can be calculated. Practical tests show the possible applications. In addition, force measurements are performed and analyzed to determine how wear affects the force distribution in the die. The assessment based on optical measurements allows objective statements about the remaining tool life of forging dies. The analysis of the force measurements shows potential for predicting tool life but needs further investigation.
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Process monitoring, wear, optical measurements, force measurement
A continuously growing number of product variants increases the demands on the flexibility of intralogistics transportation. One way to achieve greater flexibility is the use of cellular automated guided vehicles, which can be variably interconnected depending on the size of the product to be transported. This article explains the characteristics of cellular automated guided vehicles and the relationships between influencing variables of the cellular transport system and economic and logistical target variables.
Intralogistics, automated guided vehicles, cellular transport units
The resilience of a supplier is a fundamental factor in the design of supply chains. In supplier selection, resilience is not yet fully taken into account in the evaluation process. As part of a research project, the aim is to create a basis for this and thus integrate resilience as an evaluation criterion into the supplier selection process. The article aims to create an understanding of the various success factors of resilient supply chains.
Resilience, sustainability, supply chain management, risk management
Twelve interviews were conducted with IT system users and providers in order to investigate the adaptability of IT systems in manufacturing companies. A methodical evaluation of the interviews made it possible to identify factors that influence the service life of IT systems. The evaluation shows that, in addition to the technical characteristics, human and organizational aspects in particular are decisive for the long-term use of IT systems.
Information management, people and technology, software
Hybrid components, made of multiple materials, can meet the increasing demands for lightweight construction and functional integration in the automotive and aircraft industry. Hybrid semi-finished components are produced by applying a high-alloy cladding to a low-alloy base material before hot-forming and machining the workpiece. Throughout this process chain, workpiece deviations in the form of material distribution and material properties can occur that influence the component’s lifetime. This paper investigates whether such workpiece deviations can be detected within the process chain by analyzing process signals obtained from subsequent process steps. For this purpose, artificial workpiece deviations were introduced to hybrid semi-finished workpieces made of C22.8/X45CrSi9-3. Then, process signals during forming and machining were analyzed to determine their sensitivity to the artificial deviations. The results revealed that deviations in cladding size can be effectively monitored using signals from both forming and machining. Cladding position deviations can only be detected during machining, while forming signals are more responsive to detecting the introduced hardness deviations of approx. 100 HV0.1.
Laser hot-wire cladding, Cross-wedge rolling, Machining, Monitoring, Workpiece deviations
In the research project “AutoPress”, the IPH – Institut für Integrierte Produktion Hannover gGmbH and Jobotec GmbH are jointly striving to develop an automated process control of screw presses. By retrofitting and applying an optimization algorithm, the energy demand is to be reduced and the component quality increased.
digitalization, forming technology, production technology
By creating ultrafine-grained microstructures, the properties of a material can be improved. Ultrafine-grained microstructure has high strength combined with high ductility. This paper describes how a rolling process can be used to influence the microstructure of a material. The process is investigated by simulation and process windows are determined using statistical design of experiments for practical testing.
Grain refinement, flat-jaw rolling, non-circular rolling, finite element method
