Although factory planning is widely recognized as a way to significantly enhance manufacturing productivity, the associated costs in terms of time and money can be prohibitive. In this paper, we present a solution to this challenge through the development of a Software-in-the-loop (SITL) framework that leverages an Unmanned Aircraft System (UAS) in an autonomous capacity. The framework incorporates simulated sensors, a UAS, and a virtual factory environment. Moreover, we propose a Deep Reinforcement Learning (DRL) agent that is capable of collision avoidance and exploration using the Dueling Double Deep Q-Network (3DQN) with prioritized experience replay.
Artificial Intelligence, reinforcement learning, Unmanned Aircraft Systems
A new process chain for the manufacturing of load-adapted hybrid components is presented. The "Tailored Forming” process chain consists of a deposition welding process, hot forming, machining and an optional heat treatment. This paper focuses on the combination of laser hot-wire cladding with subsequent hot forming to produce hybrid components. The applicability is investigated for different material combinations and component geometries, e.g. a shaft with a bearing seat or a bevel gear. Austenitic stainless steel AISI 316L and martensitic valve steel AISI HNV3 are used as cladding materials, mild steel AISI 1022M and case hardening steel AISI 5120 are used as base materials. The resulting component properties after laser hot-wire cladding and hot forming such as hardness, microstructure and residual stress state are presented. In the cladding and the heat-affected zone, the hot forming process causes a transformation from a welding microstructure to a fine-grained forming microstructure. Hot forming significantly affects the residual stress state in the cladding the resulting residual stress state depends on the material combination.
laser hot-wire cladding, cladding, hot forming, residual stress, tailored forming
Geometry, design, and processing in addition to the thermoelectric material properties have a significant influence on the economic efficiency and performance of thermoelectric generators (TEGs). While conventional BULK TEGs are elaborate to manufacture and allow only limited variations in geometry, printed TEGs are often restricted in their application and processing temperature due to the use of organic materials. In this work, a proof-of-concept for fabricating modular, customizable, and temperature-stable TEGs is demonstrated by applying an alternative laser process. For this purpose, low temperature cofired ceramics substrates were coated over a large area, freely structured and cut without masks by a laser and sintered to a solid structure in a single optimized thermal post-processing. A scalable design with complex geometry and large cooling surface for application on a hot shaft was realized to prove feasibility.
thermoelectric, printed electronic, laser structuring, printed ceramics, spray coating
The digital development of spaces within the city of Hannover by means of a digital image makes it possible to cover the usage needs of spaces more efficiently and in line with the requirements. The crea-tion of a digital image, which develops new possibilities for access to public space, requires the use of different sensors such as LiDAR sensors and tracking cameras. In order to select suitable sensors that can be used with UAS, the requirements for the overall system are first defined, which are derived in functional requirements for the sensor technology. Subsequently, the degree of fulfilment of the functional requirements by the different sensors
5G, UAS, digital image, digital twin
The temporally and spatially accurate display of information in augmented reality (AR) systems is essential for immersion and operational reliability when using the technology. We developed an assistant system using a head-mounted display (HMD) to hide visual restrictions on forklifts. We propose a method to evaluate the accuracy and latency of AR systems using HMD. For measuring accuracy, we compare the deviation between real and virtual markers. For latency measurement, we count the frame difference between real and virtual events. We present the influence of different system parameters and dynamics on latency and overlay accuracy.
augmented reality, image processing, driver assistance system, forklift trucks
Additive manufacturing enables the economical production of complex components with a high degree of customization. Therefore, the medical industry is using the advantages of additive manufacturing to produce individualized medical devices. Medical devices are subject to special quality control requirements that additive manufacturing processes do not meet yet. This article deals with the introduction of an in situ process monitoring concept using the example of fused deposition modeling. The process monitoring is carried out by a quality model, which accesses the data of a self-developed sensor concept integrated in the printer. This data is analyzed using a machine learning pipeline to predict process and product quality. Thereby, the machine learning pipeline consist of several sequential steps, ranging from data extraction and preprocessing to model training and deployment. The procedure presented for ensuring print quality forms a basis for the production of safety-relevant components in batch size one and extends conventional quality assurance methods in additive manufacturing.
additive manufacturing, quality monitoring, fused deposition modeling, artificial intelligence
Factory planning can increase the productivity of manufacturing significantly, though the process is expensive when it comes to cost and time. In this paper, we propose an Unmanned Aerial Vehicle (UAV) framework that accelerates this process and decreases the costs. The framework consists of a UAV that is equipped with an IMU, a camera and a LiDAR sensor in order to navigate and explore unknown indoor environments. Thus, it is independent of GNSS and solely uses on-board sensors. The acquired data should enable a DRL agent to perform autonomous decision making, applying a reinforcement learning approach. We propose a simulation of this framework including several training and testing environments, that should be used for developing a DRL agent.
drone, UAS, deep reinforcement learning
In this paper, objective functions for the optimisation of modular conveyor systems will be introduced. Modular conveyor systems consist of conventional as well as modular conveyor hardware, which are arranged in form of matrix-like layouts. The aim of an ongoing research project is to provide small and medium-sized enterprises with a user-friendly decision support for the selection and planning of modular conveyor systems. For this purpose, the conveyor systems should be evaluated according to the objectives throughput and space requirement. Therefore, mathematical equations have been developed, which enable a fast and precise evaluation of layouts. The paper focuses mainly on the efficient calculation of the throughput. The result quality of the evaluation equations regarding the throughput was proven by a simulation of example systems.
modular conveyor, conveyor system evaluation, throughput analysis, layout optimisation, logistics
Tailored forming is used to produce hybrid components in which the materials used are locally adapted to the diferent types of physical, chemical and tribological requirements. In this paper, a Tailored Forming process chain for the production of a hybrid shaft with a bearing seat is investigated. The process chain consists of the manufacturing steps laser hot-wire cladding, cross-wedge rolling, turning and deep rolling. A cylindrical bar made of mild steel C22.8 is used as the base material, and a cladding of the martensitic valve steel X45CrSi9-3 is applied in the area of the bearing seat to achieve the strength and hardness required. It is investigated how the surface and subsurface properties of the hybrid component, such as hardness, microstructure and residual stress state, change within the process chain. The results are compared with a previous study in which the austenitic stainless steel X2CrNiMo19-12 was investigated as a cladding material. It is shown that the residual stress state after hot forming depends on the thermal expansion coefcients of the cladding material.
Tailored forming, Residual stress, Laser hot-wire cladding, Deep rolling, Hybrid Components
The Tailored Forming process chain is used to manufacture hybrid components and consists of a joining process or Additive
Manufacturing for various materials (e.g. deposition welding), subsequent hot forming, machining and heat treatment. In
this way, components can be produced with materials adapted to the load case. For this paper, hybrid shafts are produced by
deposition welding of a cladding made of X45CrSi9-3 onto a workpiece made from 20MnCr5. The hybrid shafts are then
formed by means of cross-wedge rolling. It is investigated, how the thickness of the cladding and the type of cooling after
hot forming (in air or in water) afect the properties of the cladding. The hybrid shafts are formed without layer separation.
However, slight core loosening occurres in the area of the bearing seat due to the Mannesmann efect. The microhardness
of the cladding is only slightly efected by the cooling strategy, while the microhardness of the base material is signifcantly
higher in water cooled shafts. The microstructure of the cladding after both cooling strategies consists mainly of martensite.
In the base material, air cooling results in a mainly ferritic microstructure with grains of ferrite-pearlite. Quenching in water
results in a microstructure containing mainly martensite.
laser hot-wire cladding, cross-wedge rolling, hybrid components, cladding
This article presents a method for superimposing vision constraints based on the principle of augmented reality. The method is based on an overlay of the actual operator's field of view with information from a reconstructed scene. The reconstructed scene is superimposed as a hologram only over the vision-restricting components. The presented method is divided into position determination, data transmission and visualization. These software components are presented in detail. In view of the later use of the system in an industrial truck, the real-time capability of the data transmission, the accuracy of the visualization and the robustness of the position determination are also investigated.
augmented reality, driver assistance system, forklift trucks, image processing, obstacle detection
The manufacturing technology of thermoelectric materials is laborious and expensive often including complex and time-intensive preparation steps. In this work, a laser sintering process of the oxide-based thermoelectric material Ca3Co4O9 is investigated. Samples based on spray-coated Ca3Co4O9 were prepared and subsequently sintered under various laser parameters and investigated in terms of the microstructure and thermoelectric properties. Here, the combination of laser sintering and subsequent thermal sintering proved to be a promising concept for the preparation of thermoelectric films. Laser sintering can thus make a great contribution in improving the processing of thermoelectric materials, especially when films are applied that cannot be sintered under pressure.
thermoelectric, laser sintering
Additive manufacturing has established itself in medical technology, where complex and patient-specific products are manufactured. Since additive manufacturing processes are sensitive to changes in process parameters and environmental conditions, quality assurance is a key factor for production. This paper presents the approach for in-situ process monitoring in additive material extrusion.
Additive Manufacturing, 3D printing, Fused Deposition Modeling, quality control, machine learning
In order to enable even complex processes such as the joining of additively manufactured components by laser in production in a quality-assured way, the existence of specialist knowledge in companies is absolutely essential. To bundle this knowledge for process control and monitoring independently of personnel, an expert system is being developed in the IGF research project of FQS - Forschungsgemeinschaft Qualität e.V. entitled "Quality assurance in laser beam welding of additively manufactured thermoplastic components (QualLa)". By integrating specialist knowledge into the expert system, this knowledge can be secured in companies in the long term and processes can continuously be carried out with high qualitative standards.
additive manufacturing, 3D printing, FDM, laser transmission welding, laser beam welding
Qualitative uncertainties are a key challenge for the further industrialization of additive manufacturing. To solve this challenge, methods for measuring the process states and properties of parts during additive manufacturing are essential. The subject of this review is in-situ process monitoring for material extrusion additive manufacturing. The objectives are, first, to quantify the research activity on this topic, second, to analyze the utilized technologies, and finally, to identify research gaps. Various databases were systematically searched for relevant publications and a total of 221 publications were analyzed in detail. The study demonstrated that the research activity in this field has been gaining importance. Numerous sensor technologies and analysis algorithms have been identified. Nonetheless, research gaps exist in topics such as optimized monitoring systems for industrial material extrusion facilities, inspection capabilities for additional quality characteristics, and standardization aspects. This literature review is the first to address process monitoring for material extrusion using a systematic and comprehensive approach.
Material extrusion, Fused deposition modeling, Process monitoring, Sensor technology, Research gaps
The machine learning based method for layout optimization of smallscale modular conveyor systems, which is developed within a research project at IPH – Institut für Integrierte Produktion Hannover gGmbH, provides SMEs a decision support, which enables them to execute complex layout planning independently. In addition, the machine learning method is intended to reduce the cost and time required for planning and to improve the quality of the solution compared to manual layout design.
Small-scale modular conveyors, conveyor systems, machine learning, artificial intelligence
Factory planning is an important tool for
manufacturing companies to raise their efficiency and to
maintain their competitiveness by changing market or
customer requirements. A special challenge is the acquisition
of layout data and the processing of this data in suitable
planning tools. Current approaches still measure manually
or have to transfer acquired data from laser scanners by
hand into planning tools, which leads to a high effort and
error proneness.
This paper presents a holistic concept for automated
and systematic data acquisition and processing for factory
planning processes.
3D factory planning, automated drone flight, point cloud processing, 3D layout scan
In this article, a method for automatic visual obstruction detection and masktype congruent visual obstruction compensation, based on the principal of augmented reality, is presented. The method is based on the superposition of a simulated operator’s field of view with information from a scene reconstructed by two RGB-Cameras. These cameras are arranged in a way that they can record the scene information be-hind the view restriction. Besides the presentation of the test rig, a detailed presentation of the image pro-cessing software is given. With a view to the later use of the system in a forklift truck, the real-time capa-bility of the system will be tested and optimization possibilities will be discussed.
augmented reality, driver assistance system, forklift trucks, image processing, obstacle detection
The service life of rolling contacts is dependent on many factors. The choice of materials in particular has a major influence on when, for example, a ball bearing mayfail.Within an exemplary process chain for the production of hybrid high-performance components through tailored forming, hybrid solid components made of at least two different steel alloys are investigated. The aim is to create parts that have improved properties compared to monolithic parts of the same geometry. In orderto achievethis, several materials are joined prior to a forming operation. In this work, hybrid shafts created by either plasma(PTA)orlaser metal deposition (LMD-W) welding are formed via cross-wedge rolling(CWR)to investigate the resulting thickness of the material deposited in the area of the bearing seat. Additionally,finite element analysis (FEA)simulations of the CWRprocessare compared with experimental CWR results to validate the coating thickness estimation done via simulation. This allows for more accurate predictionsofthe cladding materialgeometry after CWR,and the desired welding seam geometrycan be selected by calculating the cladding thicknessvia CWR simulation.
Cross-Wedge Rolling, Forming, hybrid, tailored forming
Processing technology to improve the manufacturing of thermoelectric generators (TEGs) is a growing field of research. In this paper, an adaptable and scalable process comprising spray-coating and laser structuring for fast and easy TEG manufacturing is presented. The developed process combines additive and subtractive processing technology towards an adaptable ceramic-based TEG, which is applicable at high temperatures and shows a high optimization potential. As a prototype, a TEG based on Ca3Co4O9 (CCO) and Ag on a ceramic substrate was prepared. Microstructural and thermoelectric characterization is shown, reaching up to 1.65 μW cm−2 at 673 K and a ΔT of 100 K. The high controllability of the developed process also enables adaptation for different kinds of thermoelectric materials.
thermoelectric, laser structuring
