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Modellfabrik im Zeichen der Automatisierungstechnik / Gall, Jan ; Enning, Manfred ; Abel, Dirk
(2008)
We present an automated pipeline for the generation of synthetic datasets for six-dimension (6D) object pose estimation. Therefore, a completely automated generation process based on predefined settings is developed, which enables the user to create large datasets with a minimum of interaction and which is feasible for applications with a high object variance. The pipeline is based on the Unreal 4 (UE4) game engine and provides a high variation for domain randomization, such as object appearance, ambient lighting, camera-object transformation and distractor density. In addition to the object pose and bounding box, the metadata includes all randomization parameters, which enables further studies on randomization parameter tuning. The developed workflow is adaptable to other 3D objects and UE4 environments. An exemplary dataset is provided including five objects of the Yale-CMU-Berkeley (YCB) object set. The datasets consist of 6 million subsegments using 97 rendering locations in 12 different UE4 environments. Each dataset subsegment includes one RGB image, one depth image and one class segmentation image at pixel-level.
Numerical algorithms with C
(1996)
Numerik-Algorithmen : Verfahren, Beispiele, Anwendungen. - 9., vollst. überarb. und erw. Aufl.
(2005)
Fortran 90 mit Fortran 95
(1996)
Proteins are important ingredients in food and feed, they are the active components of many pharmaceutical products, and they are necessary, in the form of enzymes, for the success of many technical processes. However, production can be challenging, especially when using heterologous host cells such as bacteria to express and assemble recombinant mammalian proteins. The manufacturability of proteins can be hindered by low solubility, a tendency to aggregate, or inefficient purification. Tools such as in silico protein engineering and models that predict separation criteria can overcome these issues but usually require the complex shape and surface properties of proteins to be represented by a small number of quantitative numeric values known as descriptors, as similarly used to capture the features of small molecules. Here, we review the current status of protein descriptors, especially for application in quantitative structure activity relationship (QSAR) models. First, we describe the complexity of proteins and the properties that descriptors must accommodate. Then we introduce descriptors of shape and surface properties that quantify the global and local features of proteins. Finally, we highlight the current limitations of protein descriptors and propose strategies for the derivation of novel protein descriptors that are more informative.
Laser-based Additive Manufacturing (AM) processes for the use of metals out of the powder bed have been investigated profusely and are prevalent in industry. Although there is a broad field of application, Laser Powder Bed Fusion (LPBF), also known as Selective Laser Melting (SLM) of glass is not fully developed yet. The material properties of glass are significantly different from the investigated metallic material for LPBF so far. As such, the process cannot be transferred, and the parameter limits and the process sequence must be redefined for glass. Starting with the characterization of glass powders, a parameter field is initially confined to investigate the process parameter of different glass powder using LPBFprocess. A feasibility study is carried out to process borosilicate glass powder. The effects of process parameters on the dimensional accuracy of fabricated parts out of borosilicate and hints for the post-processing are analysed and presented in this paper.
In the face of the current trend towards larger and more complex production tasks in the SLM process and the current limitations in terms of maximum build space, the welding of SLM components to each other or to conventionally manufactured parts is becoming increasingly relevant. The fusion welding of SLM components made of 316L has so far been rarely investigated and if so, then for highly specialised laser welding processes. When welding with industrial gas welding processes such as MIG/MAG or TIG welding, distortions occur which are associated with the resulting residual stresses in the components. This paper investigates process-side influencing factors to avoid resulting residual stresses in SLM components made of 316L. The aim is to develop a strategy to build up SLM components as stress-free as possible in order to join them as profitably as possible with a downstream welding process. For this purpose, influencing parameters such as laser power, scan speed, but also scan vector length and different scan patterns are investigated with regard to their influence on residual stresses.
The thermal conductivity of components manufactured using Laser Powder Bed Fusion (LPBF), also called Selective Laser Melting (SLM), plays an important role in their processing. Not only does a reduced thermal conductivity cause residual stresses during the process, but it also makes subsequent processes such as the welding of LPBF components more difficult. This article uses 316L stainless steel samples to investigate whether and to what extent the thermal conductivity of specimens can be influenced by different LPBF parameters. To this end, samples are set up using different parameters, orientations, and powder conditions and measured by a heat flow meter using stationary analysis. The heat flow meter set-up used in this study achieves good reproducibility and high measurement accuracy, so that comparative measurements between the various LPBF influencing factors to be tested are possible. In summary, the series of measurements show that the residual porosity of the components has the greatest influence on conductivity. The degradation of the powder due to increased recycling also appears to be detectable. The build-up direction shows no detectable effect in the measurement series.
Application of polymers in textile reinforced concrete : from the interface to construction elements
(2006)
Composite improvement of textile reinforced concrete by polymeric impregnation of the textiles
(2006)
Mikrokleben
(2005)
Additive Manufacturing (AM) of metallic workpieces faces a continuously rising technological relevance and market size. Producing complex or highly strained unique workpieces is a significant field of application, making AM highly relevant for tool components. Its successful economic application requires systematic workpiece based decisions and optimizations. Considering geometric and technological requirements as well as the necessary post-processing makes deciding effortful and requires in-depth knowledge. As design is usually adjusted to established manufacturing, associated technological and strategic potentials are often neglected. To embed AM in a future proof industrial environment, software-based self-learning tools are necessary. Integrated into production planning, they enable companies to unlock the potentials of AM efficiently. This paper presents an appropriate methodology for the analysis of process-specific AM-eligibility and optimization potential, added up by concrete optimization proposals. For an integrated workpiece characterization, proven methods are enlarged by tooling-specific figures.
The first stage of the approach specifies the model’s initialization. A learning set of tooling components is described using the developed key figure system. Based on this, a set of applicable rules for workpiece-specific result determination is generated through clustering and expert evaluation. Within the following application stage, strategic orientation is quantified and workpieces of interest are described using the developed key figures. Subsequently, the retrieved information is used for automatically generating specific recommendations relying on the generated ruleset of stage one. Finally, actual experiences regarding the recommendations are gathered within stage three. Statistic learning transfers those to the generated ruleset leading to a continuously deepening knowledge base. This process enables a steady improvement in output quality.
Improving the Mechanical Strength of Dental Applications and Lattice Structures SLM Processed
(2020)
To manufacture custom medical parts or scaffolds with reduced defects and high mechanical characteristics, new research on optimizing the selective laser melting (SLM) parameters are needed. In this work, a biocompatible powder, 316L stainless steel, is characterized to understand the particle size, distribution, shape and flowability. Examination revealed that the 316L particles are smooth, nearly spherical, their mean diameter is 39.09 μm and just 10% of them hold a diameter less than 21.18 μm. SLM parameters under consideration include laser power up to 200 W, 250–1500 mm/s scanning speed, 80 μm hatch spacing, 35 μm layer thickness and a preheated platform. The effect of these on processability is evaluated. More than 100 samples are SLM-manufactured with different process parameters. The tensile results show that is possible to raise the ultimate tensile strength up to 840 MPa, adapting the SLM parameters for a stable processability, avoiding the technological defects caused by residual stress. Correlating with other recent studies on SLM technology, the tensile strength is 20% improved. To validate the SLM parameters and conditions established, complex bioengineering applications such as dental bridges and macro-porous grafts are SLM-processed, demonstrating the potential to manufacture medical products with increased mechanical resistance made of 316L.
Die Fallstudie FAYMONVILLE beschäftigt sich damit, wie es dem Familienunternehmen Faymonville aus Ostbelgien gelungen ist, sich zu einem der führenden Hersteller in seiner Branche zu entwickeln. Die gezielte Identifizierung neuer Märkte, die Fokussierung auf die relevanten Kundenbedürfnisse und eine konsistente Produktpolitik mit einem abgestimmten Fertigungskonzept legen die Grundsteine für den Erfolg. Das vorliegende Fallbeispiel zeigt anschaulich, wie es gelingen kann, den prinzipiellen Widerspruch zwischen wirtschaftlicher und kundenindividueller Fertigung erfolgreich aufzulösen.
The recent amendment to the Ethernet physical layer known as the IEEE 802.3cg specification, allows to connect devices up to a distance of one kilometer and delivers a maximum of 60 watts of power over a twisted pair of wires. This new standard, also known as 10BASE-TIL, promises to overcome the limits of current physical layers used for field devices and bring them a step closer to Ethernet-based applications. The main advantage of 10BASE- TIL is that it can deliver power and data over the same line over a long distance, where traditional solutions (e.g., CAN, IO-Link, HART) fall short and cannot match its 10 Mbps bandwidth. Due to its recentness, IOBASE- TIL is still not integrated into field devices and it has been less than two years since silicon manufacturers released the first Ethernet-PHY chips. In this paper, we present a design proposal on how field devices could be integrated into a IOBASE-TIL smart switch that allows plug-and-play connectivity for sensors and actuators and is compliant with the Industry 4.0 vision. Instead of presenting a new field-level protocol for this work, we have decided to adopt the IO-Link specification which already includes a plug-and-play approach with features such as diagnosis and device configuration. The main objective of this work is to explore how field devices could be integrated into 10BASE-TIL Ethernet, its adaption with a well-known protocol, and its integration with Industry 4.0 technologies.
The implementation of IO-Link in the automation industry has increased over the years. Its main advantage is it offers a digital point-to-point plugand-play interface for any type of device or application. This simplifies the communication between devices and increases productivity with its different features like self-parametrization and maintenance. However, its complete potential is not always used.
The aim of this paper is to create an Arduino based framework for the development of generic IO-Link devices and increase its implementation for rapid prototyping. By generating the IO device description file (IODD) from a graphical user interface, and further customizable options for the device application, the end-user can intuitively develop generic IO-Link devices. The peculiarity of this framework relies on its simplicity and abstraction which allows to implement any sensor functionality and virtually connect any type of device to an IO-Link master. This work consists of the general overview of the framework, the technical background of its development and a proof of concept which demonstrates the workflow for its implementation.
The development of protype applications with sensors and actuators in the automation industry requires tools that are independent of manufacturer, and are flexible enough to be modified or extended for any specific requirements. Currently, developing prototypes with industrial sensors and actuators is not straightforward. First of all, the exchange of information depends on the industrial protocol that these devices have. Second, a specific configuration and installation is done based on the hardware that is used, such as automation controllers or industrial gateways. This means that the development for a specific industrial protocol, highly depends on the hardware and the software that vendors provide. In this work we propose a rapid-prototyping framework based on Arduino to solve this problem. For this project we have focused to work with the IO-Link protocol. The framework consists of an Arduino shield that acts as the physical layer, and a software that implements the IO-Link Master protocol. The main advantage of such framework is that an application with industrial devices can be rapid-prototyped with ease as its vendor independent, open-source and can be ported easily to other Arduino compatible boards. In comparison, a typical approach requires proprietary hardware, is not easy to port to another system and is closed-source.
Sensor positioning and thermal model for condition monitoring of pressure gas reservoirs in vehicles
(2018)
Tribological performance of biodegradable lubricants under different surface roughness of tools
(2019)
The fourth industrial revolution introduces disruptive technologies to production environments. One of these technologies are multi-agent systems (MASs), where agents virtualize machines. However, the agent's actual performances in production environments can hardly be estimated as most research has been focusing on isolated projects and specific scenarios. We address this gap by implementing a highly connected and configurable reference model with quantifiable key performance indicators (KPIs) for production scheduling and routing in single-piece workflows. Furthermore, we propose an algorithm to optimize the search of extrema in highly connected distributed systems. The benefits, limits, and drawbacks of MASs and their performances are evaluated extensively by event-based simulations against the introduced model, which acts as a benchmark. Even though the performance of the proposed MAS is, on average, slightly lower than the reference system, the increased flexibility allows it to find new solutions and deliver improved factory-planning outcomes. Our MAS shows an emerging behavior by using flexible production techniques to correct errors and compensate for bottlenecks. This increased flexibility offers substantial improvement potential. The general model in this paper allows the transfer of the results to estimate real systems or other models.
The increasing digitalization brings new opportunities but also puts new challenges to modern industrial systems. Software agents are one of the key technologies towards self-optimizing factories and are currently used to address the needs of cyber-physical production systems (CPPS). However their interplay in industrial settings needs to be understood better.This paper focusses on securing a cloud infrastructure for multi-agent systems for industrial sites. An industrial site contains multiple production processes that need to communicate with each other and each physical resource is abstracted with a software agent. This volatile architecture needs to be managed and protected from manipulation. The proposed infrastructure presents a security concept for TCP/IP communication between agents, machines, and external networks. It is based on open-source software and tested on a three-node edge cloud controlling a model-plant.
Chromatography is the workhorse of biopharmaceutical downstream processing because it can selectively enrich a target product while removing impurities from complex feed streams. This is achieved by exploiting differences in molecular properties, such as size, charge and hydrophobicity (alone or in different combinations). Accordingly, many parameters must be tested during process development in order to maximize product purity and recovery, including resin and ligand types, conductivity, pH, gradient profiles, and the sequence of separation operations. The number of possible experimental conditions quickly becomes unmanageable. Although the range of suitable conditions can be narrowed based on experience, the time and cost of the work remain high even when using high-throughput laboratory automation. In contrast, chromatography modeling using inexpensive, parallelized computer hardware can provide expert knowledge, predicting conditions that achieve high purity and efficient recovery. The prediction of suitable conditions in silico reduces the number of empirical tests required and provides in-depth process understanding, which is recommended by regulatory authorities. In this article, we discuss the benefits and specific challenges of chromatography modeling. We describe the experimental characterization of chromatography devices and settings prior to modeling, such as the determination of column porosity. We also consider the challenges that must be overcome when models are set up and calibrated, including the cross-validation and verification of data-driven and hybrid (combined data-driven and mechanistic) models. This review will therefore support researchers intending to establish a chromatography modeling workflow in their laboratory.
We prove characterizations of the existence of perfect ƒ-matchings in uniform mengerian and perfect hypergraphs. Moreover, we investigate the ƒ-factor problem in balanced hypergraphs. For uniform balanced hypergraphs we prove two existence theorems with purely combinatorial arguments, whereas for non-uniform balanced hypergraphs we show that the ƒ-factor problem is NP-hard.
Das Diskussionspapier beschreibt einen Prozess an der FH Aachen zur Entwicklung und Implementierung eines Self-Assessment-Tools für Studiengänge. Dieser Prozess zielte darauf ab, die Relevanz der Themen Digitalisierung, Internationalisierung und Nachhaltigkeit in Studiengängen zu stärken. Durch Workshops und kollaborative Entwicklung mit Studiendekan:innen entstand ein Fragebogen, der zur Reflexion und strategischen Weiterentwicklung der Studiengänge dient.
Der Konstruktionsbereich ist zu einem neuen Schwerpunkt der allgemeinen Rationalisierungsbemühungen geworden. Zunehmend führt man organisatorische Hilfsmittel, technische Hilfsmittel (EDVA) und neue Konstruktionsmethoden in der Konstruktion ein. Der vorliegende Beitrag analysiert zunächst die Ursachen dieser Entwicklung und zeigt im weiteren einige heute bereits eingesetzte Hilfsmittel an Hand von Beispielen auf und diskutiert die Anwendungsmöglichkeiten.
Der Konstruktionsbereich ist zu einem neuen Schwerpunkt der allgemeinen Rationalisierungsbemühungen geworden. Zunehmend führt man organisatorische Hilfsmittel, technische Hilfsmittel (EDVA) und neue Konstruktionsmethoden in der Konstruktion ein. Der vorliegende Beitrag analysiert zunächst die Ursachen dieser Entwicklung und zeigt im weiteren einige heute bereits eingesetzte Hilfsmittel an Hand von Beispielen auf und diskutiert die Anwendungsmöglichkeiten.
In den letzten Jahren hat der Einsatz von graphischen Datenverarbeitungsanlagen auf dem technischen, naturwissenschaftlichen und kommerziellen Sektor immer mehr an allgemeinem Interesse und Bedeutung gewonnen. Diese Entwicklung hat neue Aspekte und Probleme in bezug auf Anwendungsmöglichkeiten, Programmierung, Datenstrukturen sowie der Hard- und Software dieser Anlagen hervorgerufen. Zur Zeit werden von verschiedenen Institutionen die Einsatzmöglichkeiten graphischer Datenverarbeitungsanlagen in den Funktionsbereichen Konstruktion und Arbeitsvorbereitung untersucht. Der folgende Beitrag zeigt eine kurze Übersicht über die verschiedenen programmiertechnischen Probleme sowie eine Auswahl von Programmbeispielen, die am Laboratorium für Werkzeugmaschinen und Betriebslehre der RWTH Aachen entwickelt wurden. Bei den Bildschirmsystemen wird zwischen zwei Arten unterschieden. Aktive Bildschirmeinheiten besitzen als äußeres Merkmal einen Lichtstift und eine Funktionstastatur zur Programmverzweigung. Passive Bildschirmeinheiten lassen demgegenüber einen Eingriff in das Programm in der oben aufgeführten Form nicht zu. Zwischen diesen extremen Formen gibt es noch eine Reihe Mischformen. Die in Aachen zur Verfügung stehende Anlage arbeitet aktiv und wird im nachfolgenden Kapitel näher beschrieben.
CAD/CAM - Compass Maschinenbau. Ein Leitfaden für die optimale Systemauswahl CAD/CNC/CAM/CAE/PPS
(1993)