670 Industrielle und handwerkliche Fertigung
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Most antimicrobial peptides (AMPs) and their synthetic mimics (SMAMPs) are thought to act by permeabilizing cell membranes. For antimicrobial therapy, selectivity for pathogens over mammalian cells is a key requirement. Understanding membrane selectivity is thus essential for designing AMPs and SMAMPs to complement classical antibiotics in the future. This study focuses on membrane permeabilization induced by SMAMPs and their selectivity for membranes with different lipid compositions. We measure release and fluorescence lifetime of a self-quenching dye in lipid vesicles. Apart from the dose-response, we quantify the strength of individual leakage events, and, employing cumulative kinetics, categorize permeabilization behavior. We propose that differing selectivities in a series of SMAMPs arise from a combination of the effect of the antimicrobial agent and the susceptibility of the membrane (with a given lipid composition) for certain types of leakage behavior. The unselective and hemolytic SMAMP is found to act mainly by the asymmetry stress mechanism, mediated by hydrophobic insertion of SMAMPs into lipid layers. The more selective SMAMPs induced leakage events occurring stochastically over several hours. Lipid intrinsic properties might additionally amplify the efficiency of leakage events. Leakage behavior changes with both the design of the SMAMP and the lipid composition of the membrane. Understanding how leakage behavior contributes to the selectivity and activity of antimicrobial agents will aid the design and screening of antimicrobials. An understanding of the underlying processes facilitates the comparison of membrane permeabilization across in vitro and in vivo assays.
Additive manufacturing is a key technology which applies the ideas of Industry 4.0 in order to enable the production of personalized and highly customized products economically. Especially small and medium sized companies often lack the competence and experience to evaluate objectively and profoundly the potential of additive manufacturing technologies in small and medium sized companies. Furthermore, the method has been validated in a small medical technology company evaluating the additive manufacturing potential of an existing surgery tool.
The persistent development towards decreasing batch sizes due to an ongoing product individualization, as well as increasingly dynamic market and competitive conditions lead to new changeability requirements in production environments. Since each of the individualized products mgith require different base materials or components and manufacturing resources, the paths of the products giong through the factory as well as the required internal transport and material supply processes are going to differ for every product. Conventional planning and control systems, which rely on predifined processes and central decision-making, are not capable to deal with the arising system's complexity along the dimensions of changing goods, layouts and throughput requirements. The concepts of "self-organization" in combination with "autonomous ocntrol" provide promising solutions to solve these new requirements by using among other things the potential of autonomous, decentralized and target-optimized logistical objects (e.g. smart products, bins and conveyor systems) wich are able to communicate and interact with each other as well as with human wokers. To investigate the potential of automation and human-robot collaboration for intralogistics, a research project for the development of a collaborative tugger train has been started at the ESB Logistics Learning Factory in lin with various student projects in neighboring research areas. This collaboraive tugger train system in combination with other manual (e.g. handcarts) and (semi-) automated conveyoer systems (e.g. automated guided forklift) will be integrated into a dynamic, self-organized scenario with varying production batch sizes to develop a method for target-oriented sefl-organization and autonomous control of intralogistics systems. For a structured investigation of self-organized scenarios a generic intralogistics model as well as a criteria cataloghe has been developed. The ESB Logistics Learning will serve as a practice-oriented research, validation and demonstration environment for these purposes.
After the initiator of the ESB Logistics Learning Factory, Prof. Vera Hummel had made experience in developing and implementing a concept for a Learning Factory for Advanced Industrial Engineering (aIE) at the University of Stuttgart, Institute IFF between 2005 and 2008, she was appointed as a full professor at ESB Business School, a faculty of Reutlingen University in March 2010. Lacking a realistic, hands on learning and teaching environment of industrial scale for its industrial engineering students, first ideas for a Learning Factory that would strongly focus on all aspects of production logistics were drafted in 2012. Already back then, a strong integration of virtual and physical factory was desired: While the Learning Factory itself would be physical, the neighboring partners along the supply chain, such as suppliers or distribution warehouses, could be added in a fully virtual way. Considering implementation of the ESB Logistics Learning Factory a strategic initiative of the university, initial funding was provided by the faculty ESB Business School itself. Following its own creed, to provide future-oriented training for the region, also primarily local suppliers and manufacturers were selected as equipment providers to the new Learning Factory. During the initialization phase, 2014, a total of three researchers and nine students worked approximately four months to set up a first assembly line, storage racks, AGVs, or pick-by-light systems in conjunction with the underlying didactical concept. Since then, several hundred of students have participated in trainings and lectures held in the ESB Logistics Learning Factory, several research projects were carried out, and multiple high-level politicians and industry executives have been touring the shop floor. Also, more than EUR 2 million in research and infrastructure funds could be secured for expansion and upgrade — allowing the ESB Logistics Learning Factory today to represent many core aspects of an Industrie 4.0 production environment.
Abreinigbare Schlauchfilter kommen zur Abscheidung von Stäuben sowie staubförmigen Substanzen zum Einsatz. Aufgrund typischer Prozessbedingungen unterliegen sie während ihres Einsatzes thermischer, chemischer und mechanischer Beanspruchung. Das IGF-Projekt Nr. 18307 "Untersuchung der chemischen und thermischen Degradation von abreinigbaren Filtermedien und Verbesserung deren Beständigkeit durch Oberflächenmodifikation" hat mehrere Prüfmethoden verglichen.
Homogeneous and monodispersed furan functionalised melamine-formaldehyde particles were produced. As a precursor, 2-chloro-1,3,5-triazine-2,4-diamine (Mel) was selectively substituted with 2-aminomethyl furan (Fu) units in a convenient one step reaction. The pure reaction product Fu-Mel, which was used without further purification, was reacted with formaldehyde by conventional sol-gel condensation in aqueous medium to yield chemically homogenous, spherically shaped and monodispersed particles. The particles were analysed using ATR-FT-IR, Raman, 1H and 13C NMR spectroscopy, TGA, SEM and DSC measurements. The reactivity of the furan groups located at the particle surface was studied by performing a thermoreversible Diels-Alder cycloaddition reaction with bis-maleimide coupling agents. The formed networks showed thermoreversible behaviour, which was characterised by dynamic IR and DSC measurements.
Cleanable bag filter : comparisons of different testing methods of ageing of filter materials
(2019)
Cleanable bag filters are used to separate dust and other airborne particulate systems. Due to typical process conditions, they are subject to thermal, chemical and mechanical stress during use. The main objective of the IGF project no. 18307 "Investigation of the chemical and thermal degradation of cleanable filter media and improvement of their resistance by surface modification", was the development of a valid test method which can reproduce degradation caused by high temperatures and aggressive chemical atmospheres in a practice-oriented but time-saving manner. Within the IGF project, 2 accelerated ageing methods were applied, both of which have the decisive advantage of investigating damage in the gas phase. Many resistances of filter materials are otherwise carried out by immersing the materials in a mostly liquid damage medium at a defined temperature. These resistances are difficult to transfer ageing in the gas phase.
It has not yet been possible to achieve the desired aim of decoupling economic growth from global material demand. Small and medium sized enterprises (SMEs) represent the backbone of most industrialized economies. Although material efficiency is of vital importance for many SMEs, few of them actually treat it as their top priority. There is a cornucopia of tools and methods available which can be used for material efficiency purposes. These, however, have gained little ground in the SME-field. This work deals with the enabling factors for material efficiency improvements in manufacturing SMEs and projections towards aspects of supply chain and circular economy. A multi-disciplinary decoupling approach for manufacturing SMEs and an implementation roadmap for further practical development are proposed. The approach combines appropriate complexity of technology and socio-economic considerations. It enables a connection of existing methods and the implementation of established information technologies.
The flexible and easy-to-use integration of production equipment and IT systems on the shop floor becomes more and more a success factor for manufacturing to adapt rapidly to changing situations. The approach of the Manufacturing Integration Assistant (MIALinx) is to simplify this challenge. The integration steps range from integrating sensors over collecting and rule-based processing of sensor information to the execution of required actions. This paper presents the implementation of MIALinx to retrofit legacy machines for Industry 4.0 in a manufacturing environment and focus on the concept and implementation of the easy-to-use user interface as a key element.
In smart factories, maintenance is still an important aspect to safeguard the performance of their production. Especially in case of failures of machine components diagnosis is a time-consuming task. This paper presents an approach for a cyber-physical failure management system, which uses information from machines such as programmable logic controller or sensor data and IT systems to support the diagnosis and repairing process. Key element is a model combining the different information sources to detect deviations and to determine a probable failed component. Furthermore, the approach is prototypically implemented for leakage detection in compressed air networks.