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The success of an autonomous robotic system is influenced by several not easily identifiable interdependent factors. This paper is set to lay the foundation of an integrated approach in order to examine all the parameters and understand their contribution to success. After introducing the problem, two autonomous systems for the process of unloading of containers are presented. Then a recently developed method for modelling and interpreting all the parameters, the STIC analysis, are introduced. The preliminary results of applying such a methodology to a first study case is shortly presented. Future research is in the end recommended in order to prove that this methodology is the only way to overcome barriers to the investment in autonomous systems in the logistics sector.
The increased availability of data gives rise to the use of machine learning methods for purposes like forecasting or quality control in operations management. Practitioners who want to employ these methods are faced with the task of choosing from a large number of available methods. We give an overview of classification methods and available implementations and present considerations for choosing appropriate methods.
What does the factory of tomorrow have to offer for companies? This question and its aspects are the focus of many actual articles and publications. According to Gartner digital twins, one of 2017 strategic technology trends will play a big role for the future of manufacturing. At the moment digital twins are gaining more importance for the industrial application. If companies want to be competitive in the future they have to implement the digital twin in the factories of today. Therefore this paper provides a basic overview of the concept of the smart factory and its requirements. In addition, digital twins are identified as a necessary concept for the evolution of the factory of today.
While academia and industry see large potential for human-robot collaboration (HRC), only a small number of realized HRC application is currently found in industry. To gather more data about current hindrances to wider implementation of collaborative robots, a study among 15 robot manufactureres and 14 system integrators of collaborative robot technology has been conducted through a predesigned questionnaire procedure. Additionally, five industrial users of human-robot collaboration have been interviewed on the main challenges they experienced during the initial implementation process. The quantitative data has been analyzed using the Wilcoxon-Signed-Rank-Test. Accoring to the study participants, the main challenges within the implementation currently are the identification of HRC-suitable processes, the application of relevant safety norms (such as ISO 10218, ISO/TS 15066) and the application-individual risk assessment.
Mature economies which are driven mainly by small and medium sized enterprises (SMEs) are increasingly becoming dependent on material imports. Global material consumption is ever increasing, mainly driven by population increases. Decoupling of material consumption from economic growth is one of the greatest challenges of the 21st century. Within this paper available methods for the assessment of material efficiency on different economic scales are investigated and those detected that are particulary suitable for the use in SMEs. Recommendations for further improvements of the selected tools and an outlook concerning planned research activities in the field of material efficiency in enterprises, supply chains and circular economy aspects are given.
With on-demand access to compute resources, pay-per-use, and elasticity, the cloud evolved into an attractive execution environment for High Performance Computing (HPC). Whereas elasticity, which is often referred to as the most beneficial cloud-specific property, has been heavily used in the context of interactive (multi-tier) applications, elasticity-related research in the HPC domain is still in its infancy. Existing parallel computing theory as well as traditional metrics to analytically evaluate parallel systems do not comprehensively consider elasticity, i.e., the ability to control the number of processing units at runtime. To address these issues, we introduce a conceptual framework to understand elasticity in the context of parallel systems, define the term elastic parallel system, and discuss novel metrics for both elasticity control at runtime as well as the ex post performance evaluation of elastic parallel systems. Based on the conceptual framework, we provide an in depth analysis of existing research in the field to describe the state-of-the art and compile our findings into a research agenda for future research on elastic parallel systems.
Um die ökologischen und ökonomischen Potenzaile der Elektromobilität zu nutzen, setzen kommunale Energieversorger heute auf das Betreiben öffentlicher Ladestationen, den Handel mit Ladestationen und das Bereitstellen spezieller Elektromobilitätstarife; ebenso auf elektrifiziertes Carsharing oder das Vermieten elektrifizierter Fahrzeuge und den Betrieb elektrifizierter Omnibusse im ÖPNV. Auch die Entwicklung und Planung individueller Elektromobilitätskonzepte, teils in Kombination mit Photovoltaikanlage, gehören in einigen Unternehmen zum Portfolio. Für die Zukunft sollten Stadtwerke ihre Aktivitäten im Bereich Elektromobilität an individuell definierten Zielen und Strategien ausrichten.
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