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Buchbeiträge:

ö. Sen, M.N. Durakbasa, G. Bas, G. Sen, O. Akcatepe:
"An Implementation of Cloud Based Simulation in Production";
in: "Proceedings of the International Symposium for Production Research 2019, Lecture Notes in Mechanical Engineering book series (LNME)", 1; M.N. Durakbasa, G. Gencyilmaz (Hrg.); Springer Nature Switzerland AG, Cham, Switzerland, 2019, ISBN: 978-3-030-31343-2, S. 519 - 524.



Kurzfassung englisch:
Production systems of today are developing an ever-increasing dependency on information systems, as a result of which intelligent systems are being transformed into smart systems. A production facility can be called a `smart factory´ provided that all the processes are being managed, which can be done only if sensor based an intelligent measurement data derived from pro- duction systems are analyzed and processed. To increase the quality of pro- duction and decrease energy waste, cloud computing, edge computing, energy management systems (EMS) and continuously updating simulation system must be applied to facilities. All these cutting-edge ICT technologies help the designers make more effective planning, control the Total Quality Management (TQM), and build more efficient production systems whose components interact with each other in real time. To accomplish this, previously we have set up a prototype complete which includes with sensor-based intelligent measurement nodes with a semi-edge computing and cloud-computing system to run on the real production process. And with this study we have strengthened the designed prototype with cloud-based simulation for:
. Modeling the energy consumption of the air conditioning system, which ensures the control of environmental conditions,
. Modeling the production quality that under the influence of envi- ronmental conditions.
With this new model, the product quality can be standardized by controlling the environmental conditions of the production lines as well as avoiding unneces- sary energy expenditure thus ensuring cost efficiency.

Schlagworte:
Cloud computing, Edge computing, Internet of Things (IoT), TQM, Simulation


"Offizielle" elektronische Version der Publikation (entsprechend ihrem Digital Object Identifier - DOI)
http://dx.doi.org/10.1007/978-3-030-31343-2_45


Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.