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ThinkMind // International Journal On Advances in Software, volume 13, numbers 3 and 4, 2020 // View article soft_v13_n34_2020_9


Microservice-Enabled Simulation Platform for Industry-4.0 Dynamic Systems: A Computational Fluid Dynamics Case Study for Underground Coalmine Ventilation Networks

Authors:
Alexey Cheptsov
Oleg Beljaev

Keywords: microservices; dynamic systems; real-time simulation; computational fluid dynamics; cyber-physical automation; ventilation network

Abstract:
Industry 4.0 is a state-of-the-art methodology of complex industrial systems development, which aims to improve the industrial processes by applying the digitalization and computer processing to the technology-level of production objects. The ability to process streaming data from numerous digital sensors, as enabled by Industry 4.0, endorses a potential for creation of many innovative applications. One of the major classes of industrial applications that are enabled by Industry 4.0 is the simulation – the technology that is frequently used for the “offline” optimization of technological processes. In the context of Industry 4.0, the simulation will be benefitting from the “online” integration with the digitalized industrial infrastructure, e.g., for the realization of real-time support scenarios. However, the existing simulation approaches and tools are not able to support highly dynamic, hierarchically organized industrial systems due to a monolithic design of those tools, motivated by the other essential requirements, such as efficiency, user- and developer-friendliness, etc. This article proposes an approach that is based on microservices – the functionally-decoupled, interconnected composition blocks of a hierarchically organized, modular simulation application, that implements a specific part of the simulation logic for the targeted physical phenomena. The use of the microservice-based approach is demonstrated on the implementation of a simulation framework for underground coalmine ventilation networks – complex technological objects that impose challenging tasks, such as conduction of Computational Fluid Dynamics studies.

Pages: 217 to 228

Copyright: Copyright (c) to authors, 2020. Used with permission.

Publication date: December 30, 2020

Published in: journal

ISSN: 1942-2628

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