Industry-Oriented Lightweight Simulation System

Changwei Liu, Hao Ren, Nan Zhou, Guoqiang Li, Xiaojun Liang, Weihua Gui, Chunhua Yang

Abstract: In order to address the simulation requirements arising from limited computational resources, non-reusable complex models, and low-latency demands for edge devices within the realm of the Industrial Internet of Things (IIoT), we have successfully defined and developed a Lightweight Simulation System(LSS) specifically designed for industrial applications. This system draws inspiration from the architectural principles of edge and fog computing. LSS leverages an innovative architectural paradigm known as Function as a Service (FaaS), which demonstrates an even finer granularity compared to the traditional microservices architecture. Within the framework of LSS, we have discretely compartmentalized distinct operational elements, such as data acquisition and storage, model computation, and model visualization, into Docker microservices. This strategic shift in design effectively alleviates the need for developers to be overly concerned with the intricacies of server management and domain-specific industrial knowledge. Consequently, this enables them to shift their focus towards determining "what needs to be accomplished," thereby transforming the granularity of work from being server-centric to a more task-centric perspective. In comparison to simulation platforms within other frameworks, LSS distinguishes itself through its remarkable attributes, which include a lightweight structure, minimal coupling, and superior real-time performance. These unique qualities substantially enhance the collaborative, shared, and reusable capabilities of simulation systems across various dimensions. To substantiate the viability of LSS, this paper provides empirical evidence by applying it to Electrolysis and partial cascade algorithms in the context of hydrometallurgy. The results underscore the fact that the LSS system significantly improves modeling efficiency, fosters the reusability of models and algorithms, and elevates the level of industrial automation across diverse processes.