Orchestration of model computing assets for the development of digital twins

Abstract

With the development of industries and manufacturing requirements, the use of digital twin technology is promising for increasing efficiency and improving product quality. An important component of digital twin implementation is the provision of tools for modeling and simulation processes. In this study, a solution based on the use of Python-based models and the Controller software platform, which provides communication between models and external elements of digital twins and other IIoT solutions, was proposed as such a toolkit. It defines the main approaches for creating model, scenario, and function libraries, along with the concept of implementing dynamic scenarios based on JSON requests from the orchestrator. In addition, the algorithm, the structure of the Controller, and its main functionality are considered. The resulting solution takes advantage of the Python and Node.js languages in performing the relevant tasks and contains several solutions that reduce traffic and workload on communication systems, increase system reliability, scale the system, etc.