Micro-workflows: a combination of workflows and data streaming to support digital twins of production processes

Recently, there has been an explosive growth in the development of the concept of "Digital Industry". One of the most important elements of this concept is the application of methods of mathematical modeling and intelligent data analysis to create models of production processes and final products based on the processing of signals coming from intelligent sensors. A set of such models, which represent a virtual representation of industrial processes, systems and equipment, is called "Digital twin". Digital twins use data from sensors installed on production lines or on the basis of final products to predict equipment failures, optimize product quality and reduce the environmental impact of production processes. The model sets, underlying digital twins, can be described as workflows consisting of a set of computational services, each of which is a model of a process step. To provide flexible support for cloud computing to perform digital twins, we offer the concept of "Micro-Workflows", which combines the power of the Scientific Workflows concept, the flexibility of container technology and the sustainability of the Stream Processing approach in distributed computing systems.