1. Industrial digital ecosystems: Predictive models and architecture development issues
- Author
-
Alexander Suleykin and Natalia Bakhtadze
- Subjects
0209 industrial biotechnology ,Supply chain management ,Computer science ,020208 electrical & electronic engineering ,Control (management) ,02 engineering and technology ,Field (computer science) ,Digital ecosystem ,020901 industrial engineering & automation ,Control and Systems Engineering ,Management system ,0202 electrical engineering, electronic engineering, information engineering ,Systems engineering ,Production (economics) ,State (computer science) ,Architecture ,Software - Abstract
The concept of digital ecosystem (DES) is widely used in autonomous manufacturing process control and the development of complex, stable, interactive, self-organizing and reliable management systems for various industries. The paper offers a concept of DES control system architecture based on predictive models. For estimating and predicting the state of resources in production processes, an approach is developed using data mining based model generation. The paper also reviews the current state of research in the field of DES and their applications in supply chain management (SCM).
- Published
- 2021