Autonomous Digital Twin of Enterprise: Method and Toolset for Knowledge-Based Multi-Agent Adaptive Management of Tasks and Resources in Real Time

Abstract

Digital twins of complex technical objects are widely applied for various domains, rapidly becoming smart, cognitive and autonomous. However, the problem of digital twins for autonomous management of enterprise resources is still not fully researched. In this paper, an autonomous digital twin of enterprise is introduced to provide knowledge-based multi-agent adaptive allocation, scheduling, optimization, monitoring and control of tasks and resources in real time, synchronized with employees’ plans, preferences and competencies via mobile devices. The main requirements for adaptive resource management are analyzed. The authors propose formalized ontological and multi-agent models for developing the autonomous digital twin of enterprise. A method and software toolset for designing the autonomous digital twin of enterprise, applicable for both operational management of tasks and resources and what-if simulations, are developed. The validation of developed methods and toolsets for IT service desk has proved increase in efficiency, as well as savings in time and costs of deliveries for various applications. The paper also outlines a plan for future research, as well as a number of new potential business applications.

Development approach for value-creating service process twins based on service design methods

“…To distinguish between DT of physical entities (equipment twin) and processes (process twin) becomes necessary to clarify the DT's usage [8]. In recent years, there have therefore been an increasing number of publications dealing with the use of DT in the business process environment [9] for example are discussing the management of tasks and resources, and [10] about the usage of DT in smart farming. Also, [11] describes the linkage of processes and simulations in so-called symbiotic simulations.…”