Concept of digital twins at life cycle stages of production systems

Abstract

Subject of Research. The paper analyzes the current concept of digital twins in relation to production systems. The review is given for characteristics and parameters of the digital twin that create advantages of using this concept for production systems at their life cycle stages. Technical implementation variants for the concept of digital twins are proposed aimed at improvement of the technological processes of production systems at the following stages of the life cycle: an idea, project, realization, operation, and disposal. Method. We performed a retrospective analysis of scientific papers on the methodology and practical application of software-based approaches to the design, implementation and operation of industrial systems in Industry 4.0. An expert assessment and applicability analysis of the digital twins at the stages of the life cycle of production systems are given. Main Results. The main characteristics of the digital twin affecting the effectiveness of the concept application in production systems are determined and arranged into groups according to their importance based on the analysis of the foreign studies over the past 10 years. The advantages and disadvantages of a software-oriented approach application to the design, implementation and operation of production systems are formulated. Practical Relevance. The digital twin characteristics are determined that affect the efficiency of its usage at the life cycle stages of production systems. Variants of the modern concept technical implementation of digital twins for production systems are proposed by applying of advanced digital technologies and intelligent electronic devices. Requirements are systematized concerning functionality, performance, correspondence accuracy of the virtual and physical environment state, as well as the qualitative characteristics of the digital twin. They provide for the assessment about the applicability of digital twins for solving existing problems of control and management in production systems.