Digital twin modeling: A comparison of current approaches

Abstract

Background The implementation of digital twins is of growing importance due to increasing interest. Various procedural models are used or are currently being developed in theory and practice. However, there is no generally accepted model. The aim of the present study is to record and analyze existing models and from the perspective of deriving development trends. Method In the first step, a systematic literature search is carried out; in the second step, the results are subjected to a comparative analysis. Results The study provides an overview of common process models for implementing Digital Twins. Fifteen approaches were selected for a detailed analysis. 1/3 are hybrid process models (i.e. a combination of several models), sequential and evolutionary models still dominate, and the phase length is between 5 – 10 phases. In other words, the majority of the existing process models analysed surprisingly follow a more sequential approach. Discussion Process models with a sequential character - with and without accompanying project management - dominate, but hybrid approaches are increasing in importance: (a) on the one hand as an integrated project management component, i.e. a combination of agile and classic project management, since these meet the digital twin requirements in terms of hardware (= rather classic approach), software (= more agile approach) and data management; (b) on the other hand, the merging or mutual supplementation of existing data science approaches - such as data mining with CRISP-DM - with the above project management approaches is to be expected.