A Generalized Feature Model for Digital Twins

TL;DR

This paper introduces a comprehensive feature model for Digital Twins, aiming to standardize their design and development across various domains, thereby enhancing decision-making, development, and validation processes.

Contribution

It presents the first generalized feature model for Digital Twins, derived from a systematic literature review and validated through multiple real-world use cases.

Findings

The model covers mandatory and optional features of Digital Twins.

Application to diverse domains demonstrates its versatility.

Facilitates improved design, development, and validation of Digital Twins.

Abstract

The adoption of Digital Twin technologies is rapidly expanding in diverse industrial, economic, and societal domains. Over the past decade, a multitude of studies, surveys, and investigations have been conducted, examining the nature, applications, and advantages of Digital Twins. However, up until now, no proposal for a comprehensive feature model exists that effectively captures the mandatory and optional features of Digital Twins. To address this shortcoming, in this article, we present a general feature model for Digital Twins. Based on a systematic mapping study of existing literature, we developed a generalized feature model for Digital Models, Shadows, and Twins. To assess the validity of our proposed feature model, we have applied them to three use cases from the emergency, vehicular, and manufacturing domain. We conjecture that our proposed general feature model advances the field around Digital Twins by facilitating informed decision-making during design, enabling improved model-driven development of Digital Twins, and, eventually, fostering verification~\&~validation of Digital Twins by delivering a model-based foundation for test case inference.