Simulation and Digital Twin: Contrasting the Capabilities and Bridging the Gap

Abstract

Driven by the advancements related to Industry 4.0, Digital Twin (DT), usually described as a virtual representation of a physical product or system connected with bi-directional data, has been a topic of increasing interest by both academia and industry. As a consequence of this growing interest, many works have been published about DT and its applications, leading to a dilution of the concept of DT, which is engendering a misunderstanding of the application of DT and its benefits. The use of simulation combined with a DT is quite common, which creates an immense misconception about classifying a simulation model as a DT and vice versa. In fact, several papers reviewed herein build simulations and call them DT, but it is unclear if these simulations have the full capabilities usually associated with DT. Simulation and DT are distinct technologies with unique benefits; therefore, they should be classified accordingly, and it is crucial to clarify their differences to prevent misunderstandings and achieve consistency in DT implementations. Therefore, in order to fill this gap, this dissertation explores the levels of capability’s levels of both simulation and DT, investigating the connection between them and demonstrating how to bridge this gap. The first contribution of this work is to propose a simulation capability framework and provide an example of a fully capable simulation application, adding and illustrating each level of capability, one at a time. This proposed framework, later referred to as the 4S framework, is different from the existing frameworks for simulation because it is directly comparable and analogous to an existing framework for building DTs, called the 4R framework. In the second contribution, a systematic literature review was performed to investigate whether the current literature is truly applying DT or using a simulation in its place. In this contribution, the 4R framework and the 4S framework provided in the first contribution are used to classify the works herein as either simulation and/or DT, based on the capabilities that they have. In the third contribution, a real-world case study that documents the process of transforming a fully capable DES into the first two levels of capability of a DT is presented. This contribution identifies the key steps involved in this transformation, documents the challenges encountered, and present the solutions that were found. The finding of this work and its future extensions can potentially help academia and the industry by moving the discussion towards a consensus about when a simulation model is a DT and when it is not.