A categorical approach for defining digital twins in the AECO industry

Abstract

Operations and Maintenance (O&M) costs account for 60-80% of a facility’s lifecycle costs. Using Digital Twins (DTs) can aid in making O&M more effective and efficient, leading to time and cost savings. The concept of DT started in the Aerospace domain, and other industries eventually adopted it. DTs are a new concept to the Architecture, Engineering, Construction, and Operations (AECO) Industry, and there is a lot of confusion around this concept. The purpose of this paper is to provide a DT definition along with a classification structure to create a common ground for understanding DTs in the AECO industry, which leads to easier adoption of DTs. A systematic literature review was completed to identify the existing DT definitions and classification approaches. Then, through a content analysis, the core components of definitions were extracted. The identified components were used to develop a comprehensive and inclusive DT definition for the AECO industry, using the domain language. In a similar fashion, existing DT classification structures were studied, and their components were identified through content analysis. Using the identified components, a DT classification structure was proposed for the AECO industry using domain concepts and terms. The results were validated and refined through a series of semi-structured expert interviews and surveys. Interviewees and survey participants comprised DT experts from academia and industry with diverse backgrounds. The components of the proposed DT definition include virtual representation, data connection between physical and digital entities, analysis, actuation, and frequency of updates. The classification structure consisted of three DT categories, namely Digital Twin Prototype (DTP), Digital Shadow (DS), and Cyber-Physical System (CPS).