# A Roadmap to Integrate Digital Twins for Small and Medium-Sized Enterprises
###### Abstract  
In the last decade, Australian SMEs are steadily becoming more digitally engaged, but they still face issues and barriers to fully adopt Industry 4.0 (4.0). Among the tools that 14.0 encompasses, digital twin (DT) and digital thread (DTH) technologies hold significant interest and value. Some of the challenges are the lack of expertise in developing the communication framework required for data collection, processing, and storing; concerns about data and cyber security; lack of knowledge of the digitization and visualisation of data; and value generation for businesses from the data. This article aims to demonstrate the feasibility of DT implementation for small and medium-sized enterprises (SMEs) by developing a framework based on simple and low-cost solutions and providing insight and guidance to overcome technological barriers. To do so, this paper first outlines the theoretical framework and its components, and subsequently discusses a simplified and generalised DT model of a real-world physical asset that demonstrates how these components function, how they are integrated and how they interact with each other. An experimental scenario is presented to transform data harvested from a resistance temperature detector sensor connected with a WAGO 750-8102 Programmable Logic Controller for data storage and analysis, predictive simulation and modelling. Our results demonstrate that sensor data could be readily integrated from Internet-of-Things (IoT) devices and enabling DT technologies, where users could view real time data and key performance indicators (KPIs) in the form of a 3D model. Data from both the sensor and 3D model are viewable in a comprehensive history log through a database. Via this technological demonstration, we provide several recommendations on software, hardware, and expertise that SMEs may adopt to assist with their DT implementations. digital twin; Industry 4.0; digital thread; small-and-medium sized enterprises; product lifecycle management Article  
A Roadmap to Integrate Digital Twins for Small and Medium-Sized Enterprises  
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A Roadmap to Integrate Digital Twins for Small and Medium-Sized Enterprises  
model of every vehicle manufactured, collecting data from the sensors of each vehicle and integrating this data into the DT's simulation. The DT data have enabled Tesla to remotely monitor the state of each vehicle and perform maintenance via software updates [1; 2]. Furthermore, the combination of AI, machine learning and big data have allowed Tesla to create a system of dense traffic data that will be used in the development of autonomous vehicles [1; 2]. This is a potential new product, an upgrade of the existing product, and a new avenue for increased revenue. General Electric (GE) has embraced the DT model for its benefits of increased reliability, reduced risk and maintenance and faster time to value. The company claims to have saved $1.6 billion for customers through DT capabilities [3]. Rolls-Royce, an engineering company known for its motor cars, has also implemented DT technology into its turbine design, testing and maintenance [4]. However, Rolls-Royce has gone beyond simply improving turbine design and has innovated its entire business model. Whereas previously Rolls-Royce participated in the construction and selling of engines in the aviation industry, it now operate under a business model of selling 'power by the hour' [5]. Under this model Rolls-Royce maintains ownership of the engine and instead sells thrust hours to the airlines. As the production and manufacturing processes have evolved and transitioned to become increasingly digital, the concept of a DT, which is a virtual representation of the as-designed, as-planned, as-built and as-maintained physical product, is key to support product development [6]. DT is commonly referred to as an 'integrated multiphysics, multi-scale, probabilistic simulation of a complex product, which functions to mirror the life of its corresponding twin [7].