Use Cases for Digital Twin

Introduction

The ability to unleash various potentials of virtual product creation has increased with the use and sophistication of simulation models. While simulation software has gotten increasingly powerful, attempts to maximise the potential benefits of product simulations are increasingly centred on the input data that is now accessible. More accurate simulation models that ultimately produce better products can be created. The definition, upon which this work is based, states that “use phase data” refers to data generated by the product itself during the usage phase. The term “digital twin” is frequently used to describe such integration of simulation models and the usage of phase data (Autiosalo, 2019). In this contribution, a “digital twin” is defined as “a virtual, dynamic representation of a physical system that is connected to it over the whole life cycle, enabling bidirectional data exchange (Latif, 2020) the heating and cooling systems industry partner of this case study, like many other businesses today, is having trouble changing from a “conventional” mechanical engineering firm to a forward-thinking business that fully embraces digitization. Although the goods currently in use are technically sound and frequently already supply some basic data from the usage phase, the promise of data-driven engineering and the integration of the devices on the Internet of Things are just now being realized. Some initial steps have been made, such as allowing customers to use an app to control their heating system (Tao, 2018; Beil, 2020; Bentley Systems, 2021). Digital twin technology is becoming important for digitization. Although there are many potential advantages for businesses, from predictive maintenance to the creation of new business models, there is no approach in literature or practice that fully supports businesses in introducing their digital twin, considering their unique requirements and circumstances (Biesinger, 2019; Botín-Sanabria, 2020). The digitalization of tools, procedures and products is becoming more important considering the industrial industry's significant transition and the necessity to profit from the industry 4.0 bonanza. The idea of a digital clone of a real item has been around for ages, but it is about to enter a new era (Botín-Sanabria, 2022; Briggs, 2020). Since its introduction, the digital twin has influenced product lifecycle management, driving dynamic evolution in the industrial sector. The manufacturing industry can now accept the evolving aspects of the digital twin from a variety of fresh perspectives, particularly about the asset and the product. When physical assets like equipment are digitally represented in the manufacturing sector and connected based on their functions, the equipment becomes the supply chain's and the smart factory's connection point. The connected equipment at all levels of this intelligent digital representation's connected system can send and receive data to and from it Bentley Systems (Campos-Ferreira, 2019; Carvalho, 2020). In the meanwhile, operators, maintenance experts, regulatory authorities, and other participating vendors can all read the digital depiction of the equipment, the use cases in the industry are in fig 1.