Abstract
Digital Twin (DT) implementation in manufacturing plants has attracted increasing attention. Owing to advancements in the use of technologies related to Industry 4.0 pillars, such as the Internet of Things, Big Data analytics, and simulation, the potential of DTs to profoundly impact manufacturing has been recognised. However, DT implementation is challenging. In practice, manufacturing companies that consider DT implementation may encounter several challenges, which can prevent the achievement of its potential benefits and impede its successful realization. Research on this topic lacks empirical evidence and models to guide practitioners to overcome this problem. Therefore, the aim of this study was to map the key challenges related to DT implementation in manufacturing contexts and propose a set of possible countermeasures. To achieve this objective, we conducted a Delphi study involving 15 experts, both practitioners and academics. The process required three rounds. In the first round, the experts were requested to provide a personalized list of potential challenges to DT implementation. In the second round, the experts evaluated the challenges from the literature and their suggested potential challenges, providing a measure of relevance. Furthermore, experts were asked to propose possible countermeasures to these challenges. Finally, a third round achieved consensus. The study identified 18 key challenges divided into four categories and proposed a set of possible countermeasures to overcome these problems. Moreover, a relevance/agreement matrix of the key challenges was proposed to establish a relative impact.
