Elsevier Predictive Digital Twins: Foundations and Applications

Predictive Digital Twins: Foundations and Applications addresses the theoretical foundations, practical applications, and emerging trends associated with predictive digital twins. Specifically focusing on predictive capabilities, digital twins designated for this purpose are commonly known as predictive digital twins. Despite the growing recognition of their importance, discussions surrounding predictive digital twins remain fragmented and lacking a comprehensive resource. This gap becomes particularly pronounced in the academic world, where, as a university professor teaching a master's program course in digital twins, there arises a pressing need for a dedicated reference book to furnish students with a structured and in-depth exploration of predictive digital twins. The book fills the existing void in literature and academia, providing students, researchers, and practitioners with a valuable resource to enhance their understanding of this cutting-edge concept. The digital twin concept stands as a pivotal facilitator in the ongoing Industry 4.0 revolution, with one of its most significant advantages lying in its capacity to offer precise predictions. Provides the clear explanations and theories underpinning predictive digital twins to facilitate effective teaching and research Includes real-world applications and success stories that illustrate the practical implementation of predictive digital twins across different industries Provides practical insights into how to implement predictive digital twins for improving processes, especially in predictive maintenance Gives guidance on best practices for developing, managing, and optimizing predictive digital twin systems