Value Creation With Digital Twins
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Value Creation with Digital Twins
Author: Linard Dario Barth
language: en
Publisher: BoD – Books on Demand
Release Date: 2024-09-20
A digital twin is a digital representation of a real-world counterpart, which can receive and provide data to create value within a use case. Digital twins create value for users by enabling new and enhanced smart services. However, ambiguous definitions and terminology coupled with a lack of shared conceptual reference frameworks complicate cross-functional discussions and hinder the widespread implementation of digital twins. This thesis proposes a new definition and presents two conceptual reference frameworks to systematically depict value creation with digital twins. A design science research approach with mixed methods was used to iteratively design and evaluate these artifacts while ensuring scientific rigor, practical relevance, and usefulness. The applied methods within the five research phases include systematic literature research, interviews, workshops with academic experts, qualitative and quantitative questionnaires, workshops with practice experts, and an in-depth case study in smart waste management. The major findings of this research are (i) the proposal of a new definition of digital twins that reflects a practical understanding by focusing on value creation; (ii) a scientific conceptual reference framework focusing on completeness by distinguishing 81 elements involved in value creation with digital twins; (iii) a second, more application-oriented conceptual reference framework focusing on the interrelations of the elements essential for the value creation in practice; and (iv) an instantiation of the application-oriented framework for the use case of the in-depth case study. All artifacts are consistent in content and include the following main dimensions, which are to be considered when creating value with digital twins: data resources, internal value creation, and external value creation. These artifacts contribute to a common understanding of value creation with digital twins in research and practice. Furthermore, they enable researchers and practitioners to structure their digital twin activities and communicate them to internal and external stakeholders.
Generation and Update of a Digital Twin in a Process Plant
This book covers the most important subjects of digital twin in a process plant, including foundations, methods, achievements, and applications in a brownfield environment. Besides offering a variety of applications and procedural variants from research and industrial practice, this book also provides a comprehensive insight into holistic plant planning. It also discusses the challenges that currently exist in different application areas. This book would be of interest to industry professionals and researchers in industrial and manufacturing engineering.
Empowering Value Co-Creation in the Digital Era
In the digital era, the concept of value co-creation evolved from a passive exchange to a dynamic, collaborative process that empowers organizations and consumers. The rise of interconnected technologies, data-driven insights, and digital platforms unlock new avenues for creating shared value. Companies can now engage customers, partners, and competitors in real-time, transforming traditional business models into systems of innovation. Empowering value co-creation fosters an environment where all stakeholders contribute, interact, and obtain mutual benefits, driving sustainable growth, customer satisfaction, and competitive advantage. Empowering Value Co-Creation in the Digital Era explores emerging trends in co-creation in business, highlighting how value co-creation can transform customer relationships in the digital era and digital age. It examines the evolution and trends of digital transformation and its implications in organizations and customer relationship management. This book covers topics such as entrepreneurship, digital technology, and manufacturing, and is a useful resource for business owners, entrepreneurs, computer engineers, academicians, researchers, and data scientists.