Optimizing Digital Twin Design Through a QFD and AHP-Based Selection Methodology

As digital twins gain prevalence across various industries, the need for a structured selection process becomes crucial. This paper proposes using the Quality Function Deployment (QFD) and Analytic Hierarchy Process (AHP) to help users determine the suitable quality level of digital twin models based on their actual needs. Our proposed methodology integrates the quality goals and existing resources of organizations to provide a comprehensive and systematic approach to the selection of digital twin models. This approach guides organizations to identify the importance of Engineering Characteristics (ECs), enabling efficient resource allocation for the design and operation of digital twins. Further, it facilitates comparative performance analysis against other models, thus enriching the understanding of digital twins' capabilities. This methodology fills a significant gap in the current research landscape and has the potential to improve the quality and effectiveness of business operations. Future research directions include the validation and enhancement of the methodology through case studies and an exploration of additional influencing factors in digital twin design.