Session: 02-07-01: IoT and Digital Twins

Paper Number: 146078

146078 - Integrating Digital Twin Technology During the Concept Development Phase of the Product Development Process 

Digital Twins (DTs) are an essential component of Industry 4.0, as they can significantly enhance every stage of a product's life cycle, from its initial design to its disposal. In the traditional approach, data generated during each stage of the product lifecycle is often isolated and of different types. This creates efficiency issues and results in valuable data being underutilized. Digital twins address this problem by leveraging the power of simulation and advanced analytics in the context of a well-defined digital thread. They enable “real-time” monitoring and optimization of products and processes, resulting in significant improvements in efficiency, productivity, and cost savings. This paper introduces a new approach called Design for Digital Twins (DFDT), which aims to seamlessly integrate Digital Twin technology into the design and development processes of engineered consumer products that are physical and have moderate complexity. DFDT outlines specific tasks that need to be incorporated into the different phases of the traditional product development process (PDP) in order to facilitate the identification and simultaneous development of both focused and/or comprehensive DTs in alignment with the physical product. The proposed DFDT methodology takes into consideration the use of existing technologies such as 3D scanning, 3D printing, Computer Aided Design (CAD), Finite Element Analysis (FEA), and Machine Learning (ML), which can support different activities related to the development of digital twins. An important goal is that the proposed DFDT methodology will be able to guide the development of virtual models that can help to make informed decisions about the product early in the development cycle. It also considers the product planning stage that precedes the Product Development Process (PDP).

An electric scooter is used as a case study to showcase the application of essential components of the proposed DFDT methodology during the concept development phase of the PDP. The digital twin must be developed at the same time as the product, rather than being developed once a product design has been selected. The virtual scooter twin will use the force exerted on the chassis to provide a comprehensive view of the stress and strain fields in the scooter’s frame. Load sensors and displacement sensors will collect data for simulation, which can then be used to evaluate the performance of the product.

DFDT promises a paradigm shift towards more informed and data-driven product design, also reducing the number of physical prototypes needed. It also enables identifying and resolving product performance issues before they lead to costly design changes.

Presenting Author: Karim Muci-Kuchler Texas State University

Presenting Author Biography: Before joining Texas State University, Dr. Karim Muci-Kuchler was a Professor of Mechanical Engineering and Director of the Experimental and Computational Mechanics Laboratory at the South Dakota School of Mines and Technology. He received his Ph.D. in Engineering Mechanics from Iowa State University in 1992. He has taught a wide variety of undergraduate and graduate engineering courses and his main interest areas include Engineering Education, Computational Mechanics, Product Design and Development, and Solid Mechanics. Dr. Muci-Kuchler is a Fellow of the American Society of Mechanical Engineers, co-author of a book about Adaptive Meshing with Boundary Elements, and author or co-author of over 85 publications. The latter include papers related to engineering education, the boundary element method, the friction stir spot welding process, and surrogate perforating projectile wounds, among others. He is an ABET PEV, has served as session chair or co-chair at international conferences, has reviewed papers for technical journals and conference proceedings, has served as panelist for the National Science Foundation (NSF), and has done consulting for industry in Mexico and the US.

Authors:

Sm Tawhid Mahmud Texas State University
Karim Muci-Kuchler Texas State University