Data-Driven Approach for Product Design and Development by Digital Twins ^†

Digital twin, a new emerging and fast-growing technology, which connects the physical and virtual world, has recently attracted much attention worldwide. On the other hand, the current global manufacturing value chain is manifested by intense competitive pressures, ever growing demand for niche products, and inflating costs; manufacturers need to intelligently design their product lines in such a manner that customer’s expectations are either met or exceeded [1]. Digital twin means an integrated multiphysics, multiscale, probabilistic simulation of a complex product, which functions to mirror the life of its corresponding twin [2].

In the light of the data-driven product design in low volume and high variety production circumstances, bidirectional relations with two sides of customers and manufacturers and also the linkage between physical products and virtual products are some of the challenging areas in academia and also in industry. Nowadays, the success of product design hinges increasingly on the manufacturer’s capability to handle data. Data can be accumulated through different phases of a product’s lifecycle, including design, production, distribution, usage, maintenance, upgrade and recycle.

In this study, the data-driven framework for product design using new digital technology will be reviewed and the limitations of redesigning and adaptation of this technology will also be considered.