Why is this happening even though today’s products are developed and produced with the utmost care, a wealth of experience, and state-of-the-art tools? One reason is that products are always developed based on assumptions and empirical values regarding later use, operating conditions, and loads, which may subsequently prove to be inaccurate. Fast, systematic, complete, and automated feedback from the field on product quality, safety, and use could help by using this type of feedback to proactively drive timely product improvement. However, this is still a dream far off in the future for many engineers: Collecting and evaluating feedback from the field is often a lengthy process and often only makes its way back to engineers after a long delay.
The digital twin can change this. In essence, it is the virtual representation of a specific product that accompanies its physical counterpart for a lifetime. Each representation/data model remains assigned to an individual product – from development and production to subsequent operation – and is fed with its real operating data. “This allows us to monitor the condition, quality, and use of, say, a vehicle or an entire fleet under load, and to determine decisive cause-and-effect relationships by analyzing the data,” explains Sascha Leidig, Head of the PLM Global Competence Center at T-Systems.
But not only that. “The digital twin opens up completely new possibilities in product development,” predicts the expert on digital twins, Christian Völl, from the consulting company Detecon. According to Völl, structured innovation management which leads to products with significantly higher customer attractiveness is already a critical success factor for surviving in the market.