A power plant manager receives a notification to change a certain tube in the boiler during the next planned outage. An online store automatically sends an email mentioning ski clothing on sale to a new customer who just purchased a pair of skis. A freight train driver notices on the dashboard screen that his speed is automatically changed to save fuel based on the railway profile.
What do these three stories have in common? They each show people operating on insights created by a virtual replica of their asset. This virtual replica is called a digital twin. It uses first principal and statistical models, design information and external drivers to generate near real-time product information such as remaining life time, distance to optimal operations and geographical position.
This ISG white paper explores the concept of the digital twin and its potential to oﬀer data-driven insights that enhance products and services, drive predictive maintenance and field service management to provide greater value to the end customer.
About the author
Sébastien has 20 years of IT and digital experience with various leadership positions. During his career, he worked for software providers and global industrial companies in France and Switzerland, for which he led several digital transformation programs. Sébastien holds a masters degree in applied mathematics from both the French National Institute of Applied Sciences and Toulouse University and he received further business and leadership training at GE’s Crotonville leadership institute. At ISG, Sébastien leads customer engagements in DACH and his a member the Engineering Services practice. In addition, he is engaged in product lifecycle management (PLM), Internet of Things (IoT), Industry 4.0 and digitalization topics. He has wide ranging industry experience in power generation, manufacturing and supply chain where he led multiple large digital transformation programs. His work for ISG clients has led to significant improvements on key metrics such as productivity, product introduction lead time and cost of ownership.