CIMdata, Inc., the leading global PLM strategic management consulting and research firm announces the release of an eBook, “Hybrid Digital Twins: Evolving from Product Development into Operational Efficiency,” focused on the state of the art in applying digital twin technologies in industrial companies.
Manufacturers in all industries have been applying digital modeling and simulation technologies since the 1970s but now face new challenges as products continue to become more complex, more functional, and more connected with an ever-increasing amount of embedded software and electronics as part of the Industry 4.0 “systems of systems” world. New business models such as “products as a service” are changing the way manufacturers think about the product lifecycle. Established market leaders are also competing with emerging start-ups that can digitally design new products faster and from scratch without the limitations of legacy products and traditional hardware-centric processes. Companies can no longer develop innovative new products with traditional design processes working across disconnected silos of engineering knowledge and data (mechanical, electrical/electronics, embedded software, controls, manufacturing, etc.).
Hybrid digital twins consisting of physics-based simulation models augmented with empirical data from real world operations and AI/Machine Learning analytics are now being applied across a wide range of industries and across the entire product lifecycle including in service operations to perform virtual commissioning and troubleshooting; reduce maintenance costs and cycle times; and optimize in-service operational performance and lifecycle costs including production yield as a service.
“However, realizing the business benefits of hybrid digital twin technologies also requires a business strategy and technology implementation roadmap that spans engineering, manufacturing, operations, IT, and IoT including the data management infrastructure required to establish a digital thread of key information across the global enterprise”, states Donald Tolle, CIMdata Practice Director, Simulation-Drive Systems Development. “As such, developing and applying hybrid digital twins must address engineering process and organizational factors in addition to the effective use of the latest multi-physics modeling and simulation technologies and software tools.”
As the market share leader in the CAE domain, Ansys provides a complete portfolio of hybrid digital twin software tools and implementation services capabilities to meet the business needs of industrial machinery providers and the end users of today’s complex cyber-physical systems. “Creating predictively accurate models that evolve and age with the asset that they are paired with is a key requirement for digital twins,” says Sameer Kher, Senior Director Digital Twins at Ansys. “Ansys’ Hybrid Analytics capability is an end-to-end solution that combines physics-based and machine-learning techniques to meet this requirement in a scalable way.”
The CIMdata eBook on hybrid digital twins is available at: www.CIMdata.com.