Model-based data integration along the product & service life cycle supported by digital twinning

Currently, a mega-trend on digitization and servitization using digital technologies and digital twins to support digital (business) transformation can be observed. In literature, emerging digital technologies are considered as an enabler for the creation of additional value, the strengthening of the customer relationship, and as an accelerator of the servitization process in manufacturing. The introduction of such technologies may result in adaptations of the product & service life cycle as well as the business model. A generic product & service life cycle consisting of four phases - design, simulation, manufacturing, and usage of products and services - serves as a foundation for the integration of digital technologies and related data. It can be observed that there is a gap with respect to data integration between the manufacturing and the usage of products and services. A model-based approach including digital twinning is applied to bridge this gap and to show how data can be integrated along the product & service life cycle. The conceptual approach of such a model-based digital twin environment is presented in form of a meta model. To depict how the integration could be eased and guided in manufacturing, findings of the European project Change2Twin, where a digital twin is established for a paint production pilot, are introduced. This industrial manufacturing pilot was supported by production process models. Additionally, a physical experiment was created to raise awareness for the challenges of digitization and servitization. (c) 2022 Published by Elsevier B.V.

Automated summary

Currently, there is a growing trend of digitization and servitization, using digital technologies and digital twins to support digital transformation. These emerging digital technologies are considered as catalysts for creating added value, strengthening customer relationships, and accelerating the process of servitization in manufacturing. By implementing a model-based digital twin environment, the gap in data integration between manufacturing and product/service usage can be bridged.