Inspection Data to Support a Digital Twin for Geometry Assurance
Paper in proceedings, 2018

Geometrical variation is a problem in all complex, assembled products. Recently, the Digital Twin concept was launched as a tool for improving geometrical quality and reduce costs by using real time control and optimization of products and production systems. The Digital Twin for geometry assurance is created together with the product and the production systems in early design phases. When full production starts, the purpose of the Digital Twin turns towards optimization of the geometrical quality by small changes in the assembly process. To reach its full potential, the Digital Twin concept is depending on high quality input data. In line with Internet of Things and Big Data, the problem is rather to extract appropriate data than to find data. In this paper, an inspection strategy serving the Digital Twin is given. Necessary input data describing form and shape of individual parts, and how this data should be collected, stored and utilized is described.

point cloud

Digital Twin




geometrical variation

Big Data


Kristina Wärmefjord

Chalmers, Industrial and Materials Science, Product Development

Rikard Söderberg

Chalmers, Industrial and Materials Science

Lars Lindkvist

Chalmers, Industrial and Materials Science, Product Development

Björn Lindau

Volvo Cars

Johan Carlson

Fraunhofer-Chalmers Centre

Proceedings of the ASME international Mechanical Engineering Congress and Exposition

Vol. 2

ASME International Mechanical Engineering Congress and Exposition
Tampa, Finland,

Subject Categories

Production Engineering, Human Work Science and Ergonomics

Reliability and Maintenance

Areas of Advance




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