Increased digitalization brings new possibilities for Swedish manufacturing companies. This project focuses on what data are needed to feed assembly variation simulation and how this data can be captured and stored efficiently and effectively. The project contributes to increased geometrical quality and better decision support for engineers and designers. The technical value chain from part inspection, to extraction of relevant data, to storage of data in a database, to usage of data in variation simulation (as a digital twin) and to visualization of simulation results as a decision support will be covered. This empowers the industrial value chain from supplier of inspection services, to part manufacturer, database supplier, simulation tool supplier and up to the OEMs. This has the potential to replace prototypes/test series and saves cost, time and reduces the environmental impact.
WP1 focuses on data collection on part level and different methods to measure geometrical deviation, surface roughness and mechanical properties. WP2 specifies the database framework needed, including data integrity, communication between systems and data logistics both within the company and in the whole industrial value chain. WP3 links data to variation simulations to predict geometrical quality of a final product. Enabling technologies for utilizing different kind of input data are specified. Results from WP1 and WP3 are used in WP4 to enrich visualization, used as decision support. Industrial needs will be mapped to available technologies. Finally, WP5 handles project management.
The goal is to mirror the production and make custom information available for industry personnel.
The aim is to develop new models for visualizing and predicting delivery schedule variations in supply chains.
Recent research from Chalmers have shown that by slightly tuning robot motions, the energy use can be reduced by 10 –30%, with preserved cycle time.