Data analysis identifies product issue

A customer experienced a complex quality issue on their final product. Traditional methods failed to identify the cause of the problem.

OCAS suggested to analyse the issue by carrying out measurements on the steel sheets at different stages of the production process. The obtained data was analysed and ‘translated’ in a set of quantities expressing the quality of the incoming material.

Statistical analysis revealed a clear correlation between those quantities and the customer’s evaluation score.  From this correlation between different indicators extracted from the measured data and the customer’s quality evaluation score, it was possible to identify the upstream processing step causing the quality issue. This highly valuable information will now enable both customer as well as supplier to look for a solution to solve the problem.

Thanks to this digital approach the complex problem could be addressed in a limited amount of time.

“In our digital approach, modelling goes hand in hand with physical experiments in the lab. Managing large quantities of data and comparing these with the customer’s quality evaluation is a good example of how digitalisation leads to knowledge to create better products as well as better customer experiences.”

Steven Cooreman, Senior Research Engineer, Applications & Solutions Department, OCAS
Patrick Goes, Senior Research Engineer Applications & Solutions department, OCAS