PROPID PROduction development using Product Individual Data

Important results from the project

The purpose of this project was to investigate the possibility of creating knowledge based on existing big data, without having to experience the process of learning from mistakes. Hence, the focus has been to predict problems by analyzing big data. Basically, this was both a feasibility study and a high-risk project and the difficulty of identifying potential knowledge gaps was evident.

Expected long term effects

The hypothesis has not been confirmed in this project by the data-set used for the analysis. By carrying out practical tests on Big Data at Volvo, we have been able to clarify that existing production data could not be consistently correlated, to market problems. This does not mean that it is not possible to build knowledge on data, but it may indicate that the analysis method used was not the right for an unstructured data set. The research will continue with the focus on building knowledge on more structured data such as written deviation reports.

Approach and implementation

The project has been carried out in collaboration between Chamers, AB Volvo and Rejmes Transportfordon. The consortium made it possible to explore problems that arise in development or production, and which arise in the marketplace. The arrangement as such was therefore valuable and gave many insights that could not be obtained without an extended value chain. Case studies on data collection on the exchange / re-manufacture of high-value components such as Turbo and compressors were made possible thanks to this approach.