Analysis of Production Disturbances with the Use of Big Data: Identifying Quality Issues Through a Case Study at an Electronics Manufacturer

Abstract

In Industry 4.0 and Quality 4.0 one of the key enablers is big data and the analysis of it. The interest in Industry 4.0 and the possibilities that comes with it seems to be limitless. However, the implementation comes with big challenges and there is a big knowledge gap when it comes to implementation. Big data analysis can be one of the key enablers to reduce production disturbances and to gain a more controlled and predictable manufacturing process. Therefore, this thesis has investigated how data can be analyzed and what has to be considered when analyzing production data. A case study has been performed at a company in Sweden that has been gathering data for a while but not yet started the analysis. Through current state mapping of the production and the pre-gathered data, insights of the manufacturing process have been obtained. Production tests were performed where a gap in the data was uncovered in order to investigate whether that could affect the production outcome. Through those investigations, this thesis could conclude that it is of very high interest and importance to have a closed loop of data to enable complete and reliable analysis.