Optimized high pressure die casting process with advanced digitalization
|Coordinator||Swerea SWECAST AB|
|Funding from Vinnova||SEK 1 200 000|
|Project duration||August 2017 - August 2018|
|Venture||Strategic innovation programme for process industrial IT and automation – PiiA|
Purpose and goal
The project has generated knowledge about which process data is currently being logged by the participating die casting companies, and what data is still missing in order to create algorithms that allow for predictive maintenance. Several factors unrelated to the die casting machine itself could be identified as having a significantly detrimental effect on the OEE number (overall equipment efficiency). In the long run, the knowledge gathered within the project may lead to fulfillment of the main goal of increasing the OEE of the participating die casting companies by 10 %.
Expected results and effects
As expected, the project has resulted in knowledge and practical experience with respect to sensor technology and methods for logging and analyzing data stemming from older die casting machines; this will form part of the basis for further work aimed at digitizing the die casting industry. In addition, all participants have gained insights into which factors other than the die casting machines themselves that negatively affect the production. One effect of this project is an increased awareness of the importance of logging and continually analyzing production data.
Planned approach and implementation
In the project’s initial stage an investigation was conducted into which data is already being logged. However, a root cause analysis showed a necessity for further logging; quantitatively and qualitatively new data was needed. A second root cause analysis at the end of the project led to the same conclusion. The approach taken here works well in principle, but it is important that identification of currently logged data and analysis of additional needs should be carried out as soon as possible in future projects, since the time required to gather a sufficient amount of data may be long.