@ARTICLE{Perzyk_M._Introducing_2019,
 author={Perzyk, M. and Dybowski, B. and Kozłowski, J.},
 volume={vol. 19},
 number={No 1},
 journal={Archives of Foundry Engineering},
 pages={53-57},
 howpublished={online},
 year={2019},
 publisher={The Katowice Branch of the Polish Academy of Sciences},
 abstract={The paper presents some aspects of a development project related to Industry 4.0 that was executed at Nemak, a leading manufacturer of the aluminium castings for the automotive industry, in its high pressure die casting foundry in Poland. The developed data analytics system aims at predicting the casting quality basing on the production data. The objective is to use these data for optimizing process parameters to raise the products’ quality as well as to improve the productivity. Characterization of the production data including the recorded process parameters and the role of mechanical properties of the castings as the process outputs is presented. The system incorporates advanced data analytics and computation tools based on the analysis of variance (ANOVA) and applying an MS Excel platform. It enables the foundry engineers and operators finding the most efficient process variables to ensure high mechanical properties of the aluminium engine block castings. The main features of the system are explained and illustrated by appropriate graphs. Chances and threats connected with applications of the data-driven modelling in die casting are discussed.},
 type={Artykuły / Articles},
 title={Introducing Advanced Data Analytics in Perspective of Industry 4.0 in a Die Casting Foundry},
 URL={http://journals.pan.pl/Content/109231/PDF/AFE%201_2019_09.pdf},
 doi={10.24425/afe.2018.125191},
 keywords={Application of information technology to the foundry industry, mechanical properties, Die casting, process control, Data analytics},
}