HyProCell presents a paper entitled Time Series Display for Knowledge Discovery on Selective Laser Melting Machines at the 20th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL) taking place at The University of Manchester, UK during 14 – 16 November 2019. The oral presentation will be delivered IK4 Lortek’s Head of Science Dr Moreno.
The paper presents a method for displaying industrial time series. It aims to support data and process engineers on the data analytics tasks, specially in the area of Industry 4.0 where data and process joins. The method is entitled SCG, from Splitting, Clustering and Graph making which are its main pillars. It brings two innovations: Samples making and Visualizations. The first one is in charge of build well-suited samples fostered to reach the data exploring objectives, whereas the second one is in charge showing a graph-based view and a time-based view. The final objective of this method is the detection of stable working states on a working machine, which is key for process understanding, while at the same time it enlightens on knowledge discovery and monitoring. The use case in which this work is grounded is the Selective Laser Melting (SLM) industrial process, though the introduced SCG procedure could be applied to any time series collection.
The paper is accessible from Springer with its full citation being:
Moreno R., Pereira J.C., López A., Mohammed A., Pahlevannejad P. (2019) Time Series Display for Knowledge Discovery on Selective Laser Melting Machines. In: Yin H., Camacho D., Tino P., Tallón-Ballesteros A., Menezes R., Allmendinger R. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2019. IDEAL 2019. Lecture Notes in Computer Science, vol 11872. Springer, Cham. DOI: 10.1007/978-3-030-33617-2_29
