Data Analysis and Visualization of Mechanical Properties of Aluminium Coils, Focusing on Chemical Composition, Annealing Temperatures and Holding Time

Abstract:

As a producer of aluminium coils in a broad variety of applications AMAG faces challenges to control and monitor a long, multi-step production process with an immense number of parameters. Identifying impactful parameters or outliers becomes increasingly difficult when considering multiple production steps. Monitoring many coils over a big set of parameters manually is difficult, time consuming and error-prone and thus an unreasonable endeavour. To support employees in technology- and process-oriented domains, AMAG data scientists develop analytical tools for data exploration and data analysis. Based on material data containing mechanical properties in deformation tests, chemical composition, hot rolling temperature, intermediate annealing, and pre-heating duration we propose a framework of data collecting mechanisms and subsequent statistical methods to analyse and visualise data. The produced visuals can be interactively explored by material experts to gain better understanding of the complex interactions in production parameters and the effect on mechanical properties. Incorporating many coils at once, the framework offers a means to point out problems in process stability. A collaboration and a feedback loop between material scientists and data scientists is key to further develop advanced analytical methods.

• Periodical: Key Engineering Materials (Volume 968)
• Pages: 123-128
• DOI: https://doi.org/10.4028/p-c9CP1l
• Online since: December 2023
• Authors: Patrick Pfeiffer*, Josef Berneder, Alexander Haidenthaler, Peter Schulz
• Keywords: Chemical Composition, Feature Selection, Industrial Manufacturing, Interactive Visual Analytics, Least Angle Regression, Tensile Testing

References

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DOI: 10.1214/009053604000000067