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M. Musleh, A. Chatzimparmpas, I. Jusufi:
"Visual Analysis of Industrial Multivariate Time Series";
in: "The 14th International Symposium on Visual Information Communication and Interaction", Association for Computing Machinery, 2021, ISBN: 9781450386470, S. 1 - 5.

The recent development in the data analytics field provides a boost in production for modern industries. Small-sized factories intend to take full advantage of the data collected by sensors used in their machinery. The ultimate goal is to minimize cost and maximize quality, resulting in an increase in profit. In collaboration with domain experts, we implemented a data visualization tool to enable decision-makers in a plastic factory to improve their production process. We investigate three different aspects: methods for preprocessing multivariate time series data, clustering approaches for the already refined data, and visualization techniques that aid domain experts in gaining insights into the different stages of the production process. Here we present our ongoing results grounded in a human-centered development process. We adopt a formative evaluation approach to continuously upgrade our dashboard design that eventually meets partners' requirements and follows the best practices within the field.

https://publik.tuwien.ac.at/files/publik_300419.pdf