Visual analysis of blow molding machine multivariate time series data

• Published in: Journal of visualization Vol. 25; no. 6; pp. 1329 - 1342
• Main Authors: Musleh, Maath, Chatzimparmpas, Angelos, Jusufi, Ilir
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 2022; Springer Nature B.V
• Subjects: Best practice; Blow molding machines; Classical and Continuum Physics; Clustering; Computer Imaging; Computer Science; Dashboards; Datavetenskap; Decision making; Domains; Engineering; Engineering Fluid Dynamics; Engineering Thermodynamics; Evaluation; Factories; Heat and Mass Transfer; Industrial plants; Multivariate analysis; Pattern Recognition and Graphics; Regular Paper; Scientific visualization; Subject specialists; Time series; Time series data; Unsupervised machine learning; Vision; Visualization; Unsupervised machine learning; Visualization; Time series data
• ISSN: 1343-8875; 1875-8975; 1875-8975
• DOI: 10.1007/s12650-022-00857-4

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. The tool is an interactive dashboard with multiple coordinated views supporting the exploration from both local and global perspectives. In summary, 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. We also conducted a case study with a domain expert to validate the potential application of the tool in the real-life context. Finally, we assessed the usability and usefulness of the tool with a two-layer summative evaluation that showed encouraging results. Graphical Abstract