Journal Automotive Engineering

Understanding Failure Mode Effect Analysis Data using Interactive Visual Analytics

Rahul Basole, Ahsan Qamar, Biswajyoti Pal, Michael Corral, Matthew Meinhart, Arpit Narechania

IEEE CG&A · 2019

DOI Video Demo

Teaser for Understanding Failure Mode Effect Analysis Data using Interactive Visual Analytics

Abstract

Providing actionable insights through interactive visual analytics is essential to effective decision making. Yet, many complex systems engineering (SE) domains still lack such tools. Design reviews are often still based on static snapshots of data, without any dynamic interaction, data curation, and view creation capabilities to answer salient analysis questions. In this study, we report on a tool called DataHawk that helps answer common questions associated with one prominent SE context, namely failure mode and effect analysis (FMEA). The tool provides powerful exploration capabilities that enable system engineers, designers, and managers to probe FMEA data from multiple starting points, build questions dynamically, and find triangulated answers using multiple views rapidly. Field results are illustrated through a usage scenario from the automotive industry and show that the tool demonstrates the needed versatility, scalability, and effectiveness for real-world engineering data.

Citation

@article{basole2019understanding,
    author = {Basole, Rahul C and Qamar, Ahsan and Pal, Biswajyoti and Corral, Michael and Meinhart, Matthew and Narechania, Arpit},
    title = {{Understanding Failure Mode Effect Analysis Data Using Interactive Visual Analytics}},
    journal = {IEEE Computer Graphics and Applications},
    year = {2019},
    volume = {39},
    number = {6},
    pages = {17-26},
    doi = {10.1109/MCG.2019.2944230},
    url = {https://doi.org/10.1109/MCG.2019.2944230},
    publisher = {IEEE}
}