research-article

A Visual Analysis Approach for Understanding Durability Test Data of Automotive Products

Authors:

Lei RenAuthors Info & Claims

ACM Transactions on Intelligent Systems and Technology (TIST), Volume 10, Issue 6

Article No.: 70, Pages 1 - 23

https://doi.org/10.1145/3345640

Published: 12 December 2019 Publication History

Abstract

People face data-rich manufacturing environments in Industry 4.0. As an important technology for explaining and understanding complex data, visual analytics has been increasingly introduced into industrial data analysis scenarios. With the durability test of automotive starters as background, this study proposes a visual analysis approach for understanding large-scale and long-term durability test data. Guided by detailed scenario and requirement analyses, we first propose a migration-adapted clustering algorithm that utilizes a segmentation strategy and a group of matching-updating operations to achieve an efficient and accurate clustering analysis of the data for starting mode identification and abnormal test detection. We then design and implement a visual analysis system that provides a set of user-friendly visual designs and lightweight interactions to help people gain data insights into the test process overview, test data patterns, and durability performance dynamics. Finally, we conduct a quantitative algorithm evaluation, case study, and user interview by using real-world starter durability test datasets. The results demonstrate the effectiveness of the approach and its possible inspiration for the durability test data analysis of other similar industrial products.

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Index Terms

A Visual Analysis Approach for Understanding Durability Test Data of Automotive Products
1. Human-centered computing
  1. Visualization
    1. Visualization application domains
      1. Visual analytics

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Published In

cover image ACM Transactions on Intelligent Systems and Technology

ACM Transactions on Intelligent Systems and Technology Volume 10, Issue 6

Special Section on Intelligent Edge Computing for Cyber Physical and Cloud Systems and Regular Papers

November 2019

267 pages

ISSN:2157-6904

EISSN:2157-6912

DOI:10.1145/3368406

Editor:
Yu Zheng
JD Finance, China

Issue’s Table of Contents

Copyright © 2019 ACM.

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Association for Computing Machinery

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Publication History

Published: 12 December 2019

Accepted: 01 July 2019

Revised: 01 July 2019

Received: 01 December 2018

Published in TIST Volume 10, Issue 6

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Funding Sources

National Key Research and Development Program of China
National Science Foundation of China
National Natural Science 8 Technology Fundamental Resources Investigation Program of China
Anhui Province Key Laboratory of Industry Safety and Emergency Technology
Natural Science Foundation of Hunan Province

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