Interactive feature extraction for diagnostic trouble codes in predictive maintenance-Reference-Cited by-同舟云学术

Interactive feature extraction for diagnostic trouble codes in predictive maintenance

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Workshop on Interactive Data Mining - WIDM'19
language:
Short-container-title:

Author:

Pirasteh Parivash¹,Nowaczyk Slawomir¹,Pashami Sepideh¹,Löwenadler Magnus²,Thunberg Klas³,Ydreskog Henrik²,Berck Peter¹

Affiliation:

1. Center for Applied Intelligent Systems Research, Halmstad University, Sweden

2. Aftermarket Solutions Department, Volvo Trucks, Gothenburg, Sweden

3. Service Market Products, Volvo Buses Gothenburg, Sweden

Publisher

ACM Press

Reference20 articles.

1. Dentcho Batanov, Nagen Nagarur, and Prapan Nitikhunkasem. 1993. EXPERT-MM: A knowledge-based system for maintenance management. Artificial intelligence in engineering 8, 4 (1993), 283--291.

2. Christine W Chan. 2005. An expert decision support system for monitoring and diagnosis of petroleum production and separation processes. Expert Systems with Applications 29, 1 (2005), 131--143.

3. Christos Emmanouilidis, Erkki Jantunen, and John MacIntyre. 2006. Flexible software for condition monitoring, incorporating novelty detection and diagnostics. Computers in industry 57, 6 (2006), 516--527.

4. Moa Fransson and Lisa Fåhraeus. 2015. Finding Patterns in Vehicle Diagnostic Trouble Codes: A data mining study applying associative classification.

5. Andrew KS Jardine, Daming Lin, and Dragan Banjevic. 2006. A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical systems and signal processing 20, 7 (2006), 1483--1510.

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. DTC-TranGru: Improving the performance of the next-DTC Prediction Model with Transformer and GRU;Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing;2024-04-08

2. Advent of Artificial Intelligence in Automotive Engineering;2023 2nd International Conference on Multidisciplinary Engineering and Applied Science (ICMEAS);2023-11-01

3. DTCEncoder: A Swiss Army Knife Architecture for DTC Exploration, Prediction, Search and Model Interpretation;2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA);2022-12

4. A Semi-Supervised VAE Based Active Anomaly Detection Framework in Multivariate Time Series for Online Systems;Proceedings of the ACM Web Conference 2022;2022-04-25

5. Circular production and maintenance of automotive parts: An Internet of Things (IoT) data framework and practice review;Computers in Industry;2022-04