English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In large-scale industrial plants, fault diagnosis and treatment are conducted by field experts. However, there is a limit to relying on limited number of field experts for all faults. For this reason, the industry records a failure report and accumulates it for use in future trouble shooting. However, it is almost to impossible to search from failure report and reuse this knowledge in the real time so it produces huge delay and becomes a critical industrial disaster. In this paper, we propose the problematic knowledge extraction framework, which allows transferring failure reports to structured knowledge and who filed experts can construct their knowledge easily. The framework automatically transfers the content of analyzed failure report to the structured knowledge, and it provides UI for users to easily modify the knowledge base. The proposed knowledge-reuse approach can be expected to use for domain knowledge maintenance and the industrial plant management automation system.

Failure Knowledge Extraction Framework from Failure Reports in Large Industries