Banca de DEFESA: AGUINALDO BEZERRA BATISTA JUNIOR

Uma banca de DEFESA de DOUTORADO foi cadastrada pelo programa.
STUDENT : AGUINALDO BEZERRA BATISTA JUNIOR
DATE: 08/10/2021
TIME: 09:00
LOCAL: meet.google.com/skr-exkc-ypd
TITLE:

A knowledge graph data-driven approach for analyzing industrial alarm and event records 

KEY WORDS:

alarms and events, knowledge graph, natural language processing, data visualization.

PAGES: 150
BIG AREA: Engenharias
AREA: Engenharia Elétrica
SUBÁREA: Eletrônica Industrial, Sistemas e Controles Eletrônicos
SPECIALTY: Automação Eletrônica de Processos Elétricos e Industriais
SUMMARY:

Alarm and event logs make up a voluminous and dormant historical repository of tabular-like data, commonly undervalued or overlooked in manufacturing. Although they are a potentially rich source of relevant information about the monitored plant or process, these records are taken for analysis only as a last resort, mainly due to the difficulties imposed by the large volume and low expressiveness of those databases. Such oversight is no longer acceptable in the contemporary data-oriented scenario, already ubiquitous in several productive sectors and gaining prominence in traditional manufacturing, especially due to the advent of the Industry 4.0 paradigm. Therefore, it is proposed to transpose these bases to a more expressive and flexible representation domain, allowing a more proactive exploration of the episodes reported in the records and, consequently, entailing more agile incident, anomaly, compliance, and performance analysis tasks. For such, from the recognition of an ontology, entities, attributes, and associations virtually immersed in the operational context described in the records are mapped into a Knowledge Graph (KG). The approach uses Exploratory Data Analysis, Natural Language Processing, Network Analysis, Multivariate Analysis, and Composite Indicators techniques to derive a myriad of aspects, properties, and relations from data, which are incorporated as hierarchical, temporal, and similarity relationships (edges) between identified entities (nodes). The visualization of the KG is dynamic and interactive, with different visualization modes and levels of detail. Evaluation scenarios are designed to demonstrate the effectiveness of the approach.

BANKING MEMBERS:
Presidente - 2885532 - IVANOVITCH MEDEIROS DANTAS DA SILVA
Interno - 1153006 - LUIZ AFFONSO HENDERSON GUEDES DE OLIVEIRA
Externo ao Programa - 1555898 - DIEGO RODRIGO CABRAL SILVA
Externo ao Programa - 1775264 - GUSTAVO BEZERRA PAZ LEITAO
Externo à Instituição - JUAN MOISES MAURICIO VILLANUEVA - UFPB
Externo à Instituição - PLACIDO ANTONIO DE SOUZA NETO - IFRN