Introduction
An Oil and Gas company wanted their maintenance to be made digital as a part of their mission towards Industry 4.0. All their machines were connected and the BDB team was requested to provide a solution for their maintenance/ monitoring of machine-related issues.
Pre-Requisites
Pipeline to be activated for the entire workflow
Data Generator - Pipeline which generates data based on the API request/
Machine sensors_alert_pipeline - Main Pipeline which detects anomaly from the input data/
Jira_Status_changer - Pipeline which changes status, comments, and assignee of the issue ticket from the dashboard.
Postman API is to be called for generating sensor data & alerts values from the pipeline.
curl --location --request POST 'https://app.bdb.ai/ingestion/dataIngestion' \
--header 'ingestionId: 7319662eed9b-1e58-6834-6778-c93c119d' \
--header 'ingestionSecret: VIyWyZ7nbmw6cBJVv1+tH0eANkqqGjj4xNsNPDUoDMX/unDA1tZb0L5THftaMIUd' \
--header 'Content-Type: application/json' \
--data-raw '[{
"SensorID": ["P1_U1M1S1"],
"duration": 60,
"alert" : "no"
}]'
Alert: yes/no will trigger the alert/normal values respectively.
Dashboard to look for
Manager - Dashboard which consists of both live monitoring, past alert records, and issue ticket.
Unit Engineer - Dashboard which consists of issue tickets for the respective Engineers.
Data As APIs
Last 10 mins data
Last 10 mins data with sensor ID as parameter:
Last updated