Case Studies olOne for Condition Monitoring

	olOne for Condition Monitoring

olOne for Condition Monitoring

Technology Category	Analytics & Modeling - Real Time Analytics Sensors - Pressure Sensors Sensors - Temperature Sensors
Use Cases	Machine Condition Monitoring
Challenge	Given to identical production pipe lines in an industrial plant each one with one motor equipment monitored by temperature and pressure sensors: check if the motors parameters on both production lines behave the same way. This operational context, requires that data processing system must be able to analyze in real-time more than 1M+ data points/s per sensors. Read More
About Customer	Industrial plant Read More
Customer Name	Undisclosed Read More
Solution	Thanks to olOne technology this complex context can be handled by writing, through the IDE, this simple event: hol("temp1_line1","PT2H").trend().eq(hol("temp1_line2","PT2H").trend()). and( hol("pressure1_line1","PT2H").trend().eq(hol("pressure1_line2","PT2H").trend()) ) .is("Works well") Then, you can have your condition monitoring solution optimized for your device ready to run. Read More Log in to view content
Data Collected	Motor Metrics, Pressure, Process Procedure, Production Efficiency, Temperature Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Real Time Analytics

Sensors - Pressure Sensors

Sensors - Temperature Sensors

Use Cases

Machine Condition Monitoring

Challenge

Given to identical production pipe lines in an industrial plant each one with one motor equipment monitored by temperature and pressure sensors: check if the motors parameters on both production lines behave the same way. This operational context, requires that data processing system must be able to analyze in real-time more than 1M+ data points/s per sensors.

About Customer

Industrial plant

Customer Name

Undisclosed

Solution

Thanks to olOne technology this complex context can be handled by writing, through the IDE, this simple event: hol("temp1_line1","PT2H").trend().eq(hol("temp1_line2","PT2H").trend()). and( hol("pressure1_line1","PT2H").trend().eq(hol("pressure1_line2","PT2H").trend()) ) .is("Works well") Then, you can have your condition monitoring solution optimized for your device ready to run.

Data Collected

Motor Metrics, Pressure, Process Procedure, Production Efficiency, Temperature

Impact #1	[Efficiency Improvement - Production Uptime] critical outages and unplanned downtime can be avoided by identifying potential equipment failure.
Impact #2	[Cost Reduction - Inventory Management] Excessive inventory of spare parts to reduce downtime can be eliminated. Costly truck rolls can be prevented by sending the right supplies when needed.

Impact #1

[Efficiency Improvement - Production Uptime]
critical outages and unplanned downtime can be avoided by identifying potential equipment failure.

Impact #2

[Cost Reduction - Inventory Management]
Excessive inventory of spare parts to reduce downtime can be eliminated. Costly truck rolls can be prevented by sending the right supplies when needed.

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Overview

olOne for Condition Monitoring

Operational Impact