Condition Monitoring
with Sightprobe
Condition monitoring (CM) is the process of monitoring a particular condition in machinery (such as vibration, temperature, etc) to identify changes that could indicate a developing fault. It is a major part of predictive maintenance as implementing condition monitoring allows for maintenance to be scheduled and preventive actions taken to prevent further failure and subsequent unplanned downtime.
Rotating Equipments
Condition monitoring has a wide range of applications right across industry wherever there is machinery in use. Here are some commons applications:
Electric Motors
Motors are an essential part of most productions. They are highly important to production uptime, as they ensure everything else is running smoothly.
HVAC
HVAC systems comprise several critical asset types, and monitoring them can enhance reliability, minimize downtime, and streamline the maintenance process.
Pumps
Pumps are one of the most critical asset types in most industries. By monitoring patterns in vibration, it becomes possible to prevent expensive pump failures.
Belts
Belts are used primarily for transporting materials such as ore, coal, and other mined resources over short or long distances in a continuous and efficient manner.
Compressors
Compressors play a vital role in many industries. Monitoring the vibration patterns in these machines is crucial in preventing costly failures and ensuring smooth operation.
Gears & Bearings
Across all asset types, machine failures are often caused by misinstallation or wear in gears and bearings. By predicting these types of faults you avoid expensive downtime.
How does Sightprobe work?
1. (Wireless) sensor collects surface temperature, triaxial vibration data and calculate time domain KPIs, frequency domain spectrum, transmits to the gateway via wireless mesh network.
2. Gateway transfers data from the sensors to the cloud platform via Ethernet, WIFI or GSM/LTE.
3. IoT Cloud Platform;
- decodes, processes, analyzes and stores the data received,
- visualizes analyzed data to users on dashboards,
- executes user rules based on both periodic controls and event based where new data received. These rules check data validity and create violation records and notifications upon any anomaly detected,
- creates scheduled reports as attachment of emails or instant download from user requests.
What is the route
of data in Sightprobe?
Data Collection
Wireless sensors are battery operated, so most of the time they sleep. Internal timers wake the sensor up for specific periods of time to measure surface temperature and vibration of machine. Math calculations from measured data take place at edge and sent to gateway directly or through another neighbor node. Gateway forwards data to cloud through wired or wireless WAN connection.
Cloud Analysis
IoT Cloud Platform accepts, extracts, stores and analyzes both time and frequency domain data. Time domain data (KPIs) consist surface temperature, 3-axis RMS, peek to peek, zero to peek of vibration velocity and acceleration, kurtosis and crest factor. Frequency domain data consist triaxial FFT conversion of vibration RMS acceleration calculations.
Get Notified
Users can create rules from off-the-shelf templates in order to trigger notification upon an anomaly detected. Rules can be applied for whole organization, just for specific facilities, even for specific asset groups or just assets. Reports can be generated instantly or can be scheduled to be received as email attachments.
What are Sightprobe advantages?
Condition monitoring is becoming an essential tactic for machine maintenance groups, crucial in their daily tasks. Primarily, it enables these Maintainers to make educated choices regarding the performance and upkeep of their equipment. Beyond aiding the Maintainers, condition monitoring empowers firms to gather and scrutinize data essential for enhancing machine efficiency, ensuring the longevity of assets, and refining their maintenance methodologies.
Early failure prediction
In essence, condition monitoring employs various indicators to forecast three key aspects. Firstly, it predicts if an asset is likely to fail. Secondly, it determines the manner of potential failure, and thirdly, it estimates the available window to repair or replace the asset before it ceases to function. This knowledge enables the scheduling of maintenance to align with production demands.
Avoid Unplanned Downtime
The capability to schedule downtime in industrial settings is extremely advantageous, given the often grossly underestimated true cost of unplanned downtime from asset failure. Several often overlooked cost elements include:
⦿ The actual expense of unexpected production delays,
⦿ The necessity of paying maintenance staff overtime for asset replacement,
⦿ The potential for other machines to be damaged due to the severity and nature of the machine failure,
⦿ The expense involved in maintaining a large inventory of spare parts in anticipation of any asset malfunction.
With Sightprobe, you're alerted in advance about any impending asset failures, sometimes 6 months ahead, allowing for the strategic procurement of replacement parts only when necessary.
Maximize ROI
Predictive maintenance using condition monitoring allows you to maximize the return on investment in your mechanical assets. By monitoring the actual condition of your machine, you can inspect, fix or replace the machine only when it’s necessary, and not before.
Our solution has both hardware
and software components
CM Software Subscription Prices
Pricing tables only include software licencing per sensor. They do not include hardware prices. Hardware prices are depend on the application and project. Please request quotation with your requirements.
Titanium
$20/month- Temperature Analysis
- Vibration KPI Analysis
- Vibration Spectrum Analysis
- Machine Health Scoring
Gold
$25/month- Temperature Analysis
- Vibration KPI Analysis
- Vibration Spectrum Analysis
- Machine Health Scoring
Platinium
Coming Soon- Temperature Analysis
- Vibration KPI Analysis
- Vib. Spectrum Analysis
- Machine Health Scoring
Titanium
$200/year- Temperature Analysis
- Vibration KPI Analysis
- Vibration Spectrum Analysis
- Machine Health Scoring
Gold
$250/year- Temperature Analysis
- Vibration KPI Analysis
- Vibration Spectrum Analysis
- Machine Health Scoring
Platinium
Coming Soon- Temperature Analysis
- Vibration KPI Analysis
- Vibration Spectrum Analysis
- Machine Health Scoring
Get Every Single Update
From There.
- 29 January 2024
- Knowledge
How to Generate Reports?
How to Generate or Schedule Reports? You can find 5 minutes video below telling how to generate report on demand or how to schedule reports to receive periodically as an
- 22 January 2024
- Knowledge, Predictive Maintenance
Motor Speed Harmonics on Spectrum Chart
The Importance of Motor Speed Harmonics on Spectrum Displaying motor speed harmonics on a spectrum chart is crucial in the field of machinery maintenance and diagnostics, particularly for technicians and
- 22 January 2024
- Knowledge, Predictive Maintenance
Sightprobe Rule Management Example
Sample Rule Adding & Disabling Example You can find 5 minutes video below telling how to define new rule from the template, how to provide parameters (criterion, actions, etc), how
- 18 January 2024
- Knowledge, Predictive Maintenance
What is Spectrum Analysis and How is it Useful?
Introduction In the realm of condition monitoring for rotating equipment, spectrum analysis emerges as a pivotal technique. It’s not just a tool; it’s a window into the unseen world of
- 17 January 2024
- Knowledge, Predictive Maintenance
Key Performance Indicators that Sightprobe analyze
K.P.I. What is Key Performance Indicator? A Key Performance Indicator (KPI) is a measurable value used to evaluate the success of an organization, team, or individual in achieving specific objectives.
- 15 January 2024
- Communication, Knowledge
What is Wireless Sensor Network
Wireless Sensor Networks (WSN) refer to a group of spatially distributed and dedicated sensors for monitoring and recording the physical conditions of the environment and organizing the collected data at
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