How To Get Started
RedRaven brings the full power of internet of things (IoT) technology to your operation in as little as a few weeks, enabling you to predict equipment behavior, focus maintenance efforts on assets that need attention, enhance equipment efficiency, reduce costs, and increase safety.
This revolutionary combination of advanced IoT architecture, devices and monitoring solutions enables you to shift from a reactive to a proactive approach. You’ll benefit by reducing equipment failures, downtime and costly repairs — while increasing your predictability and productivity.
Decide which equipment you want to monitor
Start by separating your rotating equipment into two categories: critical assets and balance-of-plant equipment.
Critical assets: Those assets that are essential to your operation and should they fail, it could shut down production.
Balance-of-plant equipment: Those supporting components and auxiliary systems that are important but would not shutter your operation if they failed.
The technology used and the type of data collected vary between these two categories, so this is a vital step to implement an optimized and cost effective solution.
Define the data you want to see
Our team will help you define the most valuable type and level of service, with a combination of condition monitoring or predictive analytics services depending on the specific characteristics of your assets and their criticality level.
Then, Flowserve will architect a turn key end-to-end solution, from edge devices to cloud connectivity to advanced engineered algorithms to an interactive visualization portal.
Determine access to expertise
The ability to predict why your critical assets might experience issues and then take preventive action before it happens is IoT technology’s greatest benefit. By combining these insights with a team of technical specialists at our Flowserve Monitoring Center and easy access to maintenance services, you’ll have the tools and insights to keep your vital assets up and running.
You can find more information in the RedRaven FAQs below to help further define your specific needs
Condition monitoring provides a snapshot of equipment performance and detects small changes in equipment behaviors, which could be an indicator of a potential failure. Predictive analytics collects comprehensive data and, by using engineered algorithms, can identify the major failure modes at an earlier stage to forecast why your equipment might experience issues and what you can do to minimize disruptions.
Plant operations will receive a near real-time system measurement and analysis. Depending on the service, the analysis will include critical equipment monitoring and failure mode(s), a configurable trending report, efficiency and performance optimization curves, and customizable alerts and alarms.
Monitoring equipment performance leads to real insights (not just data) you can use to make more informed decisions to improve your plant’s efficiency, productivity and reliability.
You can set alerts and be informed when equipment performance deviates from a pre-defined threshold and generate trend reports to see how equipment performs over time.
With this information, you can forecast when to conduct equipment maintenance at the most efficient time (which limits disruptions) or order parts “just in time” to reduce inventory space and purchasing costs. With predictive analytics, you can go a step further to determine an asset’s most likely failure modes and recommended actions to mitigate serious failures.
Predictive Analytics is most beneficial in applications where there is the possibility of increased levels of productivity impairment and/or revenue loss, expensive equipment repairs, and long lead times on replacement equipment.
You should consider condition monitoring for balance-of-plant equipment for and when unplanned downtime results in higher maintenance costs but do not immediately affect your production.
Flowserve Monitoring Center
See how our monitoring center supports your team with insights, alerts and recommendations