Determine the lifetime of factory components and machines, predict when repairs will be needed, and schedule maintenance accordingly. Keep your business operating smoothly while reducing or even eliminating unplanned downtime.
By pairing intuitive machine learning tools with cloud-based or edge computing systems to analyze data from your shop floor, RapidMiner helps you keep a close eye on your equipment’s health.
Leading organizations trust RapidMiner to keep them operating optimally.
Plan Maintenance & Prevent Equipment Failure
In the past, preventative maintenance was based on either time or cycles of use. This helped prevent equipment failure, but it also meant stopping a well-functioning machine to conduct maintenance, even if there was no indication of anything wrong.
Predictive maintenance offers a better way to maintain your equipment without disrupting production. You’ll have the confidence to keep machines running, knowing that you can catch and address issues that aren’t easily detectable, avoiding costly failures and equipment downtime.
Four Reasons Predictive Maintenance Wins
Improve maintenance planning: Optimize maintenance schedules with thoughtfully allocated resources and reduce mean time-to-repair.
Lower maintenance costs: Don’t waste money by performing maintenance when it isn’t needed; only conduct repairs when there’s an issue.
Avoid unplanned maintenance: Minimize unplanned downtime and catastrophic failures that put your business at risk.
Root-cause analyses: Find causes of equipment malfunctions and work with supplies to switch off reasons for high failure rates, increasing return on assets.
Key Predictive Maintenance Components
Data warehouses to store historical data from IoT sensors.
Domain experts to understand the data, evaluate potential models, and adjust maintenance plans. Real-time IoT connectivity to measure and record equipment states.
RapidMiner for Predictive Maintenance
You’re ready to embrace the Industry 4.0 revolution and move to predictive maintenance. But how? With RapidMiner, digital manufacturers are able to predict the lifetime of factory components and machines to intelligently plan maintenance, while reducing or even entirely eliminating failures.
Using state-of-the-art machine learning tools that anyone can master, paired with cloud-based or edge computing systems to read in data from your shop floor, RapidMiner provides a real-time perspective on the health of your equipment.
Check out the customer stories below and see how RapidMiner is being used to achieve predictive maintenance success.
Superb Machine Learning Environment
RapidMiner accurately does basic ETL for us. It is a proven way to perform various kinds of data computation and machine learning capabilities. Smoothly runs and can be handled easily. Basically, it has no drawback aside the technicalities involved in using most machine learning tools.
Food and Beverage
Reliable Data Analytics Tool
The tool has helped the business to minimize the manhours spent to do manual jobs in Excel, it is really easy to upload files and work and transform the parameters to your liking.
Senior Supply Chain Transformation Analyst
Automated Machine Learning
RapidMiner Studio is an awesome visual workflow designer. The way they present visually is so unique. It helps in speeding and automating the creation of visual models. It helps in creating models in only 5 clicks by automated machine learning.
Senior Software Engineer
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Avoid Full Operations Shutdown with Predictive Maintenance
Learn how simple repairs and maintenance can have massive downstream implications, and what this auto parts manufacturer did to reduce out-of-service times.