Predictive maintenance is a data-driven maintenance strategy that relies on cutting-edge technology and carefully chosen tools to proactively maintain your equipment. The strategy uses condition monitoring and data analytics to spot potential defects in your machinery before they become serious problems. When you implement predictive maintenance tools effectively, this approach can save time and money, while dramatically increasing productivity.
What is predictive maintenance?
Predictive maintenance is a proactive approach to maintenance. Unlike traditional maintenance strategies, such as preventive maintenance, predictive maintenance is not time-based. Instead, predictive maintenance uses data from the machine itself to dictate when maintenance activities are needed.
Predictive maintenance starts with data collection. Sensors and smart IoT devices track your assets’ power usage, temperature, and vibration. Over time, that data creates a detailed profile of your equipment and its changes over time.
From there, analytics software compares real-time data from your assets against a baseline of optimal performance indicators. When your real-time data is outside the threshold for normal operation, that’s often the first sign of a problem. Your maintenance team will then get an alert letting them know the asset requires attention.
Predictive maintenance allows you to have gives you eyes and ears on your assets, all the time. It lets you to “see” problems as soon as they arise, so that you can fix what’s broken, without wasting time and money on unnecessary inspections and tune-ups. Learn more about the many benefits of predictive maintenance.
Why are predictive maintenance tools important?
Predictive maintenance tools give you insights into just about every part of your equipment. To implement predictive maintenance effectively, you need a steady supply of real-time condition data for each of your critical assets. You’ll need sensors and smart devices to collect, transmit, and store that data. Ideally, condition-monitoring sensors should be placed on as many parts of your critical equipment as possible, so that you can pinpoint the exact location of any defects.
Predictive maintenance also relies on data analysis tools to interpret and extract actionable insights from the large volume of health and performance data now coming from your machines. Today’s data analytics are often powered by machine learning, which allows them to quickly sift through mountains of numbers and identify patterns. Data analytics can tell you, for example, what it means when a motor part starts to vibrate at a slightly higher frequency and then alert your maintenance crews when there’s an issue that needs attention.
What are the best predictive maintenance tools?
Every operation is different, which means that you’ll need different predictive maintenance tools depending on your industry and your equipment. However, there are a few key predictive maintenance tools that can make a difference for just about any industry.
Vibration monitoring
Vibration sensors collect data about the frequency of the vibrations emitted by your equipment. Remote vibration sensors can automatically send data to cloud-based software for analysis, so there’s no need to interrupt operations to manually inspect your equipment. Depending on the equipment, remote sensors may also be much safer than sending maintenance teams to hazardous or hard-to-reach locations to inspect the assets.
Vibration monitoring can identify early warning signs of machine failure on rotating equipment across all industries–from remote oil and gas sites to general manufacturing facilities. The sensors are easy to install and make it easy for just a few team members to monitor assets throughout your entire facility.
Temperature monitoring
Temperature monitoring sensors measure changes in temperature over a period of time. Similar to vibration monitoring, changes in temperature are often the first indicators of a potential problem on your machines. For example, temperature sensors can identify overheating motors and overloaded circuit boards.
Power monitoring
Finally, power monitoring sensors can track changes in power supply levels in real time. The best power monitors can also send automatic alerts to smartphones or other devices, so that your team is never caught off-guard by an unexpected power surge or loss of power.
Predictive Maintenance and CMMS Software
CMMS (Computerized Maintenance Management System) software connects the dots from all the data that your sensors collect. CMMS software stores and organizes all that data so that you can make sense of it. It allows your teams to get a comprehensive view of your maintenance activity and equipment health at any given time. Predictive maintenance is a powerful approach to machine maintenance, and with the right tools, it can take your facility to new levels of productivity and uptime.