Predictive Maintenance: Minimize Downtime

Predictive Maintenance: Minimize Downtime

What is predictive maintenance?

Predictive maintenance with Parker SensoNODE wireless sensors and IIoT

Predictive maintenance relies on data, not operating hours, to determine when service is needed. Manufacturers and plants can monitor for environmental and systemic conditions that fall outside of ideal parameters using Industrial IoT, or IIoT.

How IIoT works to predict required maintenance

Industrial IoT relies on a wireless network of sensors that captures data and transmits it to connected devices. IIoT makes it possible for facilities to “work smarter instead of harder,” and a good IIoT software package helps a user gain insights from the historical data.

When devising your IIoT network, it’s important to consider the locations and types of sensor. Machinery is sensitive to conditions such as temperature, pressure, flow, and humidity. Therefore, detecting anomalies in these four areas is a good place to start. A production line’s “trouble spots” are the first place you should focus on when designing your network.

predictive maintenance detects anomalies to prevent unplanned machine downtime

Avoiding unplanned downtime

Unplanned downtime disrupts production, and the costs include lost time and profit. Facilities can work to avoid unplanned downtime by preventing the less-than-ideal conditions that cause it. For example, let’s say you are experiencing periodic air compressor shutdowns that have become unpredictable and annoying. Most air compressors trigger an automatic emergency shutdown at about 220℉. You can connect a temperature sensor at the discharge line to your IIoT network.  Unusual changes in pressure, flow and humidity elsewhere can help identify the root of the problem. Users can set up alerts when certain changes occur. This way, your facility can address a potential problem and avoid a shutdown the next time the operator receives an alert. 

IIoT can help operators control product quality in processes that are sensitive to conditions like temperature and humidity

Increasing productivity and product quality

Changes in operating conditions like temperature can affect product quality. When temperatures don’t fall within parameters, the resulting product could be faulty and may need to be discarded. This results in  wasted time and material, not to mention frustration, because you’re behind schedule.

Wireless temperature sensors like Parker’s SensoNODE Gold can alert an operator to a deviation from parameters so the problem can be addressed as soon as possible. In fact, the sensors in one of Parker’s tube fitting manufacturing facilities. A SensoNODE Gold temperature sensor was placed in the plating bath to monitor that process remotely. If the plating bath was too hot or too cool, the coating (and the product) was no good. With the introduction of a temperature sensor that can be monitored remotely, the facility increased output by nearly 33%. When the temperature fell outside parameters, the operator received an alert and knew to check the plating bath and the product.

What’s the difference between predictive maintenance and preventive maintenance?

You can’t always avoid unplanned downtime with preventive maintenance. Routine, or preventive maintenance, addresses issues related to the filtration and cleaning and lubrication of internal components. If the oil and filters are not changed, the machinery could malfunction. Preventive maintenance happens as scheduled downtime. During this period, fluids and components are checked and replaced if needed. Any data collected on temperature, pressure, flow, and humidity is only relevant to that moment time. You may not have another maintenance period for three, six, or maybe even 12 months. A lot can happen in between scheduled maintenance. Operators may not have a grip on all these conditions at all times. Doing it manually, particularly with multiple machines, is usually not possible. IIoT packages monitor your machinery’s needs in real-time, so predictive maintenance closes the gap that preventive maintenance misses. 

Predictive maintenance does not replace routine maintenance

Predictive maintenance doesn’t address all aspects of maintenance.  IIoT networks are powerful, but they will not alert you of every aspect so you still need to use your eyes. Facilities should continue to check the oil and filters at regularly scheduled intervals. And you should still keep  the area clear of dust and dirt that could end up in your machinery. 

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