Avoiding Equipment Failure’Preventive and Predictive Approaches to Maintenance

Averting a system failure before it happens is an ideal scenario for any engineering company. It keeps business ticking smoothly, ensuring the quality and reliability of service. But how is it possible to know something is going to fail? In fact, technology has come a long way in creating innovative solutions that foresee upcoming engineering risks.                                                                                            

Two of the current approaches available to avoid failure are predictive and preventive maintenance. When integrated into an organization’s enterprise resource planning system, they can become an effective tool in managing and preventing problems.

In this article, we’ll uncover more about the two approaches ”preventive and predictive ”and find out how to choose which option best suits your business needs.

Preventive and Predictive ”What’s the Difference?

Both preventive and predictive maintenance types are proactive measures in ensuring that equipment will not break or experience downtime in the near future. Essentially, it is fixing an issue before it becomes a problem. Although both are pre-emptive, they don’t function in quite the same way. Let’s uncover the differences and discover which, if any, solution comes out on top.

Preventive

Preventive maintenance solutions work by scheduling expected downtime to solve issues preemptively. Such maintenance is carried out based on a schedule to create minimum disruption to the working process.

Consider your car’s oil, for example. Depending on the make and model of the vehicle, you can expect to change the oil somewhere between every 3,000 to 10,000 miles, and sometimes you’ll find your car runs fine even longer.

We all know that oil changes keep things flowing as they should, so if you leave it too long, you could start to experience problems with your engine, fuel consumption, etc. To avoid any unnecessary problems, you undertake the predictive maintenance of changing your oil (and filters), and this is the same issue you need to address in your business on a larger scale.

No matter what equipment you use, every piece has a life span; to maximize its longevity, it requires a little attention every now and again. Preventive maintenance works by ensuring everything functions just as it should by undertaking planned maintenance.

Advantages

• Preventive maintenance is easy to budget for and implement as the required resources and finances will be available.
• It is highly effective at repairing known commonly occurring issues that tend to cause downtime.
• It minimizes the disruption to your business, allowing work to continue as usual, and lowering the cost of failures.

Disadvantages

• Preventive maintenance focuses on commonly recognized errors only, leaving your company vulnerable to unexpected occurrences.
• The right failures may not be caught at the correct time. Preventive maintenance utilizes a schedule to plan activities, which does not account for unforeseen events that may lead to the system breaking earlier.

Predictive

Similar to preventive, predictive maintenance uses a variety of technologies to preempt specific faults within a system. Unlike preventive, this approach doesn’t use recommended service dates but instead focuses on technology to get the job done. An example of its industrial use is Boeing, who used RFID tags and data analytics to optimize aircraft maintenance.

Let’s briefly explore two key pieces of tech that can be combined to create an efficient predictive error detection system:

• RFID sensors. Radiofrequency identification tags work to collect, store, and report information about equipment in real-time. These pieces of IoT kit, including sensors for temperature, vibration, pressure, and more, can detect in advance when equipment is about to fail so it can be repaired in time. They use wireless technology to transfer this information about a failure to the relevant system for it to be repaired.

• Big data and machine learning. Working through large data sets, machine learning models analyze various types of data ”structured and semi-structured ”to develop conclusions about the maintenance needs of equipment, all you to base your repair schedule on facts. The technology allows for the development of accurate predictive models based on real-time data from sensors, as well as historical data about failures.

Overall, predictive maintenance is more sophisticated than preventive. It also has a number of distinct advantages and disadvantages.

Advantages

• Efficient at detecting a fault before it becomes critical, all the while not wasting time and money on maintenance that may not be required.
• Increases the operational life of the component by detecting errors early so they can be corrected to avoid additional issues.
• Saves money in terms of only replacing the parts that are required to be replaced, avoid discrepancy between official product life span and its actual one.
• Predictive maintenance allows engineers to identify not only what is wrong but also the root cause of the issue.

Disadvantages

• The technology doesn’t come cheap; initial and ongoing investments can cost your company a pretty penny to install and maintain.
• Additional staff training may be required to run preventive maintenance.
• Predictive solutions require a certain level of equipment and data which may not be readily available to every company.

Combine Both and Integrate with ERP

Today, many companies engage in custom ERP software development to ensure that all specific processes within the enterprise work in concert. Making preventive and/or predictive maintenance part of your ERP is crucial to ensure control over possible issues.

A combination of both approaches can optimize your maintenance system by creating a more encompassing and effective solution. You can utilize the best of both worlds and lower your risk of unexpected downtime, however at all times you should evaluate three key factors for your business: cost, efficiency, and suitability, to define if the technology is for you.