The main purpose of predictive maintenance is to proactively predict and prevent the failure of in-service equipment and operating software by providing scheduled maintenance to the equipment before it fails.

Predictive maintenance combines historical and current data analysis along with additional techniques to pinpoint the expected time of equipment failure and implements planned downtime to repair and address the equipment in advance of an unplanned or unexpected failure.

Machines and equipment are designed to operate at a particular capacity for a certain period of time. Regular maintenance is required to keep equipment operational and running in order to meet the needs of the business that it serves. Predictive maintenance provides businesses with more uptime of their in-service equipment and keeps operations running smoothly.

Predictive maintenance or “planned maintenance” is an excellent strategy for the businesses that hold physical assets to employ as it operates under the premise of understanding that it is not a matter of “if” a piece of equipment will fail, but “when.

As businesses become proactive in their ability to monitor, predict, and prevent maintenance issues predictive maintenance is playing a much bigger part in preventing extended equipment downtime and saving companies millions of dollars.

How Predictive Maintenance Works

Predictive maintenance operates the premise of creating a maintenance schedule based on the performance of similar equipment maintenance schedules including past breakdowns and failures. Based on data collected from similar operating equipment, predictive maintenance provides a relevant time frame and prediction of when that equipment will fail. The goal of predictive maintenance is to follow the preset schedule for expected equipment failure and provide maintenance in advance of the expected failure.

Operating on a predictive maintenance schedule allows in-service equipment to have more in service hours and prevent having to employ reactive maintenance which is unplanned and comes into play after the equipment has already failed.

Brands like Andromeda Systems Inc. employ predictive maintenance strategies to keep their client’s physical assets and fleets of up and running with the goal of improving performance and reducing the life-cycle costs of in-service equipment. Andromeda Systems Inc. has also created an enterprise asset management software called OptiAM.

Predictive Maintenance Techniques and Strategy

Businesses choose to implement predictive maintenance strategies based on the method that works best for their individual business needs. There are many available options for companies to implement predictive m maintenance into their daily operations processes. Some common predictive maintenance techniques that business employ includes:

  • Vibrational Analysis
  • Thermal Imaging
  • Electronic Sensors

Let’s look at each one of these predictive maintenance techniques in detail.

Vibrational Analysis

Rotating machines and equipment vibrate or oscillate at a particular speed based on the equipment type. Vibrational Analysis monitors the vibrations of rotating equipment and can predict possible imminent failures by noting any changes in the desired vibration and scheduling maintenance in advance of the equipment actually failing. This means that if a particular piece of equipment operates at a certain number of rotations per minute and those revolutions increase or decrease from the average that maintenance is likely needed.

Thermal Imaging

Monitors the thermal output of operating machines and equipment and can quickly identify equipment that will soon need service based on the thermal output reading that the imaging provides if those readings aren’t in alignment with the desired operational capacity and performance.

Excessive heat signatures of lack of signature can indicate an impending issue and alert technicians to begin planned maintenance on the equipment prior to its’ complete failure.

Equipment Sensors

Using equipment sensors involves installing sensors in specific locations that are connected to a data system. The combination of the reporting sensors and data analysis provides the monitoring technicians with a specified range of time for when the monitored equipment is most likely to fail.

Using a combination of the strategies discussed here and other strategies as business decision makers see fit will allow for a company to operate at it’s fullest potential with a small window for unexpected failures, at least in the area of equipment.

By using predictive methods and completing repairs in advance of the potential failures businesses like Andromeda Systems Inc. and yours can save themselves millions of dollars per year in revenue in the areas of:

Equipment Downtime

Reactive Maintenance

Technician Services

Production Quotas

Equipment Replacement

 

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