Before you decide whether you should use predictive maintenance for your business or not, you first need to know what it is. Only then will you be able to determine what’s best for you and your business. So, let’s begin with the basic understanding and definition of predictive maintenance.

Predictive Maintenance:

Predictive maintenance, as the name suggests, is a technique that allows you to predict the failure of a machine or equipment before it occurs. In other words, it predicts the future of whether the failure is going to happen or not. The main aim of this technique is to prevent the risks that are associated with the failure of assets. Moreover, it allows you to replace a device or any component before it fails and helps you in tracking the performance of the asset.

Thus, the downtime of any machine, equipment, or component can be minimized, and its lifecycle can be maximized through the use of predictive maintenance.

How does it work?

Predictive maintenance works based on condition-monitoring of equipment that allows you to evaluate the performance of any asset in real-time. The main element that functions in this process utilises sensor technology also referred to as IoT. IoT is applicable for various systems and assets and allows them to connect, work together, and share and analyze the data. You can read more about IoT here.
Some examples where predictive maintenance is used include oil analysis, vibration analysis, pressure sdrop analysis, temperature flow and returns rates, acoustic analysis, and thermal imaging to name but a few.
Why should you use predictive maintenance for your business?
There are many reasons why predictive maintenance is right for your business and how it can benefit you. Firstly, the implementation of predictive maintenance will allow you to carry out maintenance when it is required, rather than at a predetermined frequency.

Thus, achieving cost savings by:

  • Reducing equipment maintenance time.
  • Reducing the cost of fixing the equipment in case of failure.
  • Reducing the cost of maintenance supplies as well as spare parts.
  • Reducing the unplanned downtime of equipment.

As compared to time-based preventive maintenance, this advanced technology ensures that any machine or equipment that requires maintenance will automatically issue a work order to proactively request a service on the asset before it goes outside its normal operating envelope. Thus, it minimizes any potential downtime as well as reducing the total cost of maintaining the asset.
Additionally, the sensors that are used in predictive maintenance are very robust, are easy to install and do not require frequent intervention or calibration.


The improvement in sensor technology, coupled with innovative software platforms, such as Azolla, has made the decision for forward-thinking organisations to move from time-based maintenance to predictive maintenance easy. The cost savings of implementing predictive maintenance are achieved through the prevention of equipment failures, the improved energy efficiency of equipment due to operating equipment within its design envelope and maintaining equipment when required rather than at a frequency that drives up the cost of maintenance.

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