How To Start A Successful Predictive Maintenance Program

Most people think that a predictive maintenance program is expensive, complicated and unnecessary. Whereas everybody’s reason may be valid, most organizations are implementing this vital program. If you are considering this approach, the following steps will be useful in ensuring a successful maintenance program.

Identification stage

It is important to note that not all machines require a predictive maintenance program. You need a listing of those assets that in case of breakdown or malfunction will have a significant negative impact on your business. Some assets can run with routine maintenance and at lower cost until they are due for replacement. You can choose those machines which break down more often and those whose maintenance cost is high. Also on your list, you can include those machines whose malfunction can affect other functions in the organization.

Data collection stage

Predictive Maintenance Program

Young engineer in the plant.

You will need to gather all data and information about your machines before setting up a predictive maintenance program. This information is useful in making valuable decisions on how and when the machine requires maintenance. You can collect data from the manufactures user manuals and instructions manual that comes along with every purchase. Your maintenance team can also give historical technical, wear and tear information on each of the assets. All this information put together will help in creating a future action plan for each machine.

Performance assessment stage

You will need to analyses probable failures of the machines in your register. The objective here is to get information on the frequency of different failures, their impact on business processes, and whether the failures were easily identifiable. You can measure and rank each failure alongside the risk it poses on your business and the ease of detecting it. The product of this analysis is a priority list that will guide you and your team in building a failure prediction program with a priority on high risk to low-risk assets.

Monitoring and prediction stage

For the program to be a success, there is a need for real-time data collection that will assist you in monitoring the condition of the machine. There is always an assumption that machines will wear, fail partially or even completely. You can install sensors to measure temperatures, leakages, speed, vibrations, acoustics, current and voltage.

You can have a system in place that uses algorithms to identify and forecast the time remaining for a fault or failure to occur. The outcome is an automated system that generates alerts and informs you that a particular machine is deviating from its average performance. It then allows you to take action to rectify this abnormally.

Pilot stage

With your predictive maintenance program in place, the final step is to test on a few selected machines. Its success can then be rolled over other machines. If you are using dozens of machines, you may require to scale up data collection, storage and analysis in platforms such as the cloud.

A predictive maintenance program is a must-have for any business since it ensures maximum utility of deployed. It may cost you more in the implementation stage; however, the costs of not having one are much higher. If you are looking to having a predictive maintenance program, BRAVO has qualified personnel to get you started.