Predictive maintenance and mobile technologies

What is predictive maintenance?

Predictive maintenance is a technique that, thanks to data analysis, makes it possible to detect errors in the operation of a machine or process. This makes it possible to anticipate failures and prevent them from occurring or to solve them as soon as possible so that the consequences are as minimal as possible.

This is just one example of how the collection of data and information has been a turning point in the business world. In addition to being able to view historical data and analyse trends, it is also possible to observe the information in real-time. This way you can see if a process is being carried out correctly.

Successful predictive maintenance of business assets and processes requires a number of elements and tools. Some of which we highlight:

• Connected devices: Those machines that you want to track and collect data from need to have a connected device. This is what allows you to know their performance. Thanks to the IoT, machines, and devices can be connected to help in the analysis of data in real-time.
• Software solutions: through the use of machine learning technologies, together with the development of software solutions and the evolution of mobile devices, tailor-made solutions are created that allow large amounts of data to be collected and analysed to make decisions, observe trends and make predictions.

Benefits of predictive maintenance

As we have been saying throughout this post, implementing software solutions that enable predictive maintenance can help to predict the wear of machinery, signs of rust, sudden changes in a process, blockages or leaks, etc.

For all these reasons and for its benefits, implementing software solutions for predictive maintenance is an increasingly common practice in many companies. Among the advantages that we can find we can highlight:

• Lower investment in asset maintenance: By incorporating technologies capable of analysing machinery and predicting errors, the cost of maintenance is lower.
• Optimisation of resources: Carrying out predictive maintenance of business assets allows resources to be optimised. In addition, they also improve the planning of situations by being able to foresee or anticipate possible failures.
• Risk and cost reduction: Predictive maintenance saves costs by minimising errors and machine downtime. In addition, it reduces decision-making time as constant analysis provides a history and trends that allow you to anticipate and plan for different possible situations.
• Improved asset performance: Thanks to predictive maintenance and the technologies used for it, the useful life of the assets is improved, as well as their performance by giving them a better use.

ABAMobile, 10 years transforming businesses

As you can see, the importance of data and data analytics today can influence business planning and asset performance. Through predictive maintenance and real-time data analysis, asset failures can be anticipated and increasingly better decisions can be made based on this information.