Predictive Maintenance

One of the keys to maximize the performance of a platform is predictive maintenance. In this article we will see why it is important and how IDbox helps to overcome the barriers in order to implement it in your business.

In any industry (IT, naval, automotive, energy …) we will always have a number of personnel and infrastructure, a platform of any type that will always have a life cycle associated (with usual phases): Development / Production, Production , Operation and Maintenance and Disposal.

Being the Operation and Maintenance phase the one that interests to extend and whose stop will always have associated losses, we always seek to extend this phase as much as possible, reducing as much as possible the downtimes between phase and phase of operation and maintenance for any element and / or complete system.

In order to reach that goal, one of the most important tasks in any system is its maintenance. Be aware of your past, current and, as far as possible, future state. The better our maintenance is, the more we can (with certain limits) lengthen that phase of operation and production of our system and, therefore, reduce costs due to stops.

The search for means and new technologies that reduce the cost of the maintenance phases in order to reduce the total cost of a system, without implying the non-availability or loss of benefits is fundamental and of great interest for any company. Therefore, we could mark for any maintenance organization a set of basic objectives:

• Try to decrease maintenance tasks.
• Always seek to increase availability.
• Improve security.
• Reduce the associated maintenance costs.

Traditionally, maintenance has been carried out in a reactive way (when we detect a failure, this is tried to be solved as quickly as possible and sometimes by using redundancy systems to avoid downtime during maintenance) or periodically, that is, following a predefined plan, probably pre-established by the manufacturer of the system / platform, who seeks to guarantee maximum and minimum performance measures. As well as a good use guide that maximizes the life of the same.

Perhaps the easiest example to understand would be the one of a car, since we know that it has a number of pieces that we must change every certain time and at the same time, if we have a breakdown, correct it. For this, we could describe the evolution of maintenance in the following way:

Predictive maintenance: getting ahead of the problems

We define therefore predictive maintenance as the set of techniques that allow reducing costs to ensure availability and performance. It is a set of instrumented techniques for measuring and analyzing variables to predict the future point of breakage or failure of a component or system in such a way that said component can be used just before it fails.

These techniques require indicators or parameters to predict the life of the component to be analyzed within the platform, as well as the possibility that these will be monitored and measured during their lifetime.

This theoretically allows the repair, supply and labor time to be scheduled well in advance and has important implications:

• Reduces the possibility of downtimes.
• Extends the intervals between downtimes.
• It allows optimizing the service life of the components.

However, it also entails a number of drawbacks: it requires continuous and rigorous monitoring of all the elements that, in a large number of situations, is not viable or presents great difficulty.

Traditionally, to carry this out, a routine data collection with a portable equipment was used, which had to be moved to the place where it was necessary. Thanks to advances in information technologies, this situation is in the process of change.

Currently, the presence of sensors and measuring instruments already integrated in the equipment is something more and more common and therefore the challenge lies in the collection of the data, as well as its integration and subsequent analysis, that is, to be able to perform this continuous monitoring and know how to interpret that data. Most critical equipment can have installed a monitoring system with multiple indicators. These systems are generally networked to provide analysis and alarm data to operators, etc.

IDbox, facilitating the integration

The traditional maintenance program has evolved towards a more modern approach , fueled by increasingly complex and growing software. Therefore, having a software-hardware platform for data acquisition is essential.

This is where the IDbox product comes in; One of the biggest challenges is the great diversity of manufacturers and types of data sources that require the aforementioned surveillance and, therefore, be able to collect all that information, in a standardized way in a single place, where being able to analyze it is very useful.

IDbox is able to connect to multiple sources of information independently and under specific conditions for each source and release that information to a system in its entirety. Through a number of patterns analysis and historical query tools we can know the state of our platform in time, past, present in real time, future and carry out an appropriate and intelligent decision making.

Once we have all the information at our disposal, we can define the conditions that we consider relevant in order to start performing a predictive maintenance, thus benefiting us from all its advantages and fed by an advanced monitoring software.