Blog Industry 4.0

Elliot RoT® selected for WindEurope 2022

We have been able to present our Elliot RoT solution at the Wind European annual event of global impact addressing onshore and offshore wind energy issues, with more than 350 exhibitors from around the world. The event takes place from 5-7 April 2022, in Bilbao, the heart of the global wind industry. It brings together all the world leaders providing the energy of the future. 

Two of Elliot RoT's solutions have been selected to be presented at the Wind Europe Congress.

A novel technology has been developed for the early detection of failures in industrial equipment through the use of Artificial Intelligence (AI) techniques under the name of Reliability of Things® (in API and Edge Computing format). By invoking the API, the degradation level of any equipment being monitored on the IoT platform is assessed.

This universal algorithm models the normal behaviour of the equipment (motors, pumps, electrical consumption, etc.) and subsequently calculates the degradation of any component, detecting faults well in advance, also allowing the identification of the root cause and the evaluation of maintenance actions.

The system generates individual alarms for each monitored component, but the objective of the platform is more ambitious, as it generates a global knowledge database for obtaining equipment reliability indicators.

When new equipment is connected to the platform, the type of equipment in question is identified (motor, pump, generator, etc.), the manufacturer, the model, whether it is new, repaired or has been in operation for some time (in order to censor or not the statistical data) before being connected to the platform, and a series of other parameters that serve to carry out a correct characterisation of the population.

Elliot RoT, the Elliot & Reliability of Things® Universal Platform for Predictive Maintenance & Equipment Reliability Characterisation

The IoT platform of Elliot Cloud is the perfect architecture to combine the Reliability of Things® solutions.This is because it allows the integration of PLCs, Edge Computing systems and IoT sensors with Cloud environments, which makes it possible to exploit all the reliability and artificial intelligence techniques for the detection of malfunctions in any industrial equipment.

The platform combines the latest Condition Based Maintenance (CBM) techniques with more classical Reliability Based Maintenance (RCM) techniques. For this purpose, different types of data are used in combination:

  1. Operational data.
  2. Alarms.
  3. Work orders.
  4. The asset history.
Elliot ROT
Elliot ROT

When a user registers an asset on the platform, they have a series of asset registration menus where they can register the manufacturer of the asset, the model and the type of asset among other fields. There is also the option to register a series of assets in bulk.

When an asset is registered on the platform, all its operating variables are immediately recorded. If the user subscribes to the RoT service, he has the option of monitoring the condition of each of its components, for which the platform provides two indicators at any given moment:

  1. Malfunction indicatorwhich analyses whether the equipment behaves in accordance with its previous behaviour in a fault-free period.
  2. Probability of failure indicatorwhich estimates the probability of equipment failure based on the failure history of similar equipment. This probability is calculated:
    • From customer equipment failure histories.
    • From historical data of similar equipment recorded in a global and anonymous database of all customers on the platform.
Blog Industry 4.0

Agile methodologies and IoT (Internet of Things)

Being agile in decision making and in the implementation of changes is essential for a company to be a leader in its sector, and this is where agile methodologies take on great importance. Decisions must be oriented towards continuous improvement, both in terms of cost reduction or increased efficiency, as well as innovation and the creation of new products to meet new market demand.

The agile methodologies take on a new meaning and dimension when the foundations of IoT are applied. The paradigm of continuous improvement is currently being imposed, the essence of which is that if you want to improve a magnitude of a parameter you must first measure it, i.e. you cannot improve what you cannot measure.

The Industry 4.0 is a hyper-connected and sensorised industry where decisions can be made quickly. There are many questions that can arise: 

  • What happens when you have a lot of variables, measurements or history of these measurements?
  • How can we find patterns, deviations, correlations between these parameters?
  • How to measure quantities of different nature, with different protocols, on different machinery and in different locations?
  • How to visualise, interpret and analyse business variables with mechanical or social variables?
  • How do you make important decisions quickly based on what is happening in your production?
  • What if you also want to know what is happening in the market to make that decision?

Nowadays, it is necessary to have mechanisms to help in this process of measurement and correlation. New technologies allow the replication and deployment of cost-effective sensors on a massive scale and the collection of information from different machines, tools and systems.

Today, we have the capacity and the technology to measure a wide range of variables and parameters.

Not only is it possible to measure these quantities, but we can also collect them digitally, process them automatically, translate them into a common language and transmit them securely.

Elliot Cloud acts as the brain of the system, as an umbrella that collects this data, and is able to correlate and determine the degree of ascendancy that some parameters have over others, as well as storing and displaying the historical data in an agile way and analysing them by means of innovative techniques of Big Dataanalytical, machine learning and artificial intelligence.

Thanks to these techniques, it will be possible to detect characteristics such as the seasonality of occurrences and events, and it will also be possible to define alerts that will trigger orders to activate mechanisms and protocols for action, among others.

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