During the last three decades the development of Data collection and IT based monitoring solutions was essentially to implement the use of Artificial Intelligence (AI) as an attempt to replace human supervision with machine intelligence.

The definition of machine intelligence was the monitoring of assets by computers, either using criteria based on pre-defined scenarios from the equipment manufacturers or based on the operational team experience.

This era has seen the creation of big data centres collecting data from multiple sources into advance data servers, now opening the opportunity of acquiring, storing and sharing online, a big quantity of data from multiple sources.

By developing data analysis platforms able to clean up and process these data in order to acquires experience based on collected data was now opening the possibility to the development of:

  • Automation: allowing the triggering of pre-defined actions without human action and based on predefined indicators, in order to automate a process, increase the safety and to reduce the operational cost.
  • Machine Learning: considered as a subset of artificial intelligence and allowing the modelling of new scenarios, based on experience by using advance algorithms and statistical models to enrich the existing data base.
  • Predictive Maintenance: allowing the optimization and redefinition of the maintenance tasks based on advance algorithms or patterns on pictures, allowing to reduce the maintenance cost or to increase the safety by monitoring the vibrations of bearings for example.

Another key benefit of such cloud based big data platforms are the possibility to now design and visualise in real time equipment status or to go thru an historic of data from any connected tablet or remote computer.

Now giving to the operational excellence and maintenance teams, the possibility to manage multiple sites, to focus on the review of new modelized scenarios and to communication with manufacturers about the validation of these new optimized scenarios, meanwhile the AI will automate the low value asset monitoring process and will trigger basic actions, allowing operation in degraded status by the time the services technicians will intervene.

Another benefit is the possibility to compare assets performance between manufacturers and sites and to undertake upgrades based the technical solutions performance.

The technical services performance can be included in services-based contracts, including KPIs on collected data, now allowing the purchase of kilowatts per hour, instead of the purchase of power-generators for example, with the signature of a service agreement aside.

Our team is having about 25 years of experience in the negotiation of services-based agreement for the provision of maintenance by services companies world-wide.