The importance of failure prediction in the energy industry
Electricity and gas management is a major issue at local, national and even international levels. Various issues exist throughout the value chain, from production equipment management to the constant supervision of distribution systems, including the maintenance of storage facilities.
While a constant rate of availability must be ensured for all service users, it is also necessary to ensure their safety and the safety of the operators working in the field.
The diversity and criticality of equipment, the variety of data types, combined with the lack of historical failure data, make it very difficult to design cost-effective predictive modeling solutions.
Predictive maintenance in the nuclear industry
The nuclear industry is at the beginning of the chain and enjoys an economically privileged status. French nuclear power is imported and exported and represents a significant industrial asset.
To make such a powerful industry work, it must be equipped with effective tools that meet its demanding safety and reliability needs, like our DiagFit Software.
Predictive maintenance, because it increases the reliability and availability of assets, is proving its relevance in the nuclear sector.
To increase its presence in this key sector, Amiral Technologies has chosen to join the Nuclear Valley cluster
Use cases
Predictive maintenance in the nuclear industry
The nuclear industry is at the beginning of the chain and enjoys an economically privileged status. French nuclear power is imported and exported and represents a significant industrial asset.
To make such a powerful industry work, it must be equipped with effective tools that meet its demanding safety and reliability needs, like our DiagFit Software.
Predictive maintenance, because it increases the reliability and availability of assets, is proving its relevance in the nuclear sector.
To increase its presence in this key sector, Amiral Technologies has chosen to join the Nuclear Valley cluster
Use cases
Predictive maintenance for energy distribution and production equipment
Production and distribution equipment, whether for oil, gas or electricity, requires reinforced maintenance. As the severity of these installations is extremely high, specific accreditations are often required in order to intervene. Particular attention is paid to the safety of operators working on this equipment.
Moreover, on industrial sites, this equipment is responsible for the continuous and constant distribution of energy, and its malfunctioning can jeopardize the whole activity. It is therefore important to be able to validate, qualify and even anticipate possible failures that may occur.
Thanks to our DiagFit software, predictive maintenance once again proves to be particularly relevant in terms of reliability, anticipation and upstream risk prevention.
Use cases
Predictive maintenance for energy distribution and production equipment
Production and distribution equipment, whether for oil, gas or electricity, requires reinforced maintenance. As the severity of these installations is extremely high, specific accreditations are often required in order to intervene. Particular attention is paid to the safety of operators working on this equipment.
Moreover, on industrial sites, this equipment is responsible for the continuous and constant distribution of energy, and its malfunctioning can jeopardize the whole activity. It is therefore important to be able to validate, qualify and even anticipate possible failures that may occur.
Thanks to our DiagFit software, predictive maintenance once again proves to be particularly relevant in terms of reliability, anticipation and upstream risk prevention.
Use cases
Predictive maintenance for renewable energies
The development of new production technologies around renewable energies (solar, wind, bioenergy) makes it a sector where lack of knowledge of the equipment is commonplace.
The anteriority of failures is low or even non-existent, which makes maintenance much more complex.
In that context, DiagFit‘s unsupervised and incremental approach makes sense and allows the deployment of a preventive maintenance as soon as the equipment is implemented.
Use cases
Predictive maintenance for renewable energies
The development of new production technologies around renewable energies (solar, wind, bioenergy) makes it a sector where lack of knowledge of the equipment is commonplace.
The anteriority of failures is low or even non-existent, which makes maintenance much more complex.
In that context, DiagFit‘s unsupervised and incremental approach makes sense and allows the deployment of a preventive maintenance as soon as the equipment is implemented.
