Predictive Maintenance Software: Selection Criteria, Implementation Method and User Feedback
Implementing a predictive maintenance strategy isn’t about adding a few sensors and hoping for “magic” alerts. It’s about gradually structuring a chain of analysis, decision-making and system integration that transforms raw data into relevant, actionable interventions. Condition monitoring standards provide a clear framework: characterising the asset, selecting the relevant physical measurements, organising data collection, and […]
Predictive Maintenance: two terms, one reality
For a long time, French-language literature has maintained an ambiguity between preventive maintenance and predictive maintenance. In reality, according to the AFIM consensus and standard NF EN 13306, these two terms refer to exactly the same approach: “Conditional maintenance performed following a prediction obtained through repeated analysis or known characteristics and an assessment of the […]
The strategies of industrial maintenance: understanding, choosing, and preparing the transition to data-driven predictive maintenance.
In industry, people often talk about “types of maintenance” as if one had to choose a single approach. In reality, it’s a continuum of complementary strategies that are combined according to equipment criticality, operational constraints, and the organization’s data maturity. The goal isn’t to follow a doctrine, but to achieve operational optimization: fewer unplanned downtimes, […]
The 3 challenges facing maintenance teams
The 3 challenges facing maintenance teams In recent years, the industrial sector has undergone profound change, driven by the advent of new technologies. In this context, maintenance teams play a central role and must meet challenges that go beyond simply ensuring that equipment runs smoothly. Industry players who want to be part of what is […]
Anomaly detection in industry: towards greater productivity and safety
Security, productivity, and guaranteed availability thanks to anomaly detection At the forefront of Industry 4.0, anomaly detection addresses the increasingly demanding security and productivity challenges facing today’s businesses. By using artificial intelligence to predict equipment failures and enable repairs before damage occurs, anomaly detection helps ensure the operational continuity of production facilities and reduce the […]
Data security in Industry 4.0
Data Security at the Heart of Industry 4.0 Challenges In the era of Industry 4.0 and the Internet of Things (IoT), as our production systems become increasingly digitalized, data security has taken on unprecedented importance. This future-oriented industry, where physical equipment, control systems, and information networks are interconnected, aspires to achieve operational excellence. From energy […]
Industrial data is gaining trust
Amiral Technologies is joining Bleu’s Départ ISV program to deploy our DiagFit software on Bleu’s Azure cloud. This trusted cloud, currently undergoing SecNumCloud 3.2 certification by ANSSI, will guarantee immunity from extraterritorial laws and maximum data protection. Founded and wholly owned by two French shareholders, Capgemini and Orange, Bleu is a new French cloud services […]
Performance-enhancing connected sensors
How can you get the most out of the sensor data on your industrial equipment? Central elements of Industry 4.0 and emblems of the IIoT (Industrial Internet of Things) connected sensors are at the heart of a revolution that has only just begun. By enabling maintenance technicians to obtain invaluable information on the operation of […]
Thales integrates Amiral Technologies’ DiagFit solution into its infrastructure
After several years of successful collaboration, the Thales group is integrating Amiral Technologies’s software, DiagFit, into its infrastructure to enable rapid failure diagnosis on equipment operating in critical environments.
AI at the service of domain experts :
In industry, digital transformation is increasingly based on the use of data from production equipment and processes. Artificial Intelligence (AI) and Machine Learning (ML) bring new solutions, as they enable us to optimize the performances of industrial equipment, anticipate malfunctions and improve product quality. However, it’s not always easy to adopt these technologies and bring […]
