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“Proactive maintenance will improve machine reliability and up-time”

An interview with Florent Barbier from PREDICT. For more than 17 years, this company based in France has specialized in digital solutions regarding Condition Based Monitoring (CBM), Prognosis & Health Management (PHM) and Fault Tolerant Control (FTC).

How did you know about the project? What aspects of the project attracted you to join it?

Through its CASlP and KASEM software solutions, PREDICT implements analysis techniques offering Anticipation and Optimization capabilities, such as continous analysis of massive data, predictive analysis, semantic analysis, systemic analysis, functional analysis and dysfunctional analysis.

predictAn example of proactive maintenance solutions currently developed by PREDICT.

These analytical techniques are real answers to the affluence and treatment of massive, heterogeneous and diachronic data. They are a part of the Big Data technologies. These solutions are deployed in the service of industrial installations like machine tools, forklifts, ships. For our customers the benefits are clear:

  • Elimination of breakdowns from 70% to 75%
  • Reduction in maintenance costs from 25% to 30%
  • Increase in production from 20% to 25%
  • Return of investment from 3 to 6 months
  • Reduction of downtime from 35% to 45%

When we learned about Twin-Control, we realised that the strategic vision of PREDICT to develop new digital products and services for Factories of the Future is in direct link with the project’s objective, both aiming to increase the competitiveness of European manufacturing industry and strengthen its leader position in sectors like aerospace and automotive.

Which results do you expect from the Twin-Control project?

Thanks to Twin-Control, a fleet-wide management platform with CBM technologies will be achieved as a major result for PREDICT to address the new market of machine-tool manufacturers, and complete the services coming from machine-tool monitoring systems. The results of previous projects, such as Power-OM and T-REX, will be used as inputs for Twin-Control, for example in the application to facilitate predictive maintenance of machine tool from test sessions data.

The results of T-REX project are explained in detail in this video:

In conclusion, the benefits and advantages of the Twin-Control platform will be the following:

  • Application to all machine tools,
  • Calculation of new health indices and aggregation with actual conditions,
  • Facilitate understanding of machine tools fleet health for different user profiles: maintenance, production, quality, after-sales, etc.

In summary, with proactive maintenance methodologies implemented, this digital platform will improve machine reliability and increase machine up-time between 2 and 4.5%.

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