Industrial Machine Learning: Failure Prediction and Energy Optimization
6 novembre 2025
Project Context
A Lyon-based company specializing in energy performance management through cooling sought to strengthen its competitive advantage.
Its dual objective was to:
- Reduce maintenance costs caused by unexpected machine failures
- Optimize energy consumption in its buildings while aiming for ISO certification to access subsidies
Objectives
The main goal was to develop a Machine Learning-based solution to:
- Anticipate and prevent critical equipment failures
- Reduce operational costs and extend equipment lifespan
- Optimize building energy consumption (based on occupancy, weather, and manual settings)
Mission Duration
A multi-month engagement including solution design, algorithm development, and knowledge transfer to internal teams.
Implementation
Agaetis implemented a Data & AI approach focused on business value:
- Diagnosis and scoping: Clarification of opportunities through the use of existing industrial data
- Predictive algorithm development: Design of advanced models to anticipate failures and detect anomalies
- Energy optimization: Creation of tools leveraging occupancy, weather, and manual control data to reduce energy consumption
- Knowledge transfer: Training and support for internal teams to ensure ownership and sustainability of AI models
Results Achieved
- Reduced unexpected failures: 20% decrease in critical incidents
- Energy optimization: Significant reduction in energy costs through smarter resource management
- Extended equipment lifespan: Improved preventive maintenance and machine responsiveness
- Increased Data/AI maturity: Predictive algorithms integrated into operational processes
Key Success Factors
- Agaetis’ expertise in Machine Learning applied to industry
- Combination of data science with the client’s business knowledge
- Implementation of training and skill transfer programs
- Pragmatic and results-oriented approach
And You?
Are you wondering about:
- Using Machine Learning to reduce maintenance costs?
- Optimizing your energy consumption?
- Implementing anomaly detection solutions tailored to your industrial environment?
👉 Contact our experts to turn your data into levers for industrial and energy performance.
Ressources Agaetis
Introduction En tant qu’architecte technique d’une application mobile et web pour un client, avec l’équipe de développement, nous avons dû nous préparer à recevoir une forte affluence sur un temps très court sur l’application et le site web. Cette application permet aux conducteurs routiers de trouver des points d'intérêt sur une carte. Ils peuvent notamment rechercher des restaurants routiers, des parkings, des stations-service et bien d’autres endroits répondant à leurs besoins, comme la présence de douches ou de machines à laver. L’application intègre également un GPS Poids-Lourd en option. Le samedi et le dimanche sont habituellement des journées calmes pour les serveurs de notre application. Les utilisateurs consultent principalement l’application en fin d’après-midi la semaine afin de préparer leurs arrêts. Nous observons donc généralement une montée progressive du trafic tout au long de la journée avec un pic entre 17h et 18h.
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