Energy

Accelerating the energy transition with artificial intelligence

From businesses of all sizes to individual citizens, the energy transition concerns everyone. 
At Probayes, we help our customers make their buildings and processes more energy efficient.
 
We also develop artificial intelligence to predict the production of renewable energy and optimize its use.

Probayes uses a number of tools to address energy-related challenges:

Algorithms tailored to the energy industry

Probayes develops, tests, and implements a wide range of algorithmic tools on energy-related use cases in many industries. Our core approaches to energy-related projects include:

 

Operational research and combinatorial optimization

  • Transportation network optimization (logistics and distribution, public transportation, delivery routes, etc.) to shorten the distances covered
  • Right-sizing inventory and optimizing how inventory is organized in space to reduce the amount of space required and the associated costs
  • Geometrical optimization to locate waste so as to reduce the number of vehicles required to remove it
  • Self-consumption optimization

 

Time-series processing

  • Detecting IoT data anomalies to optimize the quantity and quality of input data
  • Predictive maintenance solutions to reduce costs and extend equipment lifespans

 

Time-series processing and prediction 

  • Predicting solar panel production

 

La Operational research combined with time-series processing and prediction

  • Building energy management and optimization 

 

Computer vision applied to thermography

  • Leak detection on heat networks
  • Scanning building facades to detect heat loss

 

Better results, together

We work hand in hand with your business experts

Regardless of your industry, energy-related projects are usually particularly complex, with a large number of data sources. At Probayes, we work hand in hand with our customers’ experts to understand the many moving parts of the challenge at hand so that we can develop the best possible solution. We make communication a priority to ensure that we learn from each other throughout the project. Our customers come away with a better understanding of AI implementation in energy-related scenarios, and our people acquire a deep understanding of the issues our customers face. Each project strengthens our long-lasting customer relationships.

Success stories:

Renewable energy production forecasting

Project to predict solar panel energy production

Batisense

Energy optimization solution for buildings

Making hybrid vehicle engines more efficient

Project to optimize the energy consumption of a hybrid engine

Autoconsommation

Self-consumption optimization

Project allowing …

EasymAInt predictive maintenance solution

With EasymAInt, makes predictive maintenance simple. Just install plug-and-play sensors to monitor your data and equipment and you are ready to go!

Optimnet

Optimnet is custom decision-assistance tool that adapts to your unique logistics system optimization needs.

Production quality project

Success story

Project to improve medical device manufacturing

Challenge

Entire batches of medical devices can be quarantined or scrapped during manufacturing for non-quality reasons. For manufacturers, understanding why certain specifications essential to product quality are not being met is critical. 

The project

We carried out an initial phase of descriptive data analysis using quality assurance data, obtained primarily from our customer’s in-house software. The data spanned several years and included several product lines.

We then trained artificial intelligence algorithmic models to gain a better understanding of the most important factors affecting final product specifications and how these factors contribute to overall product quality. Our customer’s statistical analysis teams worked with us to guide our approach and enable a deeper understanding of the differences between a “traditional” approach and an AI-based approach.

Results

The results obtained highlighted differences in the analyses of how much different factors affecting the final product specifications contributed to product quality. Our customer was able to improve the quality of products coming off the production line and reduce the number of defective batches.

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Last name First name

Position – Company

Eramet

Success story

Eramet is one of the world’s leading metal alloy producers. The Eramet plant in Knivesdal, Norway, produces silicomanganese alloys.

Challenge

When manufacturing processes are optimized, premium raw materials can be replaced with less-expensive alternatives without affecting product quality. Eramet turned to Probayes for a real-time solution capable of detecting exactly when to switch out the more expensive raw material for the cheaper one and of generating recommendations for when to switch back in the event of drift.

The project

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Results

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First name Last name

Position – Company

Framatome

Success story

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Challenge

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The project

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Results

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“Lorem ipsum dolor sit amet, consectetur adipiscing elit. Fusce eu lacus diam. Cras congue, neque ac mattis efficitur, nibh ipsum fringilla nunc, sed iaculis neque odio non orci. Vestibulum ante ipsum primis in faucibus orci luctus et ultrices posuere cubilia Curae; Praesent lacinia, urna quis rhoncus lobortis, urna neque tempus tellus, quis auctor justo lectus vitae libero. Nulla non porta odio. Donec diam est, varius id ullamcorper a, efficitur nec libero”

First name Last name

Position – Company

Our customers*

*We take confidentiality seriously. Some of our customers’ names and other identifying information have been removed.