Our Customer: Repsol
Repsol is a global multi-energy company that has set a target of achieving zero net emissions by 2050. With over 24,000 employees, Repsol operates across the entire energy value chain and serves nearly 24 million customers in almost 100 countries.
As one of Europe's most efficient refining systems, Repsol produces an average of 650,000 barrels of oil equivalent per day. Repsol is committed to transforming its seven industrial complexes located in Spain, Portugal, and Peru into multi-energy hubs. By implementing innovative projects, Repsol aims to reduce its carbon footprint and become a leader in producing renewable hydrogen and sustainable fuels by 2030.
The Goal: Achieving Zero Net Emissions by 2050
Repsol aims to achieve zero net emissions by 2050 through an integrated model of decarbonization technologies that includes enhanced efficiency, increased renewable power generation capacity, production of low-carbon fuels, circular economy, and breakthrough projects to reduce the industry's carbon footprint.
The Challenge: Solving Complex Formulation Challenges
To develop more sustainable lubricants and fuels, Repsol's scientists rely on massive libraries of raw ingredients. They need to combine them with new, low-carbon components obtained from different types of waste. To explore the wide range of possible ingredient combinations and solutions, Repsol Technology Lab chose Uncountable's platform to improve the efficiency of its formulation optimization process.
Before Uncountable’s platform, Repsol Technology Lab was using different software solutions to handle the more than 1200 formulations and results created per year, including Excel, custom-made outdated software, and commercial solutions which remain unable to communicate amongst each other.
The Solution: A Customizable Platform for Enhancing Efficiency & Productivity
Uncountable's platform allowed Repsol to create a custom database that combines experimental data with other repositories of technical information. By utilizing machine learning tools and sequential learning routines, Repsol was able to reduce its experimental workload and accelerate its R&D cycle. The platform also improved communication among researchers and technicians in labs and sites.
Key Features & Benefits: R&D with Machine Learning & Data Management
- Create, clean, & consolidate formulation database with 10k+ of data from the last 20 years.
- Implement machine learning tools and sequential learning routines in daily workflows.
- Improve communication among researchers and technicians in different labs and sites.
- Reduce new product development costs and accelerate the R&D cycle.
The Outcome: Optimizing Formulations & Reducing Costs
Uncountable's platform allowed Repsol to optimize its formulations by suggesting only those with a higher chance of fulfilling the product specifications required. The platform also decreased the experimental workload and helped Repsol to unleash the value of its historical data. By utilizing the platform's native predictive tools, Repsol was able to accelerate its R&D cycle and reduce its new product development costs.
Overall, Repsol's journey towards sustainable fuel formulations with Uncountable highlights the benefits of utilizing data management systems in R&D workflows. Download the full case study to learn how Uncountable's platform helped Repsol achieve its sustainability goals.
Read The Full Case Study to Learn More
Additional insights in the full case study:
- Learn about Repsol’s technology challenges
- How Repsol worked with Uncountable to customize a Material Informatics solution
- Quantitative performance metrics proving Repsol’s savings
- New skills Repsol’s R&D team developed after implementing Uncountable
- Where and how Repsol plans to expand its partnership with Uncountable
- How Repsol implemented Machine Learning & sequential routines in daily workflows
- How Repsol leveraged historical data to fuel predictive insights & optimize formulations
- And much more!
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