Innovation and Precision: The New Features of Jul-ia for Fat Blends
At Alianza Team, we are committed to leading innovation in the fats and oils industry. As part of Oleum, our platform of artificial intelligence tools designed to optimize processes and enhance production, Jul-ia stands out as a revolutionary solution.
Jul-ia is our advanced platform for designing and analyzing fat blends, including margarines and shortenings. Within Oleum, Jul-ia combines artificial intelligence, cutting-edge algorithms, and updated data to deliver tailored and efficient solutions that meet the unique demands of the food industry.
Key Updates in Jul-ia
- Blend Optimization with Genetic Algorithm (GA): We have achieved a significant breakthrough in the speed and accuracy of blend design. With a 40% reduction in runtime, Jul-ia now provides more detailed evaluations to meet your specific product development needs.
- New Evaluation Factors for Optimized Blends: Analyze your blends from a more comprehensive perspective. We’ve introduced:
- Cost: for better financial planning.
- CO₂ emission factors: for more sustainable decisions.
- SAFA, MUFA, and PUFA calculations: to ensure an optimal lipid profile balance.
- Retraining with New Data: Jul-ia has been retrained using updated operational data. This process included new blend combinations and the integration of novel raw materials, ensuring the platform remains aligned with the latest market trends.
- Integration of FAMES: We’ve added fatty acid methyl esters (FAMES) to Jul-ia’s dataset, expanding its scope and enhancing analytical precision. This update represents a significant advancement in the platform’s ability to address complex needs.
At Alianza Team, we work to provide you with customized solutions that drive your projects and strengthen your market position. With Jul-ia, our innovations are designed to exceed your expectations and help you achieve your goals. We invite you to explore these improvements and all our advanced tools that are redefining the fats and oils industry.