FreshForecast is a big-data platform that calculates dynamic quality and shelf-life information by combining production, supply-chain and quality-inspection events. It turns scattered data from across the chain into a single, continuously updated view of how fresh each product really is.

How it works

• For the smallest identifiable unit (typically a pallet or single product unit), the complete product history is assembled — production details, storage and transport conditions from production to point of sale, and the associated quality-inspection events — using data from ERP, supply-chain monitoring and QA documentation systems.
• Using calibrated digital twins, the effective age and remaining shelf life are calculated and updated periodically.

Outcome

Connected quality and shelf-life information across the supply chain. Continuously updated remaining shelf life per unit, enabling first-expired-first-out logistics and fewer write-offs.

Field of application

• Supply chain transparency
• Quality supportet category management
• Date driven supplier ratings

 Validated:

• Validated for the shelf life of tomatoes with Migros Turkey.
• Validated for the shelf life and ripeness of mangoes with REWE Germany.
• Validated for the shelf life of table grapes in the FreshTwin research project.

Related Links

• Case Study: Dynamic Shelf-Life
• [Physics-Based Modelling & Digital Twins](/expertise/physics-based-modelling/) ·
• Robust Decisions from Limited Data](/expertise/robust-decisions/)
• See what FreshForecast would predict for your products. [Contact us](/contact-us/)