System und Verfahren zum Entwerfen einer Verpackung mit Optimaler Modifizierter Atmosphäre

Details

Veröffentlichungs-Nr.

EP4726604

Anmeldetag

17. September 2025

Veröffentlichung

15. April 2026

Rechtsraum

EP

Abstract

Modified Atmosphere Packaging (MAP) extends food shelf-life but is not customized for specific commodities and supply-chain conditions, leading to sub-optimal usage. The present disclosure utilizes physics-based models to simulate the system of MAP and generate data for shelf-life of the food commodity for various designs of MAP films stored in different environmental storage conditions. Further, this data is used to develop a hybrid recurrent neural network (RNN) and deep artificial neural network (ANN) model, which learns how the changes in storage conditions of temperature and relative humidity affect the shelf-life of the food commodity for different designs of MAP. Whereas optimization of multiple ordinary differential equations is time and compute resource intensive, the developed hybrid RNN-ANN model can be used as a surrogate which makes optimization significantly less resource intensive. A surrogateassisted optimization model thus developed can be used to predict the optimum design of MAP for specific storage conditions.

Anmelder

Firma

Tata Consultancy Services Limited

Land

🇮🇳 Indien