Reducing carbon footprints in food industry through AI-Powered lean manufacturing

Muneeb Ur Rehman

Authors

Muneeb Ur Rehman Author

Keywords:

Carbon Footprint Reduction, Industrial Sustainability, Artificial Intelligence, Food Manufacturing, Predictive Analytics, Reducing CO2 Emissions, Resource Optimization, AI in Food Production, Smart Food Factories

Abstract

This review describes how Artificial Intelligence (AI) has transformed food manufacturing by optimizing production, reducing waste, improving sustainability and reducing CO2 emissions. The AI uses predictive analytics, real-time monitoring and computer vision to simplify operations, reduce environmental impact and ensure product consistency. AI-powered smart food factories automate tasks, predict maintenance needs and check quality in real time to boost output. AI-powered supply chain management reduces food waste, optimizes resources and simplifies logistics. AI helps create customized nutrition and new protein sources to meet customer needs. The AI has many benefits but high prices, data privacy concerns, and job loss make it difficult to use in food processing. To solve these issues, we must invest in AI training, rules and moral use. Robotics, block chain integration and AI-driven 3D food printing will transform food production, meeting global sustainability standards and reducing CO2 emissions. It also addresses the main barriers to AI use such as infrastructure, morality and money and offers various solutions. By responsibly using AI and addressing these challenges, the food industry can generate more efficient, secure and sustainable production systems.

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References

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