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German AI to Reduce Food Waste
Artificial Intelligence to Assist in Production Planning

Food wastage is grave problem often encountered in developed nations. On one extreme where we have those who can’t access even one meal a day, there are those who waste more than half of what’s produced. Germany is currently facing a similar issue where approximately 12 million tons of food is wasted every year. Domestic households contribute to the 52% of the waste generated. And around 30% of the waste is generated in the food production and processing stage itself.

In order to combat this problem, the Fraunhofer Institute for Casting, Composite and Processing Technology IGCV is working along with its partners on a project named Resource – efficient Intelligent Foodchain (REIF). And artificial intelligence (AI) has proved to be a valuable asset in this project.

This system will focus on cheese, bread, meat and other foods which are easily perishable and more wasted. It will help in the efficient production of these items by employing data based algorithms. These machine learning methods are built to optimize sales and assist in production planning, and will also optimize process and plant control system.

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The Resource – efficient Intelligent Foodchain (REIF), for the coming three years will strive to come up with approaches in order to reduce food waste. This will be done with the assistance provided by Artificial Intelligence (AI). This research will be focusing on production and consumption of food and come up with plans to optimize these processes.

The researchers are aiming at making production lines more efficient and will be developing better forecast models in order to understand the demands in consumption. This is done to create a better connection between consumption and production of food items. Germany has allied itself to the United Nation’s goal and is utilizing all possible means in order to reduce its food waste by half by 2030.

Patrick Zimmerman, a scientist at Fraunhofer IGCV said, “Two aspects are key to significantly reducing food losses in these sectors – minimizing overproduction and avoiding waste. We apply AI to the entire value chain, especially in the production facilities. To do that, we adapt and select the algorithms that are suitable for the respective application. We look at the predictability and controllability in all areas – from production on the farm to sale in the supermarket – to optimize their potential.”

His colleague, Philipp Theumer further explains that common problems such as overproduction and waste can possibly be avoided. Employing concepts such as targeted forecasts on food requirements and by reducing quality related food loss.

The role of AI in this process is explained by Patrick Zimmerman. Taking example of meat mixer, the expiry date of the meat products is influenced by the temperature and duration of the mixing process. In this case, AI can be employed to control the amount of energy in the mixing process. This will help to extend the expiry date of the meat products and keeping it fresh. This will lead to a longer selling time of such products and in turn will reduce the wastage of food.

The Resource – efficient Intelligent Foodchain (REIF) program currently consists of 18 partners. This project will be coordinated by the University of Applied Sciences Augsberg. This project is funded by the Federal Ministry of Economics and Energy with an amount of 10 million euros.

 

 

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