AI in food production with predictive analytics will monetize the food industry in novel ways
Like many other industries, artificial intelligence (AI) is having a major impact on the food and beverage industry. Companies in the industry are becoming more aware of how AI can increase efficiency and profits, reduce waste, and protect against supply chain disruptions. These are all part of what is known as Industry 4.0.

4 uses for AI in the food industry

1. Consumer trends as a guide for creating new recipes

All food manufacturers recognize that they must constantly look for creative ways to update their product range in order to stay current and generate new revenue streams. With AI, businesses can traditionally predict what their customers want through research and adapting to new trend.

By mining vast amounts of data about sales patterns and taste preferences by demographic, manufacturers can now predict future trends and design new products that capitalize on them more quickly.

AI is also being used to give customers more customization options for what they buy.

2. Improved supply chain management

The ability to effectively manage supply networks is one of the most important goals for food manufacturers. Modern businesses are using algorithms based on artificial neural networks to track shipments at every stage of the supply chain, raising the bar for food safety and achieving complete transparency.

Use AI in the food sector to make accurate forecasts and control inventory and pricing. Using this kind of predictive research can help food companies stay ahead and reduce waste and unnecessary costs. Even though sophisticated food supply chains are more extensive and complex than ever before, AI can give companies a deeper understanding, thereby improving their ability to increase sales.

3. A more hygienic production line

Food safety violations can be incredibly costly for food manufacturers. In terms of fines (which can be millions of dollars in worst case scenarios) and reputational damage due to poor health and safety. AI in food processing mitigates the risk of these violations in a number of ways.

Additionally, AI can be applied to improve hygiene for the manufacturer’s staff. Face and object recognition technology is used to monitor compliance with hygiene standards. For example, these AI-enabled devices can flag situations where proper production procedures are being ignored or his PPE is not being worn, allowing companies to more closely manage site hygiene.

4. Food sorting

Production lines are slowed down by the time-consuming and labor-intensive process of food sorting, which requires the use of many workers. This is especially true for sorting fresh produce, where human sorters are responsible for removing anything that does not meet the standards required for sale.

With the help of AI, both the time and number of people required to perform this important task can be greatly reduced. Each item is evaluated for shape, color and structural integrity using cameras and lasers to automatically identify what should be filtered out.

Additionally, using machine learning techniques, such systems can continuously improve accuracy and help reduce waste of good products.

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Source: Analytic insights

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