Machine learning is a methodology of data processing that allows the organization’s own machinery to make decisions without the intervention of any human being. This is possible through the analysis of patterns within its own history (Deep learning), in order to adopt a behavior in the future through retro-inspection and the main purpose is that based on the experience it has acquired, it can increase the success rate in its activity.
This methodology makes a lot of sense in companies that base their business on the manufacture of goods. Industries manage to improve their results through comprehensive control and optimization of the different processes that make up their activity. As we saw in the previous article regarding Big Data, the optimal use of business data is key to building a good strategy. Within the world of food and specifically in the meat sector, great results can be obtained through the application of this technology. Some examples are:
Machine Learning allows you to select potential customers through their behavior on social networks. It allows you to know what is the right time to publish content and thus reach the target audience. It also allows you to predict the best time to contact a potential customer. In meat industries it is also applied indistinctly.
This methodology allows an automatic inspection of the different elements that are sent to other companies or individuals. Consequently, it makes it possible to drastically reduce the number of returns, increases the degree of satisfaction of the final customer, improves the relationship of trust with other subjects and, ultimately, the productive activity is benefited.
Automatically optimizes the production chain, identifies signals to have an accurate picture of supply and demand. Avoid production stoppages through preventive actions, through Machine Learning breakdowns are detected instantly, and also in meat companies.
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The EC studies reviewing materials in contact with food Published by: Josep Feixas – Share: The European Commission (EC) launches the public consultation on the