sucesss case

Smart Industry: Data Science and Performance Improvement

A case study on how Data Science made productivity and performance in a food industry take a leap forward

The industry that seeks to achieve positive results invests in performance. It measures the productivity level of the machines, that is, whether the time and quantity of production are meeting the demand.

To maintain good machinery performance, it is necessary to monitor several aspects, such as adjustments related to the production speed of the equipment. Also, the maintenance process is essential to ensure that the machinery works according to the scheduled availability time. This happens because maintenance predicts failures, performs scheduled changes and avoids downtime.

According to the CNI (National Confederation of Industry), the investments planned for 2024 by the industry aim to expand production capacity (42%) and improve the current production process (42%). Furthermore, in 2023, approximately 74% of these industries had technological innovation as an investment strategy. The study “Investments in industry”, published in 2024, disclosed this information. It reinforces the sector’s efforts to improve performance.

One example of this technological innovation is digitalization, which helps the industry reach a new level of productivity. This case study shows how a large multinational food company used data science to improve the performance of its production lines. The company sought out the ST-One Solution after realizing that two apparently identical lines were running at different speeds. With the data collected, it discovered why this was happening and corrected the problem.

The impact is also on profitability, as performance is a critical factor in the financial results of industries. According to the Industry Portal, productivity gains of up to 86% can be achieved after implementing technologies in the production line.

Discover more cases like this, in an extended version, on the success stories page.

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