sucesss case

The intelligent use of valves in industry

A Case Study on Reducing Maintenance Costs and Downtime

To maintain the integrity of equipment in the industry and ensure the continuity of processes on the factory floor, maintenance is essential. According to ABRAMAN (2018) – Brazilian Association of Maintenance and Asset Management –, this area accounts for around 5% of the industry’s gross revenue.

There are different types of maintenance in a manufacturing routine, the main ones being:

  • Preventive maintenance: performed in a scheduled manner, with the aim of reducing the probability of failure or degradation of machinery;
  • Predictive maintenance: based on machine operating patterns to predict when maintenance should be performed;
  • Corrective maintenance: performed after a failure occurs, and aims to repair the machinery so that it can perform the required function;

Despite its great importance, optimizing the maintenance process in the production process is still a major challenge. Industries have the mission of understanding how to readjust their practices and planning to meet future demands. In this case, technology is a great ally, by enhancing their production capacity, reducing errors and increasing profits.

By investing in data science, it is possible to implement predictive maintenance, avoiding sudden stops that directly influence productivity. According to McKinsey (2017), this type of maintenance can increase the useful life of a machine by 20% to 40%, and reduce process costs by up to 25%.

This case study aims to detail how a large multinational company in the food industry used the ST-One Solution. Here, the purpose was to optimize line maintenance and ensure the proper functioning of a valve matrix. To do this, the industry teamed up with a disruptive data technology, which helped it act directly on the problem, resulting in gains in several areas. Learn more about us.

 

 

 

 

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