Unreliability in production caused by technical errors or defects can be fatal. But still, it’s quite common. Corrosion is in the middle of the most dominant causes of failure. As found by the , it was among the most frequent reasons for the malfunction of production in Germany in 2019. In this blog, we will tell you how to improve the reliability of your production by using AI.
How does poor evaluation of reliability affect the outcome?
The likelihood of such incidents increases over time as machines age. So chances of failure happening becomes more and more likely. This leads to a higher risk of injuries or property damage, and also an overall less efficient production if a failure occurs. To prevent this, it’s not uncommon to use analysis of reliability.
Traditional reliability analysis methods
To stay up to date the methods used to monitor the reliability of production should be appropriate. The Institute of Electrical and Electronics Engineers compared traditional reliability analysis methods with modern AI-based methods in 2020 to determine the most effective approach for monitoring the reliability of production. They pointed out that AI was able to perform better than traditional methods. Therefore, AI can show more accurate predictions of reliability in production
How AI can help gain a competitive advantage
The use of AI for monitoring reliability can help to understand monitored data more accurately and rapidly. Thus, it can save lots of money. Using AI for monitoring reliability can accurately and rapidly understand monitored data, resulting in significant cost savings. Predicting and preventing production failures and minimizing loss of efficiency due to unplanned failure is possible with AI. Predictive maintenance can leverage AI to deliver reliable and predictable production.
Technological innovation for reliability analysis
Progress in the accuracy of monitoring is inevitable. Thus, it’s better to embrace it, understand it, and use it to improve production. AI can help your company in many aspects to rise up to Industry 4.0 – the monitoring of the productions also needs to be kept in mind to evolve accordingly.
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