Previously in this blog series, we explored what the terms ”artificial intelligence” and “machine learning” mean and discovered how the technology is revolutionizing industrial markets today. Now, let’s take a closer look at the benefits promised by machine learning (ML).
The most significant payoffs of using ML in industrial sectors include:
- Greater innovation;
- Process optimization and industrialization;
- Automation; and
- Improved quality, with the latter often yielding the quickest returns
Real-time monitoring systems for early detection of issues, advanced cognitive systems for issue investigation, predictive maintenance systems, and feedback loops for design teams have proven to be helpful aids in enhancing quality and reducing direct and indirect costs related to rework, waste, warranty claims, and recalls.
When solutions like these and other ML applications share common digital models of products and assets, and are deployed via a common collaborative platform, they can also provide the consistent digital thread (digital continuity) needed for continuous product and process innovation. This makes immediate wins in quality improvement an important lever for exponential gains through accelerated innovation.
Now that we understand the benefits of machine learning, what are the challenges that companies must overcome?
In the next blog installment, we will explore and address the key challenges of artificial intelligence that industries face today.
Part 4: Benefits of Machine Learning in Industrial Contexts
Read our White Paper on Artificial Intelligence In Industrial Markets
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