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Data is a vital new business asset for manufacturing companies. But turning this data into value and a competitive advantage requires artificial intelligence (AI) and machine learning (ML). These technologies can help companies glean actionable insights from their data to improve their manufacturing processes. More and more, companies are turning to manufacturing plant sensor data for insights. This data can help retrospectively examine the causes of production disruptions when it is collected and processed through an industrial Internet of Things (IIoT) solution. But the data has even more potential to predict the future. Integrating AI/ML into IIoT can help companies improve their overall equipment effectiveness (OEE), increase the life of their assets, enhance the overall quality of production, and become more sustainable – and that’s just the start. That said, the process of using manufacturing data in predictive analytics comes with its own set of unique challenges. Organizations need to be aware of potential data security and data quality issues. Some companies have also faced difficulties finding qualified engineers and data scientists who can effectively leverage these technologies. And understanding the true return on investment (ROI) can be troublesome, too. When companies can transform these challenges into opportunities, however, they will derive handsome gains. This ebook will discuss some of the specific use cases that progressive organizations have addressed by integrating AI/ML with IIoT. |
