Why the chemical sector should harness the power of machine learning

That's a process that may sound time-consuming -- and it is, if you're doing it in a low-tech way. "If a set of quality results does not meet standards, you can build algorithms and start doing repeatability studies to predict when things might go wrong," Ravi said. "Machine learning can be used for that. If you try doing the process analysis manually, it is going to take a lot of time. Machine learning algorithms can get that information quickly and minimize bad product quality by allowing leaders to be proactive and take corrective actions."