With machine learning, AI, and robotic process automation to apply diagnostic and predictive analytics and scenario modeling to create autonomous maturity across operations. These technologies provide reliable situational awareness, the ability to model options for the action that results in the best outcome, data access, and automation of work orders and process transfers.
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The manufacturing sector continues to become more flexible and responsive to consumer demands. Vision systems for robots provide the ability to detect and classify objects, map the environment, and respond accurately in areas such as material handling and assembly.
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Machine learning algorithms for anomaly detection can support DevOps in work routines by training and applying generalized ML models to detect hidden patterns and identify suspicious behavior.
Sooner or later, it will evolve into fully automated systems that can not only detect anomalies, but also recover and mitigate them.
