How cognitive anomaly detection can optimize your maintenance efforts

About Event

Machine breakdown, set up and adjustment, minor stoppage and idling, and line speed reduction are some of the most common problems almost every asset-intensive business faces. Many of such businesses employ strategies like accurate down time tracking, categorizing down time with reasons, or attacking the largest sources of down time. However, optimizing maintenance efforts is a real challenge.

With the advent of artificial intelligence and the Internet of Things technologies, and cognitive computing, things have changed now. In this event, we will show you how machine learning algorithms make use of unsupervised learning and pattern recognition to make precise insights in less time, improve yield, and reduce operational risks. We are also going to cover what challenges asset-intensive businesses face while continuing with traditional approaches to anomaly detection. The roadmap of how to turn data into a strategic asset will be presented as well. Lastly, we will focus on how AI-powered smart asset monitoring can uplift your overall operational efficiency.

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Agenda

• Introduction
• Remote monitoring to improve transparency
• Common challenges to traditional approaches to anomaly detection
• Cognitive anomaly detection with AI
• Common myths vs. reality
• How to implement cognitive anomaly detection
• Use cases
• Benefits
• Smart asset monitoring powered by AI
• Q&A