PETUUM REVOLUTIONIZES INDUSTRIAL AI
Manufacturing enterprises gain increased throughput, improved yield, greater productivity and more automated decision making


Petuum Industrial AI Use Cases

Data Management and Asset Connectivity

Real-time Condition Monitoring

Connected Plant and Operations

Asset and Process Prediction & Optimization

Predictive & Prescriptive Maintenance

AI-powered Process Operations and Optimization

AI Advisory and Operational Excellence

Quality Control & Intelligent Advisories

Field & Logistics Intelligence

Benefits of using Petuum's industrial grade AI:

  • Reduced variability and inconsistency
  • Avoid tedious, laborious, error-prone operations
  • Save costs : through energy savings, reduced failures and use of cost-effective fuels

Why Petuum AI:

Manufacturing enterprises are on a constant quest to improve yield, improve quality and lower costs.

With increasing automation and adoption of enterprise IT systems, greater quantities of data are now available, but harnessing this data to truly enhance operations is problematic without artificial intelligence.

Existing systems are unable to process the sheer complexity of this data to deliver timely and precise predictions, nor can they easily prescribe actions that balance quality, costs and safety tradeoffs.

Petuum Industrial Artificial Intelligence (AI) To the Rescue!

Petuum Industrial AI absorbs a variety of data types including timeseries data, unstructured log data, images and more to learn and deliver precise predictions of hundreds of parameters.

Additionally, it prescribes corrective actions to optimize multiple parameters such as throughput, quality, safety and cost.

It automatically anticipates changes in variables based on operator actions and adjusts operating conditions for the best metrics.

It also integrates with existing systems infrastructure such as OSIsoft PI systems and control systems to directly deliver timely parameter changes, so that completely automated, yet supervised operations can become reality.