Compare Optimization Scenarios and Identify Gap to Potential

Key Capabilities

AI-based process optimization

AI-based process optimization

AI-based process optimization
  • Leverage cutting-edge AI and machine learning techniques to optimize production yield and energy efficiency
  • Uncover all yield drivers, from raw material quality to process conditions
Quality issue predictions with sufficient lead time

Quality issue predictions with sufficient lead time

Quality issue predictions with sufficient lead time
  • Utilize human-interpretable outputs to rapidly triage, diagnose, and resolve emerging quality issues
  • Leverage advanced machine learning algorithms to predict end-product yield, hours in advance
  • Incorporate historical interventions to prescribe the best mitigation actions
Leverage all relevant lab, enterprise, operational, and external data

Leverage all relevant lab, enterprise, operational, and external data

Leverage all relevant lab, enterprise, operational, and external data
  • Unify data in near real-time from process simulators, operational systems, ERP systems, and asset management systems to create a unified digital twin of the manufacturing environment
  • Time-align lab testing data with the operating conditions using native time-series support for all data
Applicable to all manufacturing types and processes

Applicable to all manufacturing types and processes

Applicable to all manufacturing types and processes
  • Support continuous processes with monitoring during steady-state as well as transitions
  • Monitor batch processes for batch quality and assessment of impact on downstream quality
  • Enable semi-batch processes with monitoring of both continuous processes and batch processes
Robust and rapid scenario analysis

Robust and rapid scenario analysis

Robust and rapid scenario analysis
  • Analyze and benchmark what-if scenarios to assess the impact of operational changes on yield and process efficiency
  • Assess simulated effect on quality, yield, and material consumption
Enterprise-wide collaboration

Enterprise-wide collaboration

Enterprise-wide collaboration
  • Align engineering, operations, maintenance, testing, and quality teams on a unified digital twin of the manufacturing process
  • Use bi-directional integrations with existing systems of record
  • Alert key users to mitigate issues and codify best practices
Download Data Sheet

Scope

C3 AI Process Optimization can be deployed across a wide range of manufacturing processes and industries.

Product Type

Discrete goods

Batches

Large-scale commodities

Manufacturing Processes

Continuous

Batch

Semi-batch

Industries

Oil & Gas

Petrochemicals

Specialty chemicals

Pharmaceuticals

Biotechnology

Advanced electronics

Discrete manufacturing

Benefits for Manufacturing Professionals

Process Engineer

Review AI recommendations, investigate opportunities, share findings with Operations.

Plant Operator

Execute recommendations to implement optimized process strategy.

Data Sources

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