Compare Optimization Scenarios and Identify Gap to Potential
Key Capabilities
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
- 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
- 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
- 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
- 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
- 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
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
