Target outcome · Increase CSTR facility utilisation from 75–80% to 85–90% and reduce changeover times from 6–8 hours through intelligent batch sequencing and resource coordination.
Business problem
Pharmaceutical CSTR facilities consistently operate below optimal capacity, with equipment utilisation rates of 75–80%, inefficient changeovers lasting 6–8 hours, and inventory levels exceeding 45–60 days due to suboptimal production planning. Static scheduling systems cannot adapt to equipment conditions, material delays, or changing priorities, while Excel-based manual planning tools struggle to optimise complex interactions between equipment availability, material flow, utilities, and personnel across multiple production lines.
What it does
The CSTR Resource Planning & Scheduling Agent is an autonomous Decision Agent purpose-built for intelligent, explainable pharmaceutical production planning and resource optimisation.
Agent structure
- Dynamic batch sequence optimisation for maximum facility utilisation and minimum changeover time
- Multi-resource coordination across materials, utilities, personnel, and equipment availability
- Utility load balancing (steam, cooling water, compressed air) across multiple CSTR reactors
- Campaign planning and product quality segregation management
- Integration with CMMS to align predictive maintenance windows with production schedules
What the team handles
Handles
Batch sequence optimisation, resource allocation coordination, capacity planning, changeover scheduling, inventory level recommendations, and utility load balancing within configured business constraints.
Does not handle
Major campaign strategy changes, capital investment decisions, or resource reallocation decisions that exceed defined escalation thresholds.
Humans retain authority over
Authority over major campaign decisions, strategic capacity investments, escalated resource conflicts, and any planning action beyond defined management approval thresholds.
Current process vs. with AI Agent
Outcomes and measurement
Equipment utilisation rate
Changeover duration
Inventory holding days
Production disruptions from maintenance conflicts
*All figures are typical ranges. Achievable range depends on existing control maturity, data quality, and site-specific conditions.
Data inputs
Schedules
Other
utility capacity
*Categories only — no tag names or system-specific field references. Exact data mapping is scoped per site.
Scoping questions
Expect these questions in a first scoping conversation. They signal engineering discipline and help narrow the template to your specific site context.
- What MES and ERP systems are currently used for production scheduling, and what APIs or data export mechanisms are available for real-time integration?
- What is the current changeover time breakdown — what proportion is cleaning validation, equipment setup, material staging, and quality control clearance?
- How many CSTR reactors and downstream processing units are in scope, and what is the current capacity utilisation baseline?
- What utility metering and capacity management systems are installed, and can they provide real-time load data for balancing optimisation?
- What planning horizon is required — shift-level scheduling, weekly campaigns, or longer-range capacity planning — and what approval workflows need to be integrated?
Want our AI to walk you through these scoping questions?
SPEAK WITH OUR TEAM
Get specialist advice on scoping this for your site.
Our specialists will help you understand how the CSTR Resource Planning & Scheduling Agent fits your operations, what data you'd need, and what a scoping engagement typically looks like.
