D02 · REACTION · BATCH, SEMI-BATCH & CONTINUOUS
AI-Supported Reactor Intelligence
Turn reactor trajectories into early quality forecasts, safer operating guidance and repeatable batch performance.
NOVYRON is software-first and vendor-neutral: this is configurable software, integration and lifecycle service, not process equipment. The existing PLC or DCS keeps interlocks and regulatory control, and every recommendation stays inside a site-approved operating envelope under human oversight.
THE INDUSTRIAL PROBLEM
Batch, semi-batch and continuous reactors respond differently to heat release, mixing, feed composition and measurement delay. Quality is often known only after the batch has finished, while fouling, catalyst ageing and raw-material variability keep moving the relationship between recipe and result.
THE NOVYRON LAYER
NOVYRON builds a reactor digital twin and a batch-context layer above the site control system. It compares the live trajectory with approved historical runs, predicts endpoint and quality, and recommends bounded changes to feed profile, temperature target, agitation or transition timing. Safety instrumented functions and base control stay independent.
TYPICAL DATA INPUTS
- Temperature, pressure and jacket or coil duty
- Feed rates, ratios and cumulative additions
- Agitation speed, torque and power
- pH, dissolved oxygen, conductivity or spectroscopy where available
- Batch phase, recipe step and operator events
- Raw-material lots, laboratory quality and cleaning history
MODELS AND DECISIONS
- Dynamic state estimator for unmeasured conversion or heat-release proxies
- Multivariate batch trajectory and golden-batch comparison
- Endpoint and final-quality prediction with an uncertainty interval
- First-principles plus learned hybrid twin for scenario testing
- Anomaly detection for cooling loss, agitation degradation, fouling or abnormal progress
- Constrained predictive advisory that respects recipe and equipment limits
What each deployment reads, which models it runs, how it connects and how much authority it is given are designed for the site. None of it is pre-installed hardware, and none of it is a guaranteed autonomous function.
CORE CAPABILITIES
- PHASE-AWARE BATCH ALIGNMENT
- EARLY-WARNING HORIZON & EVIDENCE TRACE
- HEAT-REMOVAL MARGIN
- LOT-TO-LOT MATERIAL CONTEXT
- RECOMMENDATION & APPROVAL RECORD
- CAMPAIGN & CLEANING-EFFECT ANALYSIS
HOW IT WORKS
- S1Map recipe phases, control loops, interlocks and quality tests with site engineering
- S2Build a time-aligned batch data model and identify comparable production families
- S3Estimate latent reaction state, then train endpoint and quality models on it
- S4Test recommendations against the twin and against historical counterfactuals
- S5Validate in shadow mode and in supervised production trials
- S6Operate as decision support, or connect approved targets to the batch system
INTEGRATION POINTS
- DCS, PLC and batch control systems
- Historian and laboratory information management system
- Process analytical technology instruments
- MES, electronic batch records and material genealogy
- Maintenance and cleaning records
NOVYRON connects read-only and runs in shadow mode first. Any write-back is designed, tested and approved separately. Interfaces are chosen to fit the architecture already on site rather than forcing a new hardware stack.
MEASUREMENT EXAMPLES
These are measures for a baseline and target-setting workshop, agreed from your own data. None of them is a statement of a result NOVYRON has achieved.
- Batch-cycle time and phase-duration variation
- First-pass quality and endpoint accuracy
- Yield or selectivity proxy
- Energy and utility use per batch
- Abnormal-batch early-warning lead time
- Unplanned hold, rework and cleaning frequency
TYPICAL APPLICATIONS
- SPECIALITY CHEMICALS
- FOOD & INGREDIENT REACTIONS
- FERMENTATION & BIOPROCESS
- POLYMER & RESIN PROCESSING
- PILOT & SCALE-UP
DEPLOYMENT PATH
- 01Process and hazard-boundary workshop
- 02Batch genealogy and data-quality assessment
- 03Trajectory model and digital-twin build
- 04Historical replay including abnormal events
- 05Shadow mode and operator acceptance
- 06Controlled deployment with model-performance review
WHAT STAYS OUTSIDE
NOVYRON does not replace the safety instrumented system, the relief design, validated batch logic or the hazard study. Any automated action requires site approval, independent safeguards and defined fallback behaviour.
SAFETY, QUALITY AND GOVERNANCE
- The deployment architecture can be designed to segregate customer data by tenant and deployment boundary, subject to the hosting, access-control and contractual terms agreed with you. Edge, on-premises, private-cloud and managed-cloud patterns are all evaluated against your constraints.
- Role-based access, encryption in transit and at rest, audit logging, model and version traceability and a secure update process are defined during solution design.
- Data provenance, retention and permitted model-training use are documented contractually. Customer data is not silently pooled into general models.
- Predictions carry quality flags and uncertainty where that is technically meaningful. Drift and out-of-distribution conditions trigger review rather than false precision.
Bring us the process boundary
Share the process, the signals you already collect, the control architecture, the constraints and the outcome you need. An engineer turns that into a scoped data assessment, a shadow pilot and a deployment plan.