Process Scale-Up: From Lab to Commercial Success

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At IntelliScale Technologies, we specialize in systematic and intelligent scale-up of chemical processes—from benchtop experiments to full commercial deployment. Our approach combines rigorous experimentation, AI-enhanced modelling, and advanced simulation to ensure your technology scales reliably, efficiently, and profitably. 

 Here are the key stages we cover, each backed by structured methodology, real lab testing, and AI-enhanced engineering tools: 

• Design of lab-scale test plans based on process type, feedstocks, and reaction characteristics
•  Identification of critical variables through Design of Experiments (DoE)
• Execution of test runs using IntelliScale’s in-house lab facilities and partnered academic labs
• Collection of operational, thermal, kinetic, and yield data

•  Data analysis to validate feasibility, conversion, selectivity, and energy demands
•  Statistical methods to quantify sensitivity and performance variability
•  Identification of bottlenecks and critical scale-dependent behaviours

•  Use of AI/ML algorithms to predict scale-dependent effects
• Evaluation of capacity expansion scenarios under uncertainty
• Smart optimization of operating conditions for industrial performance

•  Completion of full process simulation models (e.g., Aspen HYSYS, Custom Models)
•  Dimensioning of unit operations (reactors, heat exchangers, separators, pumps, etc.)
•  Application of fluid dynamics, heat/mass transfer, and kinetics at scale
•  Capacity vs. complexity trade-off analysis

• Generation of full Front-End Engineering Design (FEED) deliverables:
  • Process Flow Diagrams (PFDs)
  • Piping & Instrumentation Diagrams (P&IDs)
  • Equipment lists, control strategies, and utility balance 

• CAPEX/OPEX estimates and scale-up risk assessment 

•  Collaboration with fabrication and construction teams for detailed engineering
• Oversight and technical support during equipment installation and commissioning
• Startup support and troubleshooting during initial operation
• Ongoing optimization through AI-powered monitoring tools

• Data-Driven Scaling: Our experimental programs are built on intelligent test planning—not trial and error.
   
• AI-Enhanced Tools: We use predictive algorithms to reduce uncertainty and accelerate scale-up.
   
• Simulation-Centric Design: Every step is validated with robust digital models.
   
• End-to-End Partnership: We don’t stop at design—we support all the way through to commercial success.
   
• Process Knowledge Reuse: Our platforms allow knowledge capture and reuse for future scale-ups.