Industrial optimization studio for the Intellect platform
Intellect iImprove is the desktop tool engineers use to design, simulate, and publish the optimization strategies that Intellect Server runs in real time. It turns predictive models into actionable setpoints by blending model predictive control (MPC), constraint handling, desirability curves, and cost weighting—so production teams can target higher throughput, tighter specs, or lower energy use across complex assets.
Why teams rely on iImprove
- Purpose-built MPC for industrial processes – Supports single-model and multi-model MPC structures, so you can optimize individual wells, entire lift-gas systems, or multi-column refining trains from one canvas.
- Multi-objective trade-off control – Define multiple goals (maximize oil, minimize steam, hold quality targets) and let iImprove negotiate the Pareto front with explicit desirability and cost functions .
- Hard constraint and safety enforcement – Encode operating envelopes, equipment limits, regulator thresholds, and “never exceed” values directly into the optimizer to prevent solutions that look good on paper but would trip the plant.
- Visual response exploration – Evaluate model responses with 3D surface plots to see exactly how manipulated variables influence outputs before you trust a new setpoint strategy.
- Offline what-if + online deployment – Run what-if studies and scenario sweeps on the desktop, then publish approved optimizers to Intellect Server so the same logic executes automatically in the field.
- Seamless suite integration – iImprove consumes the curated models, CVA contexts, and detectors produced in Intellect Expert, packages its optimization tasks, and hands them to Intellect Server’s task-oriented runtime with full provenance.
Key capabilities
Model Predictive Control Builder
- Choose single- or multi-model MPC structures.
- Specify prediction horizons, control horizons, and weighting for each controlled variable.
- Mix first-principles and data-driven models inside the same optimizer when needed.
Objective, constraint, and desirability management
- Define objective functions (maximize, minimize, hit a target) for each KPI.
- Assign desirability curves (e.g., asymmetrical penalties for over- versus undershooting) and explicit operating costs so the optimizer reflects business value.
- Add hard constraints, soft bounds, and tie-breaking rules; iImprove’s solver respects them before proposing any setpoint.
Multi-objective trade-off analysis
- Run sweeps to expose trade-offs, sensitivity, and robustness, using the multi-objective methods outlined in “Intellect Solutions: Optimization.”
- Compare scenarios and capture lessons learned before deployment.
Response surface visualization & validation
- Render 3D surface plots that show how manipulated variables influence outcomes; identify cliffs, flat spots, or non-linearities early.
- Use those visuals to brief operations teams or justify control-room changes.
Deployment-as-setpoints
- Wrap approved optimizers into Intellect tasks that can recommend or automatically write new setpoints through Intellect Server (“Intellect Architecture”).
- Track every deployment with metadata (models used, constraint sets, tuning parameters) for auditability.
Value delivered
- Higher, steadier production – iImprove turns virtual metering and predictive insights into tangible setpoint changes that lift throughput and keep quality in-spec.
- Safer optimization – Built-in constraints, desirability weighting, and visualization prevent “chasing ill-measured performance” or creating unintended consequences.
- Faster iteration – Engineers can test scenarios offline, reuse optimization templates across wells or units, and push refinements into Intellect Server without rewriting code.
- Transparent collaboration – The combination of trade-off analysis, 3D plots, and packaged deployment artifacts gives operations, planning, and management a shared view of why the optimizer chose a given operating point.