Simulation for Chemicals, Oil & Gas
The Case Rate-Based Simulation Was Built For
Most simulation software models a queue of parts. In a chemical plant there are no parts — there is material moving at a rate, through reactors and tanks and pipes, in campaigns that change grade and in batches that cannot be interrupted. Rate-based simulation was created for exactly this, and it is the one industry where the paradigm difference is not a nuance but the whole thing.
Why entity models struggle here
To model bulk material as discrete entities you have to chop it into pseudo-parts. Make them small and the model runs too slowly to explore anything; make them large and the answer is too coarse to act on. The alternative — a combined discrete/continuous language — means writing differential equations, which puts the model out of reach of the people who understand the plant.
Rate-based simulation represents flow as flow and fires events only when a rate changes. That is why a full year of a plant runs in under a second, and why a thousand scenarios is an afternoon rather than a project.
What tends to be binding
Intermediate storage between production and packaging
Bulk production and packaging rarely want to keep the same time, and when packaging is obliged to take output as it is made, neither can be scheduled on its own terms. Sizing the store between them is a capital question with a scheduling answer — and the gain from decoupling is routinely larger than the gain from buying more of the constrained stage.
Campaign scheduling and grade changes
Changeovers between grades carry cleaning, purge and off-spec cost, so campaign length trades directly against inventory and responsiveness. Move the product mix and the binding constraint can move with it, which defeats a schedule optimised against a fixed bottleneck.
Tank farms and shared vessels
Shared intermediate capacity couples processes that look independent on a flowsheet. A vessel committed to one campaign is unavailable to another, and the interaction only shows up over time.
Capital against overtime
The recurring question is whether to buy equipment or run the existing plant harder. Answering it needs the time split — production, repair, changeover, idle, overtime — under demand that varies, including the periods when demand exceeds capacity.
Every one of these is a dynamic interaction, not a rate calculation. A plant balanced on paper can be badly unbalanced in operation, and the difference is entirely in how the stages couple to one another over time.
Who has used it
Rohm & Haas · ICI Paints · Glidden · Elf AtoChem · BICC General Cable
Chemicals work on this site
The bagging lines were tied to the reactors
Packaging dedicated to individual bulk lines, obliged to pack off as product was made. Modelling intermediate storage decoupled them — and surfaced low-capital growth options the company had not known it had.
Rohm & Haas · named client quote → Same Mechanism, Different IndustryBuying time instead of buying a line
Stabilising a partially-processed intermediate decoupled two stages that had to run in lockstep. 19.8% more effective production in peak periods, and the model runs live in a browser.
Run the simulator → Recirculating MaterialToo little storage stops the expensive end
In-process storage sized against a recycle stream that scheduling itself changes. Undersize it and expensive upstream processing shuts down.
Read the case study →Adjacent work
The method has also been applied to resource and logistics problems in this sector and in government — long-horizon transport and storage planning for Department of Energy waste programmes, and facility-maintenance resource modelling used to build long-term service contract proposals. Those are network and resource studies rather than production-line studies; the underlying treatment of flow is the same.
Where to start
The browser sandbox runs a rate-based line with no download and no sign-up. The argument underneath is in how big a buffer should be and starved versus blocked; the paradigm itself is in the methodology.
Related: Food & beverage · Packaging & CPG · All case studies