Chemical Manufacturer Supply Chain Modeling

A chemical manufacturer facing a planned plant capacity expansion needed to understand whether its downstream infrastructure could absorb the increased output. Specifically, the company had to determine whether existing storage tanks, piping manifolds, and shipping facilities would become bottlenecks under higher production loads — and whether additional capital expenditures in those areas would be necessary. In process industries like chemicals, where storage and logistics assets are capital-intensive and long-lead-time items, committing to infrastructure investment without rigorous analysis carries significant financial risk. The company needed a way to simulate the full downstream supply chain before any physical changes were made.

Rockwell Automation's consulting services team built a detailed discrete-event simulation model of the production line using Rockwell Software Arena Simulation Software, serving as a digital twin of the chemical facility's supply chain. The model captured storage tank capacities, initial product volumes, manifold and piping configurations, production unit capacities, and available loading positions at the shipping facilities. To make the model accessible to the company's own engineers, the team developed a custom Excel front-end interface that allowed non-simulation experts to modify system parameters without directly editing the Arena model. This configuration layer gave engineers the flexibility to evaluate both current-state operations and proposed expansion scenarios, running what-if analyses across a range of capacity and throughput assumptions before committing capital.

Supply chain simulation provided the decision-makers with clear, data-backed answers on infrastructure requirements. The core finding was that additional storage tanks and shipping facilities were not required to support the planned production increase — a conclusion that potentially avoided significant unplanned capital expenditure. Beyond the immediate expansion decision, the Arena model was retained as a standing planning asset, supporting ongoing process improvement and capacity planning initiatives. The Excel-based front-end ensured that the company's own engineering team could operate and update the model independently, extending its value beyond the original project scope.

• Digital twin simulation can resolve capital expenditure decisions before ground is broken, providing a lower-cost alternative to physical prototyping or conservative over-building.
• In process chemical environments, simulation models must capture piping topology and manifold configurations — not just throughput rates — to accurately reflect material flow constraints.
• Building an accessible front-end (e.g., Excel) for simulation models significantly increases adoption and longevity; engineers are more likely to reuse a tool they can operate without specialist support.
• Retaining the simulation model post-project as a live planning asset multiplies its ROI across future capacity, scheduling, and process improvement decisions.
• Engaging a vendor's consulting services team to build the model, rather than purchasing software alone, can accelerate deployment and ensure the model accurately reflects operational complexity.