Averages hide where a process actually breaks. Helm runs discrete-event simulation of complex processes on the same twin that runs the rest of the platform - surfacing bottlenecks, testing throughput and capacity, and identifying the points where the process fails under load.
A value chain is a sequence of stages, queues and shared resources - and the constraint is rarely where the spreadsheet says it is. Discrete-event simulation steps through the process event by event, so variability, queueing and contention show up the way they do in the real operation. You see where work piles up, what is starving downstream, and how far the process is from falling over.
Stages, queues, resources and routing taken from the same model that runs the business - not a throwaway diagram.
The process is stepped through event by event, so variability, queueing and contention behave like the real operation.
The binding constraint is found, not assumed - the stage that actually governs throughput, with the queue building behind it.
End-to-end throughput, utilisation and cycle time under a given configuration - and how much headroom is really left.
Push volume or strip a resource and see where the process tips - the point at which queues run away and the chain fails.
Test a change - add a resource, re-route, re-sequence - and see whether it moves the constraint or just moves the queue.
The simulation runs the process forward, animates work flowing through each stage, and lights up the queue building behind the binding constraint. Push the load and it shows the failure point - the moment throughput collapses. A live walkthrough of a discrete-event simulation is being built and will be published here.
The process is assembled from the twin - stages, routing, queues, resource pools and the rules that govern them. Because it comes from the live model, it reflects how the operation is actually configured, not an idealised flow.
The engine steps through the process event by event, with variability in arrivals and service times. Queues build and clear, resources contend, and the dynamics that averages hide play out over the simulated run.
The results show the binding constraint, the throughput it allows, and the load at which the process fails. Test a debottlenecking option and the simulation shows whether it actually moves the constraint.
Anyone responsible for throughput across a complex value chain - and anyone who has approved capacity to fix a bottleneck, only to watch the constraint reappear one stage downstream.
Bring us the process you cannot get throughput out of. We'll show you a discrete-event simulation on a representative twin - bottleneck, capacity and failure point.
