Factory Twin
Where is production really constrained — and what happens if we change the system?
What actually limits production — and how can we improve flow without creating a new bottleneck elsewhere?
Factory performance is shaped by interactions that are difficult to understand from isolated KPIs.
Production data often show machine utilisation, downtime, output or OEE separately.
But operational performance depends on how these elements interact.
The slowest machine is not always the real constraint.
And improving one process does not necessarily improve total output.
It turns the production process into a dynamic operational model.
A Factory Twin represents the flow of products through machines, workstations, labour resources and intermediate queues.
Instead of analysing each production step separately, the model evaluates system-wide consequences.
Process-flow modelling
Represent production steps, capacities, processing times and dependencies as a connected manufacturing system.
Bottleneck identification
Identify where queues, utilisation and capacity constraints limit total throughput.
Capacity scenario simulation
Test alternative shifts, machines, production volumes or resource allocations before changing operations.
Disruption and downtime analysis
Estimate how equipment failures, maintenance or process delays propagate through the production system.
Where is the real production bottleneck?
How much additional production can the existing factory absorb?
Would an additional machine or shift materially increase throughput?
Which process improvement would have the greatest system-wide effect?
How much does downtime at a critical machine affect total production?
