Makespan
Makespan provides a factory scheduling platform that unifies plant simulation and AI-driven scheduling into a single live model. The platform builds a digital replica of the plant—every station, conveyor, setup, and shift—and trains its AI scheduler directly on that running simulation, so the plan re-solves in seconds when floor conditions change. This eliminates the drift between separate planning tools and keeps production schedules synchronized with real-time operations.
- Manufacturing / Industry 4.0
- Artificial Intelligence
- Industrial Automation
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Factory scheduling tools typically separate simulation from scheduling, creating drift between planning models and actual floor conditions. When machines drop, orders jump, or setups change, overnight planning runs leave operations teams with stale schedules that don't reflect what is happening on the floor right now, leading to costly bottlenecks and idle capacity.
Solution
Makespan provides a factory scheduling platform that combines plant simulation and AI-driven scheduling into a single live model. The platform first builds a digital replica of the plant—every station, conveyor, setup, and shift—and runs it forward to identify bottlenecks before they impact production. It then trains its AI scheduler directly on the live simulation, teaching it real constraints like setups, tooling, labor, and due dates, rather than relying on spreadsheet assumptions. When the floor moves—a machine drops or an order jumps the queue—the AI re-sequences every job around the live constraints and re-solves the plan in seconds, without requiring an overnight batch run.
Target Audience
Manufacturing operations teams and factory planners at discrete and process manufacturers who need to keep production schedules synchronized with live floor conditions.
Features
- Single live model unifies simulation and scheduling, eliminating drift between separate planning tools
- Digital twin of the plant captures stations, conveyors, setups, and shifts for accurate forward simulation
- AI scheduler is trained directly on the running simulation, learning real constraints rather than assumed parameters
- Real-time re-sequencing re-solves the plan in seconds when machines drop, orders change, or other disruptions occur
- Continuous re-learning updates the scheduler automatically when the plant configuration changes
- Drag-and-drop interface with live makespan recomputation for planners