Takt
Make more of your production capacity
Optimized schedules for jobs, machines, changeovers and deadlines. When a rush order lands or a machine stops, Takt re-plans the whole schedule.
Due dates and changeovers planned together, and an AI assistant sets it up with you.
How it works
From your data to a planning model
Describe the plant in your own words; the assistant builds the model on your data.
A good schedule rests on what your planners already know: which machines can run which jobs, which changeovers cost the most and which orders cannot slip. Takt turns that knowledge into a model the optimizer can search, so every plan it proposes respects it.
- 01
Bring your data
Bring production data from your enterprise and planning systems. Start from the order lists, routings and machine data you already export; a direct connection can follow later.
- 02
Describe your operation
Describe machines, job types and operating rules in plain language. The AI assistant asks about the cases your data does not show, such as rush orders, shared tooling or preferred lines.
- 03
Refine the model
Review and refine the planning model with your team. Ask the AI assistant why a job landed where it did, then adjust the rule behind it before the first live plan.
Respond to a new priority
An urgent order lands mid-week. The obvious fix often pushes other orders late; a re-optimized sequence can absorb it without a single late order.
Illustrative scenario
Three machines, three product families. Switching family costs a one-hour changeover.
- Family A
- Family B
- Family C
- Changeover
- Urgent order
AI assistant
An assistant from set-up to every re-plan
Set up by conversation
Describe how your work runs in plain language. The assistant drafts the planning model from what you say and the data you bring.
Rules you can read
The model is laid out as rules, resources and priorities that your team can check and correct.
Ready for what-if questions
Later, ask the assistant what-if questions: change the order of orders, add a rush job or take a machine offline, and compare the revised schedules.
What a better schedule buys your plant
More output
Smarter sequencing cuts changeovers, so the same machines make more good parts per shift.
On-time delivery
Every order is planned against its due date, so late orders show up early, while there is still time to act.
Faster replanning
When a machine goes down or a rush order lands, compare revised plans before you commit.
Plans you can explain
Every plan follows the rules your team set, so planners can see why it looks the way it does.
Features built for the factory
Better sequences
Balance deadlines and production priorities against machine eligibility, setups, dependencies and changeovers.
Capacity and availability
Align jobs with machine calendars, teams and available materials. Shifts and maintenance windows are built in.
What-if planning
Compare new orders, outages and changing production priorities before updating the schedule.
Under the hood
Planning applications run on the 4colors Optimizer
Takt, Roster and Stride run on 4colors optimization algorithms, the family that set new best-known schedules on a public project-scheduling benchmark.
Rules you describe become a model the engine searches within your time budget, so what-if questions return comparable alternatives, not a single plan.
Powered by
4colors Optimizer
Original search algorithms, tested on demanding benchmarks and run to your time budget. Also powers the Optimizer for Scheduling, the Optimizer for QUBO and the Quantum Compiler.
Explore the 4colors OptimizerMore planning apps
Roster
Rosters that cover every shift with the right skills, fairly, re-planned when someone calls in sick.
Stride
Project schedules built on the people and equipment you have, re-planned when a project slips.
The mathematics behind production schedules
Explore more use cases- Guide
Modeling Changeovers in Production Scheduling
The next job may depend on what the machine ran before it.
Read the guide - Insight
Batch Manufacturing: Why the Order of Production Matters
Bigger batches can reduce setups while making urgent orders late.
Read the insight - Use case
Why Scheduling a Factory Is Harder Than Lining Up the Jobs
Follow machines, precedence and competing deadlines through a real scheduling model.
Explore the use case - Insight
The Value of Asking What If
Why adding a machine can leave production unchanged.
Read the insight - Insight
The Schedule Broke. Now What?
Evaluate what must change without discarding every commitment.
Read the insight
Bring us your hardest production week
Share a real week of orders and machines, and see what an optimized schedule does with it.