AboshThe Theory of Constraints focuses improvement on what currently limits the result of a system. Identify that constraint, use its existing time well, make the rest of the flow support it, add capacity if justified, then check where the limit moved. Follow good output or customer delivery. Keeping every machine busy can increase inventory without improving either.
A clear priority for the whole flow
Less avoidable lost time at the constraint
Capacity spending checked against the actual limit
Define the result and its boundary
Choose the output the operation needs: good completions, customer deliveries or another clearly defined result. Keep demand and the time period beside it. A resource that is busy making unwanted stock is not helping that result.
Find what limits that result now
Compare capacity with the product mix, then observe queues, blocking and starvation. Starvation means a process waits for incoming work; blocking means it cannot pass work forward.
Check scheduling and release rules as well as equipment. The limiting condition can change when demand, routing or reliability changes.
Use and support the existing constraint
First reduce avoidable waiting at the constraint within approved working limits. Make material, information and qualified people available when needed. Then adjust other steps so they support its pace rather than flooding it.
- Identify
Find the condition that currently limits the system result.
- Exploit
Use the available constraint time effectively without bypassing safeguards.
- Subordinate
Align release and supporting work with the constraint.
- Elevate
Consider added capacity when the remaining limit justifies it.
- Repeat
Find the new limit after the change.
Check the rule before buying equipment
A model or limited trial can help distinguish a capacity shortage from avoidable waiting. Compare the complete flow under the same demand assumptions.
Recheck after the improvement
Once a loss is removed, another step or policy may become the limit. Keep checking delivery, queues and operating cost. The old bottleneck should not remain the default priority after the evidence changes.
A related example from Abolfazl
Abolfazl connects release decisions, queues and launch lead time.
In English, on founder Abolfazl’s personal blog. This is related reading, not an independent technical source.
Practical checklist
- Define the system result and demand.
- Use a consistent time period.
- Check capacity for the actual product mix.
- Observe blocking and starvation.
- Look for policy and release limits.
- Protect the constraint without creating excess WIP.
- Test the case for extra capacity.
- Find the new limit after changing the flow.
FAQ
FAQ
Sources and further reading
Authoritative references used to research and verify this guide.