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Cycle Time

Cycle time measures how long a single process step actually takes -- from start to finished result. It is the foundation of every process analysis.

Cycle time describes the actual duration of a work step or a complete run. Unlike takt time, which is a target value, cycle time is a measured value taken directly from the process.

There are different definitions depending on context: In unit production, it's the time from start to end of a work operation. In series production, it's the time between two consecutive finished parts.

Cycle time naturally varies from cycle to cycle. That's why it's important to measure multiple cycles and look at both the average and the variation. High variation indicates an unstable process.

Reducing cycle time is one of the most powerful levers in process optimization: Every second saved per cycle multiplies with the number of units and adds up to enormous savings.

Formula

Cycle Time = Processing Time + Ancillary Time + Waiting Time within the Process Step

Practical Example

At an assembly station, 25 assemblies are completed in 30 minutes. The average cycle time is 72 seconds. The takt time is 60 seconds. The process is 12 seconds too slow -- a bottleneck that can be resolved by optimizing hand movements or improving material staging.

How Leanshift Helps

The stopwatch function in Leanshift precisely captures cycle times across multiple runs. It automatically detects variations and calculates the stable current state as a basis for improvements.

Frequently Asked Questions

How do you measure cycle time correctly?

Measure at least 10-15 consecutive cycles, mark outliers, calculate the average and variation. Important: Always measure at the actual process, never derive from standard times.

What is the difference between cycle time and lead time?

Cycle time measures a single process step. Lead time encompasses the entire timespan from raw material to finished product -- including all waiting and storage times between steps.

Why does cycle time vary?

Common causes: Different operator experience levels, material deviations, tool wear, lack of standardization, or ergonomic issues.

Related Terms

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