Lean calculate cycle time

But what about items that don’t start and finish on the same day? For example, let’s say an item started on January 1st and finished on January 2nd.  The above calculation would give a cycle time of two days (2 – 1 + 1 = 2). This is a reasonable, realistic outcome, which makes sense from a customer’s perspective: If we communicate a cycle time of one day, then the customer might have an expectation that they will receive their item on the same day. If we tell them two days, they have a realistic expectation that they will receive their item on the next day, etc. This is just one way that Kanban calculations can help you communicate with your customers.

In fact, if we look at these three measures, cycle time, ROI and customer satisfaction, we see that they form a mutually supporting and cross-checking system of ensuring productivity and effectiveness. Measuring anything else muddies the waters and can cause sub-optimal behaviors. The real challenge for most teams is realizing that all their local measures of performance and effectiveness may actually be causing harm (unintentionally) because they draw the team’s attention away from the three organizationally important measures.

Steven, Congrats on completing this research and your conclusions. I only have one small problem with it. The definition of Takt time used in the Six Sigma world is not something you calculate from your process but it is Defined by your customer demand for your product or service. Takt time is the ‘Demand time’….the time that you IDEALLY will take to turn out each consecutive product or service in order to keep up with customer demand for that products or service. The ideal CYCLE Time is one that is Equal to TAKT Time. This will make then stop both delays for the customer and also stop over-production. Correct me if I am wrong, but I don’t think this definition or Cyle and Takt time appears in your analysis ? Thanks. John Dennis

By creating burn-up lines based on the CFD, you can make rough predictions based on your WIP and Throughput. This allows you to estimate if you’re on track with your planned work and whether or not you can expect to finish the work in a set amount of time. Using a burn-up on a CFD is similar to how a  burn-down chart  functions in the Scrum methodology, while providing additional flexibility. (Tip: Burn-ups work best when applied to a short time period; projecting an average over a longer timeframe will produce tidy, but highly inaccurate forecasts.)

Cycle time is the time it take to complete your task or piece of the process (washing, loading or drying).
Takt time is the pace at which you need to produce to meet customer demand. It is available working time divided by customer demand in that period of time. Say if you have 5 working hours available to do laundry and you have 10 customers a day that need your services, your takt time is 5/10=. So you need to deliver a clean load every .5 hrs, or every 30 minutes. It is solely a calculated time based on your available working time and customer demand. It has nothing to do with your cycle time which is how long it takes you to perform a task.
The time to wash might be 60 minutes or might be, 90 minutes. In which case you can use your cycle time to calculate how many machines you should have or people washing (if hand washing).
In this case you would CALCULATE the number of resources you need:
(cycle time) / (Takt time) = # of resources needed. In this case 60 / 30 = 2. So you would need 2 machines to meet your takt time.

Lean calculate cycle time

lean calculate cycle time

By creating burn-up lines based on the CFD, you can make rough predictions based on your WIP and Throughput. This allows you to estimate if you’re on track with your planned work and whether or not you can expect to finish the work in a set amount of time. Using a burn-up on a CFD is similar to how a  burn-down chart  functions in the Scrum methodology, while providing additional flexibility. (Tip: Burn-ups work best when applied to a short time period; projecting an average over a longer timeframe will produce tidy, but highly inaccurate forecasts.)

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