Maximum Demonstrated Speed

Reference metric for the performance factor in continuous manufacturing

The Maximum Demonstrated Speed (MDS) is the central reference used to calculate the performance factor on the ENLYZE platform. Understanding the calculation basis is helpful for correctly interpreting the performance factor and performance losses.

What is the Maximum Demonstrated Speed?

The MDS is the highest stably achieved production speed for a specific product on a specific machine—the highest observed actual performance. The concept is inspired by the Ideal Cycle Time from discrete manufacturing but optimized for continuous processes.

MDS is used to calculate the performance factor:

Performance Factor=Achieved SpeedMDS\text{Performance Factor} = \frac{\text{Achieved Speed}}{MDS}
Performance Factor=Produced QuantityMDSRequired Production Time=Production Time with MDSRequired Production Time\text{Performance Factor} = \frac{\frac{\text{Produced Quantity}}{MDS}}{\text{Required Production Time}} = \frac{\text{Production Time with MDS}}{\text{Required Production Time}}
Performance Losses=Required Production TimeProduction time with MDS\text{Performance Losses} = \text{Required Production Time} - \text{Production time with MDS}

If a product is manufactured at MDS speed throughout an entire run, the performance factor is 100%.

Maximum Run Speed – The Basis of MDS

The Maximum Run Speed (MRS) is the highest stably achieved speed within a single production run.

How is the Maximum Run Speed calculated?

We calculate the Maximum Run Speed (MRS) using a sliding window concept (optimization interval). Imagine a box (window) that moves step-by-step across the performance data of a production run. The width of the box is defined by the optimization interval, which can be adjusted.

At each step, we consider all data points within the window and record the minimum value found. This value is plotted as a blue point on a new graph.

The box continues sliding step-by-step (e.g., every 10 seconds) across the entire run. At each step, we find the lowest value in the box and add it as a blue point to the graph. This process continues until the end of the run is reached.

The lower graph shows all of these minima. The highest of these is taken as the MRS for that run.

Why is the minimum value within the interval used?

This method makes the calculation robust against outliers in performance.

The effect is illustrated here:

If we had chosen the highest value within the interval, the calculated throughput would have been much higher. However, that peak was not stable—the speed dropped right afterward.

Our method only considers values that remain stable over the full length of the interval. Downward outliers do not distort the result, as the maximum of the minima is used. This ensures that only realistic and sustainably achievable speeds are considered in the evaluation.

Calculating the Maximum Demonstrated Speed (MDS)

After calculating the MRS for each run of a product, the MDS is determined as the highest MRS across all runs for that product.

You can view the MDS and all MRS values (performance distribution) for a product in the product overview in the ENLYZE app:

Data Requirements for Determining MRS

To calculate an MRS, the following conditions must be met:

Optimization Interval: Choosing the Right Length

The optimization interval can be set individually for each machine in the ENLYZE app under Settings > Performance Recording.

It’s important to define the correct interval length:

  • If the interval is too short, temporary peaks may be selected that do not reflect stable production.

  • If the interval is too long, entire production runs may be excluded because the interval is longer than the production run.

Runs shorter than the optimization interval will not produce an MRS and won’t appear in the product overview. These runs are marked as having poor data quality.

If you need help selecting the ideal optimization interval length, feel free to contact us anytime!

No Data

If there are periods without data during a run (data gaps), those periods are skipped. Visually, the sliding window "jumps over" those gaps.

Overlapping Bookings

Time periods during which the equipment is assigned to multiple runs simultaneously are also ignored. It’s not possible to clearly assign such periods to one specific product. Therefore, the sliding window cannot enter time segments with overlapping bookings:

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