Quality

Losses due to scrap production

Quality Losses

Quality losses capture the time lost due to the production of scrap.

To calculate quality losses, the time required to produce the amount of scrap is determined. Since the exact time when scrap occurs cannot be precisely defined, the calculation is based on the average production speed for the respective order.

Example: Calculating Quality Losses

A total of 750 kg of raw material was processed over 3 hours and 30 minutes for the order. Of that, 700 kg was good product and 50 kg was scrap. Additionally, there was a 30-minute downtime during the run.

Average speed:

$$\varnothing \text{ Performance} = \frac{\text{Total Quantity}}{\text{Runtime} - \text{Downtime}}=\frac{750 kg}{3h30min - 30min}=250\frac{kg}{h}$$

Time lost due to scrap:

$$\text{Quality Losses} = \frac{\text{Scrap Quantity}}{\varnothing \text{Average Speed}} = \frac{50kg}{250\frac{kg}{h}}= 12\text{min}$$

Downtimes are excluded from the average speed calculation, as they do not count toward actual production time.

Quality Factor

The quality factor expresses the ratio of good quantity to the total quantity produced.

$$\text{Quality Factor} = \frac{\text{Good Quantity}}{\text{Total Quantity}}=\frac{700kg}{750kg}=93\%$$

Quality calculation with ENLYZE

Quality data for each production run is usually incorporated via the synchronized booking data. In some cases the data can be extracted directly from the machine.

It’s important to ensure that the scrap quantity is measured in the same unit as the performance. That means if throughput is measured in kg/h, the scrap must also be recorded in kg.

If performance and scrap are measured in different units, a conversion step must be implemented. While this is always possible in principle, it inevitably introduces inaccuracies, as conversions require approximations and assumptions.

What we observe in practice is that these approximations tend to be in the same order of magnitude as the scrap quantities themselves. This significantly impacts the reliability of quality losses, scrap rate, and the quality factor.

If your production doesn't track quality data, the OEE can still be calculated based on the availability and performance KPIs. The quality factor will be is assumed to be 100%.