Augos Factory / Proof / Food packing plant
Case study · Food packing
Three identical lines. One packed half as much. One fault code explained why.
Same machines, same products, same crew. Line 1 packed 1.67 million units in a month. Line 2 packed 855,000. Nothing on paper said why.
The problem
Twins that weren't
Three packing lines sit side by side. They run the same machines and products, with the same pool of operators.
In one month, line 1 turned 56.2% of its paid time into good output. Line 2 managed 31.7%, and packed roughly half the units.
The usual suspects didn't fit. Crew, shift and product mix were all shared, so none of them explained the gap.
What the record showed
One fault code, one line
A sensor timed every stop, and operators gave each one a reason at the line. Sorted by fault code, the gap came down to one specific fault code. Hours lost to it in month 1:
| Line | Hours lost to that fault code |
|---|---|
| Line 1, the best of the three | 0 h |
| Line 2, the line that lagged | 61.4 h, over 47 stops |
| Line 3, the middle line | 1.1 h |
The suggestion
74% of line 2's breakdown time came from one fault code that line 1 never hit. Fix that station on line 2, with line 1 as the reference.
Line 1 against line 2 in month 1:
| Measure | Line 1 | Line 2 |
|---|---|---|
| Good output, share of paid time | 56.2% | 31.7% |
| Availability | 78.3% | 51.6% |
| Hours lost to that fault code | 0 h | 61.4 h |
| Units packed, approximately | 1.67 million | 855,000 |
Source: Augos platform, Downtime Report and Performance Overview. Three anonymised packing lines, one month in 2026. Site, products and people removed.
The fix
Line 1 became the reference
Each stop averaged about 78 minutes. That is long enough to hurt, but short enough to clear and move on.
Operators had become good at recovering from it, which is why it never looked like one big problem.
Maintenance traced the fault on line 2 to its root cause and fixed it. Operators no longer had to fire-fight the same stop, shift after shift.
Holding the standard
Down, and it stayed down
Checked every month
That fault code fell from 61.4 hours to 25.4, then 9.2, and 2.4 hours by month 8. And month 9 cost only 18 minutes.
Augos caught one flare-up
It rose once, to 24.3 hours in month 6. The record showed it at once, and it was back to 2.4 hours within two months.
Method
- Source: Augos platform Downtime Report and Performance Overview, one month in 2026.
- Lines: three packing lines with the same machines, products and operators.
- Stops: timed by the line sensor, with reasons given at the terminal.
- Good output: net production time as a share of paid time.
What this case leaves out
- No rand value: the plant has not shared its sales value per product, so the case reports hours and units.
Measured figures only, as the platform recorded them.
Questions
This case, answered
Were the three lines really identical?
Yes. They run the same machines and products with the same pool of operators. Each line has its own sensor and Augos Operator Terminal.
Could the gain have been a good season?
No. Over the same months, line 1 slipped from 56.2% to 46.9% good output. The gain belonged to the line that was fixed, and line 2 now outpaces its twin.
Why did it take Augos to find it?
Before, the plant knew line 2 was slower. After, it knew which fault code, how many stops and how many hours. That comparison only exists when every stop on every line carries a reason.
Find losses like these on your own line.
Thirty minutes with a manufacturing specialist, on your own lines and products.
- Every stop timed and given a reason
- Read by your own team
- Prices in rand, ex VAT
A manufacturing specialist replies within two business hours to set a 30-minute call.