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Estimate potential cost, time, and CO₂ savings when early detection prevents long-term and expensive testing. For example...
Recycled materials present new challenges for pipe durability. Traditional 1000-hour tests are costly and unsustainable for variable waste streams. Our data-driven approach simulates long-term performance from short-term tests – avoiding expensive product testing while ensuring reliability.
This is an estimator based on industry feedback and calibration values derived from PolyCore's internal LCA/LCC baseline for hydrostatic pressure testing. Actual savings vary by lab setup, energy mix, and process conditions – adjust the values to match your reality.
EN 1852-1 acceptance ~1,000 h. Default 700 h.
Imagine having 1 outlier(s) of approximately 700 hours falling short of the required 1000h benchmark due to insufficient recycling/virgin compositions or unforeseen batch variations. Having our model applied in advance would save you:
Cost Saved
2.630 €Time Saved
700 hCO₂e Avoided
403 kgThe 10,000h ISO 9080 Benchmark
The calculations above apply to 1,000h test outliers. But imagine training our model to predict the 10,000h benchmark of ISO 9080 – the test method is still the same: hydrostatic pressure pipe test.
Instead of wasting a minimum of 14 months of test time and significant costs and CO₂e, you could predict the outcome using our model. Here are potential savings if you had 1 outlier in this test running for 9,500h instead of the required 10,000h:
Potential savings per outlier (9,500h test failure)
Real-world 10,000h tests may have different cost structures. This projection uses the EN 1852-1 model coefficients for illustration.
With your configured parameters, here is what you could save over the next five years:
Total Cost Savings in 5 Years
3.500 h
Time Saved
2.013 kg
CO₂e Avoided
Based on EN 1852-1 model parameters
Models are linear in avoided hours by default. Enable fixed terms to include extrusion/material effects. Actual savings vary by lab, energy mix, and process. Baseline figures from internal case studies.