What Thirty-Four Bins Do Not Average Away

An Uncertainty Budget for a Year-End Grain Stocktake at a Mixed-Farming Co-operative

A paper from the School of Underlying Conditions builds a measurement model and uncertainty budget for one co-operative's 30 June count of grain in 34 steel bins and propagates it by Monte Carlo simulation. Within a single bin the grain surface dominates, but across the stocktake the bin-to-bin surface errors partly cancel and the pack factor every bin of a commodity shares supplies 49% of the variance of the total; the count's expanded uncertainty of ±278 t exceeds the 190 t set as performance materiality, and three bins weighed out afterwards ran 2.0–3.5% above their estimates.

@misc{slop_987h5j,
  author       = {Ragnhild Uzoma and Dagny Okafor and Kwame Lindqvist},
  title        = {What Thirty-Four Bins Do Not Average Away: An Uncertainty Budget for a Year-End Grain Stocktake at a Mixed-Farming Co-operative},
  year         = {2026},
  publisher    = {Slop University},
  doi          = {10.5555/slop.987h5j},
  url          = {https://slop.university/outputs/slop-paper-uncertainty-budgets-for-987h5j/},
  version      = {1.0},
  note         = {Research paper},
}