A Structured Framework for Measurement Uncertainty in Bulk Gain-in-Weight Batching Systems in Feed Manufacturing SCADA

Abstract

Bulk Gain-In-Weight (GIW) batching systems present a metrological challenge absent from isolated weighing operations. 

When multiple ingredients are dosed sequentially onto a single weighing platform, each measurement is taken against an accumulated platform load rather than an empty reference. The uncertainty associated with each dosing event is therefore dependent on the delivered ingredient weight, but on the total accumulated load at the time of measurement — and grows with each successive ingredient in the sequence.

Current SCADA implementations for bulk GIW batching are not known to incorporate an explicit measurement uncertainty model. 

Without it, two critical operational functions are absent: pre-dosing feasibility assessment, which would identify whether a formula's ingredients are compatible with the weigher's metrological capability before production begins, and process-level uncertainty tagging, which would enable metrologically complete batch histories and support reliable aggregated reporting.

This paper identifies this architectural absence as the core problem and proposes a GUM-consistent conceptual framework to address it. 

The framework defines uncertainty evaluation from instrument resolution, process repeatability, and accumulated platform load; propagates uncertainty through the cumulative batching sequence; and integrates it into SCADA architecture to support both operational functions. 

Field observation, structured practitioner inquiry across multiple facilities, and quantitative analysis of production records — where an ingredient recorded as compliant within ±2 kg tolerance carries a combined expanded uncertainty of ±4.49 kg — confirm the gap and motivate the framework.