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Haul road losses
implementation study.
Separate route conditions from payload, queue and operating context before assigning a cause to a slow cycle.
Evidence & maturity
Production deployed. This study describes the implemented workflow, its outputs and operating limits. Screenshots are implementation examples; no customer endorsement or quantified financial result is claimed.
Implementation
Compare travel observations within a defined route and direction, inspect speed and grade, and compare a segment against its own baseline with sample count and confidence. Reconcile any time-loss estimate with source cycles.
Screenshot from a production system, identifiers altered. It documents an interface, not deployment acceptance or achieved savings.
Documented output
The retained route/advisor descriptions show how a finding carries its comparison basis. No confirmed tonnes recovered, road repairs or savings are asserted.
Validation and limitations
Requires representative history and agreed filters. Sparse samples, GPS gaps and traffic context can invalidate a comparison. The baseline advisor and learned machine-learning model are both production deployed.