Daiwa Logistics (Misato branch) — Japan
Six diesel trucks between 4 and 6 tonnes at the Misato branch of Daiwa Logistics were each compared against a reference consumption figure for the vehicle. All six came in above their reference, from +4.2% to +17.6%, with a median of +9.3%. It is a narrow, unspectacular spread — which is what makes it worth reading.
Six trucks of the same class, on the same branch, in the same duty — the closest thing to a repeated measurement in this part of the dataset.
| Operator | Daiwa Logistics (大和物流), Misato branch (三郷支店), Japan |
|---|---|
| Vehicles | 6 diesel trucks — Hino 4 t, 5 t and 6 t, Isuzu Forward |
| Method | 基準燃費と比較 — comparison against a reference consumption figure |
| Measured quantity | Fuel efficiency, km per litre |
| Result | Median +9.3%, range +4.2% to +17.6% |
| Control group | None |
| Measurement period | Not recorded in the dataset |
Every measurement, not just the best one
| Vehicle | Before | After | Change |
|---|---|---|---|
| Hino Truck ４ｔ (1) | 7.10 | 7.75 | +9.2% |
| Isuzu Fowerd (1) | 7.03 | 8.27 | +17.6% |
| Isuzu Fowerd (2) | 6.85 | 7.13 | +4.2% |
| Hino Truck ４ｔ (2) | 7.10 | 7.76 | +9.3% |
| Hino Truck ５ｔ | 6.80 | 7.50 | +10.3% |
| Hino Truck ６ｔ | 6.81 | 7.26 | +6.6% |
| Median across all 6 measurements | +9.3% |
Method before result
Each truck was compared against a reference consumption figure — the method the dataset records as 基準燃費と比較. The reference is a per-vehicle expected consumption rather than a directly measured pre-treatment period, which is a weaker basis than a genuine baseline but a stronger one than a single day’s reading.
The spread is the interesting property here. Five of the six trucks fall between +4.2% and +10.3%, and only one Isuzu Forward reaches +17.6%. Across a group of six similar vehicles in similar duty, that clustering is more informative than any single figure in it.
Every percentage on this page was recalculated by us from the recorded before-and-after figures rather than taken from the summary column of the source; all of them reproduce the recorded value. That is a check on transcription, not on the measurement itself — it confirms the arithmetic is right, not that the reading was.
The limits of this trial
We publish these next to the result rather than in a footnote. If a limitation would change how you read the number, you should read it at the same time as the number.
Known limitations
- How the reference consumption figure was established is not documented. If it was derived from manufacturer data or from a fleet average rather than from the individual vehicle’s own recent history, the comparison is looser than it appears.
- Six trucks at one branch is a group, not a fleet result, and the branch is one of many.
- Load weight, route and season are not recorded, and heavy goods consumption is sensitive to all three.
- This is a dataset entry, not a trial report. What we hold is the before-and-after fuel-efficiency figure per vehicle as recorded in the master test dataset — not the operator’s raw fuel logs, not the odometer readings behind them, and not a written test protocol.
- There is no control group. No comparable untreated vehicle was tracked over the same period, so seasonal, route and traffic effects cannot be separated from the treatment.
- The measurement dates and the length of each measurement period are not recorded in these entries. We therefore cannot say how far each vehicle ran between the two readings, or which months the comparison covers.
- The figures were recorded by the operator or by the local distributor, not by an independent party, and we cannot re-derive them from primary records.
Reading this evidence in context
For a freight operator, a narrow spread across six comparable vehicles is a more useful signal than a large number on one vehicle — it suggests a repeatable effect rather than a lucky measurement, even though the method here cannot prove one.
The honest summary is a mid-single-digit to low-double-digit direction on 4–6 t diesel trucks, with +9.3% as the central figure and no control group behind it.
A pilot on a comparable fleet with untreated sister vehicles would settle in weeks what this dataset can only indicate.
Questions operators ask about this trial
What is a "reference consumption figure"?
Why is the spread so much narrower than in other datasets?
Can we see the underlying fuel logs?
Provenance
- Source
- Eco-Spray / NanoEFX master test dataset, compiled 22 March 2020 — operator-named section
- Recalculation
- All percentages recomputed from the recorded before-and-after figures
- Raw records
- Held by the operator or the local distributor — not in our possession
- Operator entry
- 大和物流三郷支店 — Daiwa Logistics, Misato branch
- Method as recorded
- 基準燃費と比較 (against reference consumption)
- Name release
- Operator naming approved by ECO EFX Solutions, 15 August 2026
- Last checked
- 15 August 2026
The only baseline that matters is yours
Every trial on this site was run on someone else’s vehicles, duty cycle and baseline. A NanoEFX pilot measures yours — and we will help you design it with a control group so the result stands up.