VARNISH: Quantifying the EBITDA Value of SmartOil G3™ Technology (Part 6)

3 days ago

8 min read

VARNISH: Quantifying the EBITDA Value of SmartOil G3™ Technology

Article by William Gillette (LogiLube, LLC)

On an ultra-class hydraulic excavator like the Liebherr R9800, hydraulic-fluid condition drives valve response, thermal stability and, ultimately, how many productive hours the machine can deliver. Two companion articles set up the argument this piece quantifies: “Why Varnish Becomes an EBITDA Problem” lays out why a fixed 1,000-hour hydraulic-oil drain is a weak proxy for oil condition and why draining the reservoir does not fully reset the system, and “Inside Adaptive Dosing™” examines the technology behind a condition-based alternative: SmartOil G3™ Autonomous Fluid Intelligence™, Sensor Fusion™ (multi-domain sensing), Exception Sampling™, laboratory confirmation and Adaptive Dosing™.

This article puts a number on what that shift is worth, first on a single R9800, then across Fortescue's approximately 55-unit hydraulic-excavator fleet in the Pilbara iron ore region of Western Australia.

The Economic Problem with Calendar-Based Replacement

Pilbara Iron-Ore Economics

Fortescue (ASX: FMG) reported an FY26 hematite realised price of approximately US$90.70 per dry metric tonne, FY26 underlying EBITDA of US$8.635 billion, and an underlying EBITDA margin of approximately 51%. Public planning documents put Fortescue's large hydraulic-excavator fleet at approximately 55 units, principally in the 400 and 600-tonne classes. The fleet mix by specific model (R9400, R9600, R9800, CAT 6040, CAT 6060) is not publicly disclosed, so the fleet composition used below is modeled for illustration rather than claimed as Fortescue's actual asset roster. Fortescue's electrification program is progressively replacing part of this fleet which is addressed later in this article.

For an R9800 specifically, illustrative assumptions used in this model include:

an effective ore-loading rate of 6,000 dry metric tonnes (dmt) per hour
Fortescue's FY26 realised hematite price
the 51% EBITDA-margin proxy, 8,000 scheduled operating hours per year
8 hours of downtime per hydraulic oil service.

With these assumptions, gross ore-value throughput works out to approximately US$544,200 per productive hour, or approximately US$277,500 of EBITDA-equivalent production value per hour.

These figures represent production value exposed, not a claim that every downtime hour is an identical, permanent accounting loss. A mine can recover some lost tonnes through stockpiles, dispatch changes or extra shifts. However, when the excavator is the production constraint, the economic leverage is substantial as shown in figure 1

Figure 1: Illustrative economics of prevention utilising Smart Oil G3™.

Per-Machine Economics

Scaling the same model by nominal face-shovel capacity (Liebherr lists approximately 22 m³ for the R9400 and 37 m³ for the R9600; Caterpillar lists approximately 22 m³ for the CAT 6040 and 34 m³ for the CAT 6060), using the common assumptions of 8,000 operating hours/year, eight 1,000-hour drain events under the conventional model, two drains/year under condition-based management, and eight hours of downtime per event, yields 48 recovered productive hours per machine per year across the class:

Table 1: Approximated EBITDA values for different types of excavators*

*Throughput figures are economic-model proxies, not OEM production guarantees. Actual tonnes per hour depend heavily on bucket fill, material density, fragmentation, swing angle, bench configuration, truck match and operator practices.

Based on the values above, we can model two scenarios shown in figure 2.

Figure 2: Illustrative annual economics for a single R9800 hydraulic system: eight scheduled drains versus two condition-based drains.

Figure 3 shows per-machine economics for various types of hydraulic excavators including:Hitachi EX3600-7, CAT 6040, CAT 6060, Hitachi EX5600-7 and Hitachi EX8000-7 and the associated EBITDA equivalent.

Figure 3: Per-Machine Economics – Illustrative annual economics for ultra-class hydraulic excavators in Pilbara iron-ore mining applications

The 55-Excavator Fleet Model

Because the exact fleet mix is not public, a useful way to frame the fleet-wide answer is a sensitivity across three fleet-composition assumptions:

Table 2: Fleet Assumptions and estimated EBITDA values as per fleet assumptions

The base-case scenario (~30 m³ fleet-average bucket, consistent with a fleet weighted toward R9400/CAT 6040 and R9600/CAT 6060-class machines, with a smaller population of R9800-scale units) is used as the reference for the fleet-wide model below. At approximately 4,286 dmt/hour blended productivity, the fleet-average excavator supports approximately US$389,000 of gross production value and approximately US$198,200 of EBITDA-equivalent value per productive hour.

Applying the same maintenance assumptions used for the single R9800 (8,000 operating hours/year; eight drain events/year under fixed-interval maintenance versus two under condition-based management; eight hours of downtime per event) across all 55 machines:

Table 3: Annual improvements using two scenarios for various fleet economic factors

Under these modeled assumptions, shifting the 55-machine excavator fleet from eight scheduled hydraulic-oil drains per year to two condition-based drains potentially protects approximately US$1.03 billion of annual gross iron-ore production-value exposure, or approximately US$523 million of annual EBITDA-equivalent production exposure at Fortescue's FY26 51% underlying EBITDA margin, equivalent to about 6% of Fortescue's entire FY26 underlying EBITDA of US$8.635 billion.

EBITDA Exposure Is Not the Same as Guaranteed EBITDA

The US$523 million figure should not be represented as a guaranteed incremental improvement to Fortescue's reported EBITDA. It is the EBITDA-equivalent value associated with 2,640 modeled productive excavator-hours (48 hours × 55 machines) no longer consumed by six additional scheduled hydraulic-oil drain events per machine per year.

The amount Fortescue ultimately converts into additional EBITDA depends on mine-specific operating conditions. Some excavators may be moving waste rather than saleable ore. Maintenance can sometimes be coordinated with other planned outages. Stockpiles may temporarily buffer lost digging capacity. Fleet dispatch may move trucks to another loading unit. Some lost tonnes may be recovered later. A realization factor therefore provides a more appropriate enterprise-level financial range:

Table 4: Annual EBITDA impact compared to the share of recovered productive value monetized

A reasonable commercial planning range is therefore approximately US$180–260 million per year, if Fortescue captures roughly 35–50% of the modeled productive-hour value, equivalent to roughly 2–3% of FY26 company-wide underlying EBITDA. That range excludes the direct operating savings from reduced hydraulic-oil consumption, fewer filter changes, reduced disposal, service labor, mobile-maintenance support and reduced safety exposure, and assigns no additional value to avoiding an unplanned varnish-related hydraulic failure.

Downtime Sensitivity

The actual time required to completely drain, service, refill, circulate, inspect and return an R9800 to production will vary by mine. The model is worth checking across a few service-duration assumptions:

Table 5: EBITDA values compared to various downtime per drain intervals

Even at only four hours of downtime per drain event, the economic value associated with six avoided interventions remains material. Which is why the business case should not be framed around “how much does the hydraulic oil cost?” The more useful question is: “How much excavator production is consumed by changing it?”

As shown in figure 4, for a R9800, longer loading cycles can lead to lost production and EBITDA.

Figure 4: R9800 Workflow demonstrating how slower hydraulic response can cascade into lost production

Fortescue's Electrification Program Does Not Remove the Opportunity

Fortescue is actively electrifying its excavator fleet. It reported 16 electric excavators already operating in 2026 and stated that around half the fleet is expected to be electric by the end of 2026. Electrification does not eliminate the hydraulic-fluid opportunity: the R9400 E and future electric hydraulic excavators still depend on large, high-performance hydraulic systems. The SmartOil G3 / Adaptive Dosing value proposition therefore remains relevant through Fortescue's diesel-to-electric fleet transition.

From Pilot to Bounded Autonomy

A reliable implementation begins with a bounded engineering pilot: an R9800, or comparable machine, with meaningful production exposure and sufficient operating and oil-analysis history. Preference should go to a machine showing elevated or unstable hydraulic temperature, recurring filter issues, accelerated antioxidant depletion, elevated MPC or varnish potential, repeated hydraulic-oil replacement, recurring valve problems, or unexplained changes in hydraulic performance. Document the oil formulation, reservoir and total system volumes, filtration configuration, oil-addition history, cooler performance, component history, operating profile and historical laboratory results, and establish baseline samples before enabling dosing.

From there, the program progresses through four controlled stages:

Monitoring Mode — SmartOil G3™ characterizes normal relationships among fluid condition, hydraulic temperature, load, machine hours and oil additions.
Advisory Mode — the system identifies developing abnormal conditions, initiates Exception Sampling™ when appropriate, and recommends intervention for engineering approval.
Supervised Dosing Mode — approved logic commands a bounded treatment dose while personnel review the event and subsequent fluid response.
Autonomous Mode — the system acts within validated limits, documents every intervention, and escalates conditions outside the approved model.

Autonomy is earned through evidence, not assumed at the outset.

Measuring the Business Result, Not Just the Oil Result

A successful pilot tracks three tiers of metrics.

Fluid Metrics

MPC trend, antioxidant reserve, viscosity, dielectric trend, acid number, particle behavior, water, filter differential pressure, oil makeup, treatment concentration.

Machine Metrics

Hydraulic temperature, valve response, hydraulic alarms, filter life, cycle-time consistency, pump or valve interventions, unscheduled hydraulic maintenance.

Business Metrics

Excavator availability, scheduled and unscheduled downtime, litres of hydraulic oil consumed, filter-service events, maintenance labor, tonnes moved, truck queueing, cost per tonne, production hours preserved, EBITDA-equivalent production exposure protected.

The objective is a defensible chain: fluid condition → intervention → hydraulic response → machine response → production result.

Figure 5 demonstrates how the business results can be measured based on the 3 aforementioned KPIs.

Figure 5: Illustration of the business result from utilizing SmartOIl G3™

That means tracing exactly how much oil was added, drained and treated; what happened to varnish potential and antioxidant reserve; whether filter differential pressure and valve interventions improved; how many drain events and maintenance hours were avoided; how many productive hours came back to the machine; and, ultimately, how many tonnes remained in the mine plan because the excavator remained available.

Conclusion: The Machine Is the Business Case

Varnish control in ultra-class mining equipment is not fundamentally an oil-management problem. It is an availability and production problem. A fixed 1,000-hour interval cannot determine whether the oil is actually degraded, whether contamination is present, or whether the underlying issue is mechanical rather than chemical, and draining the reservoir does not fully reset the system regardless.

At the individual-machine level, condition-based hydraulic-fluid management can reduce unnecessary drain events, oil consumption, filter use, maintenance labor and personnel exposure. At the fleet level, the value multiplies. For Fortescue's approximately 55 large hydraulic excavators, the modeled shift from eight scheduled drains to two condition-based drains per year represents 2,640 productive excavator-hours potentially returned to the mining system annually, corresponding to approximately US$1.03 billion of gross production-value exposure and about US$523 million of EBITDA-equivalent exposure under the Pilbara assumptions used in this article. SmartOil G3™technlogy implementation can add EBITDA to the operations and enhance Fortescue shareholder value.

Those figures are not a guarantee of incremental EBITDA. Actual value realized depends on mine scheduling, asset utilization, ore-versus-waste movement, maintenance coordination and the ability to convert recovered machine availability into additional tonnes. But even partial realization of the recovered productive time can create an enterprise-level economic impact far greater than the direct cost of the hydraulic oil itself.

Varnish begins as a chemical degradation mechanism. It becomes a fluid-condition problem. If unmanaged, it can become a hydraulic-performance problem. And on a high-value mining asset, it can ultimately become a production and EBITDA problem.

Sense the condition. Capture the evidence. Treat only when justified. Verify the response. Extend oil life when the data supports it. Protect the productive hour.

About LogiLube

LogiLube, LLC is a Denver, Colorado-based technology company focused on advancing real-time fluid condition monitoring and predictive maintenance through its patented SmartOil™ platform. The company's SmartOil G3 Autonomous Fluid Intelligence™ layer combines third-party in situ sensors, Edge-AI processing, and Local Language Models (LoLM) to deliver continuous monitoring, anomaly detection, and remaining useful life (RUL) predictions for industrial assets. Serving industries such as data centers, mining, and energy, LogiLube enables operators, OEMs, and asset owners to reduce unplanned downtime, optimize maintenance strategies, and unlock the value of high-fidelity operational data across distributed fleets.

SmartOil G3™ technology is protected by U.S. Patent No. 10,466,152; 11,761,946; 12,681,003; Chilean and Australian Patents, and other U.S. and International Patents Pending.