Freeport-McMoRan Inc.
[2025] APO 23
•18 July 2025
IP AUSTRALIA
AUSTRALIAN PATENT OFFICE
Freeport-McMoRan Inc. [2025] APO 23
Patent Application: 2023203092
Title:Methods and systems for deploying equipment required to meet defined production targets
Patent Applicant: Freeport-McMoRan Inc.
Delegate: Tim Gillett
Decision Date: 18 July 2025
Hearing Date: Written submissions filed on 18 December 2024
Catchwords: Patents – section 45 – examiner’s objection – not a manner of manufacture – mining equipment – Monte Carlo – simulation – forecasting – production target – remit to examination – inventive step
Representation: Patent attorney for the Applicant: GLMR
IP AUSTRALIA
AUSTRALIAN PATENT OFFICE
Patent Application: 2023203092
Title:Methods and systems for deploying equipment required to meet defined production targets
Patent Applicant: Freeport-McMoRan Inc.
Date of Decision: 18 July 2025
DECISION
Claim 1 of the application, as proposed to be amended is not for a manner of manufacture.
The application is remitted for further examination with a focus upon inventive step and manner of manufacture.
REASONS FOR DECISION
Background
Patent application 2023203092 (‘the present application’) was filed on 17 May 2023 in the name of Freeport-McMoRan Inc. (‘the Applicant’). The application was filed as a divisional application of 2021204532 (‘the parent’), the national phase entry of PCT/US2021/022494.
Four examination reports have been issued for the present application, each with a single objection that the application is not for a manner of manufacture. Similarly, four examination reports were issued for the parent application with each one objecting that the application is not for a manner of manufacture.
One inventive step objection was raised in the first report for the parent application. The Applicant responded to that objection, and it has not been raised since.
Amendments to the present application have been proposed on 20 June 2023, 9 April 2024, and 26 August 2024 with no objection taken. I have no reason to believe that those amendments are not allowable and as such, all further references will be to the specification as proposed to be amended on 26 August 2024.
The Applicant requested to be heard on 4 September 2024 and was invited to provide submissions by 20 December 2024. The Applicant provided submissions on 18 December 2024.
The examination of the present application is governed by the Patents Act 1990 (‘the Act’) as amended by the Intellectual Property Laws Amendment (Raising the Bar) Act 2012 (‘the Raising the Bar Act’) as the application was filed after 15 April 2013. Thus, the standard of proof that applies in the present case is the balance of probabilities (subsection 49(1)). I must accept the application if satisfied on the balance of probabilities that the application complies with the Act. If I am not so satisfied, then I can refuse the application (subsection 49(2)).
Description
The description begins by setting out the technical field as follows on page 1:
The present invention relates to mining operations in general and more particularly to
methods and systems for deploying equipment required to meet defined production targets.Following from this, the description addresses efficiency as follows on pages 1-1a:
The overall efficiency of the mining operation is based in part on the efficiency of the equipment and processes for delivering the excavated ore to the various locations for further processing. Part of that overall efficiency involves a determination of the capacities of the various loading and conveying systems (e.g., the number of shovels and haul trucks) that are required to achieve a desired production target. For example, failing to provide sufficient capacity, e.g., numbers of shovels and/or haul trucks, will make it difficult, if not impossible, to achieve the desired production target. While the desired production target may be more easily achieved by providing additional numbers of shovels and/or haul trucks, the provision of an excessive number of shovels and/or haul trucks also results in inefficiencies and represents a sub-optimal use of resources. Indeed, providing an excessive number of shovels and or/or haul trucks may make it more difficult to achieve the desired production target as a result of increased wait or idle times and/or traffic congestion resulting from the provision of an excessive number of haul trucks.
I understand from this that providing the appropriate equipment to mine sites is critical for efficient operation and meeting production targets.
The description follows by stating that existing solutions are typically empirical, involving significant trial and error. Furthermore, they are not dynamic so even if the optimal amount of equipment is reached, that number will soon cease to be optimal. Note the following on page 2:
While various methods of determining the appropriate equipment capacities (e.g., the number of shovels and haul trucks) that will be required to meet desired production targets are known and being used, such methods are typically empirical and usually require a significant amount of operational trial and error before arriving at the optimal capacities or numbers of equipment required to reach the desired production targets. Moreover, because the mining environment is constantly changing, even if the optimal numbers or capacities of the various systems happen to be reached, they will soon cease to be optimal as the mining operation progresses. As a practical matter, the optimal capacity is rarely reached and the mining operation will either involve insufficient or excessive equipment capacity, or will fail to consistently meet the desired production targets.
The specification elaborates on this point on page 8 with the following stated advantages of the invention:
A significant advantage of the systems and methods of the present invention is that they
may be used to provide highly accurate estimates or determinations of the system or equipment capacities required to meet defined production targets for material processing systems. Those estimates or determinations may then be used to deploy the equipment in numbers and capacities sufficient to meet the production targets…And further on page 8:
… Unlike prior methods, which are typically empirical and involve a significant
amount of time and effort to consider the numerous variables and possible equipmentcombinations involved, the methods and systems of the present invention provide rapid and definitive determinations of the particular system or equipment capacities (e.g., number of shovels and haul trucks) that will be required to meet the defined production targets. Moreover, the systems and methods of the present invention may be used on a more or less continuous basis to ensure that the deployed capacities remain sufficient to meet the defined production targets on a shift-by-shift basis.
I take from this that the application is directed at providing a rapid and accurate estimate of equipment capacity required to meet a set production target in a mining operation.
The description follows with further information in the form of consistory clauses which provide an overview of various aspects of the invention. Without going into detail, the explanations provided match that shown in FIG.3 closely which I have reproduced below.
The specification frequently uses the term ‘entropy’ to describe the system. Specifically, the stochastic simulation is said to estimate the effect of entropy by processing historical data.
Entropy is an unexpected word in the context of a mining operation. Having not encountered its use in this field before and being unable to locate it in any relevant glossary, I have concluded that it does not have a technical meaning in this field. Whilst the specification discusses the term, it does not clearly state that a special meaning is to apply. As such, a meaning derived from a plain understanding is appropriate which I will consider closely.
The Macquarie Dictionary[1] defines entropy as follows:
noun a measure of the unavailable energy in a thermodynamic system; it may also be regarded as a measure of the state of disorder of a system. A change of entropy in a reversible process is the ratio of heat absorbed to the absolute temperature.
[1] >
The specification is clearly not directed toward a thermodynamic analysis. As such, “a measure of the state of disorder of a system” is appropriate which is consistent with the specification on pages 5-6 which states:
As is known, entropy is a measure of the degree of disorder of a system. As used herein, the term entropy is also used to describe the degree of variability introduced into a system or process as a result of entropy changes.
It is not immediately apparent what this disorder pertains to or how it should be measured though. For instance, describing a disordered bookshelf as having high entropy does not seem appropriate.
The specification provides further context on page 6 as follows:
The cycle time and variance module 48 estimates the effect of entropy on the cycle time to produce the future cycle time estimate. Module 48 does this by providing historical cycle time data to stochastic simulator 40. Stochastic simulator 40 simulates systems, such as those systems described herein, having variables that change stochastically or randomly with individual probabilities. In the case of the cycle time and variance module 48, the stochastic simulator uses the historical cycle time data to simulate the cycle time 'system,' i.e., the cycles traveled by haul trucks 22 as they move between the material loading system 12 and the material processing system 26. Stated somewhat differently, the historical cycle time data are used by the stochastic simulator 40 to account for the effect of entropy on the material conveying system 14, e.g., haul trucks 22, to produce the future cycle time estimate for the material conveying system 14.
And further on page 14:
In one embodiment, stochastic simulator 40 comprises a Monte Carlo simulator, although other types of stochastic simulators are known and could be used as well.
With this information, once the plain meaning is supplemented with guidance from the specification, and noting that the reader must avoid absurd constructions, I consider that the person skilled in the art would understand entropy to be a non-specific reference to variability or randomness. The expression ‘estimate an effect of entropy’ should not be read overly literally as though the variability or randomness has been measured. Instead, I consider that it means that randomness is somehow accounted for in the modelling system and thus included in the resourcing estimate which is provided.
The specification discusses the effect that this variability or randomness has on the system on page 9 with the following:
For example, in a mining operation wherein a plurality of haul trucks are used to convey excavated ore from one or more shovels to one or more continuous material processors, such as ore crushers, the haul trucks will tend to periodically 'bunch up,' at various points in the cycle, with an excessive number of haul trucks queuing up at either the loading area (e.g., at the shovel) or the discharge area (e.g., at the crusher). Such bunching can also occur on the mine road network between the shovels and the crusher. The frequency and/or severity of the delays associated with such truck bunching is due to a number of factors and may be exacerbated if an excessive number of haul trucks are used or if an insufficient number of shovels and/or ore crushers are provided.
Indeed, because the various elements, systems, and processes (e.g., loading, conveying, and processing systems) of the material processing system are interrelated, the effect of entropy on any one of the various elements, systems, and processes will also affect the material throughput and efficiencies of the other elements, systems, and processes. Stated somewhat differently, variations resulting from entropy in one element, system, or process will ripple though the material processing system, potentially affecting the other elements, system, and processes as well.
This last point is important, and I will come back to it soon being: “variations resulting from entropy in one element, system, or process will ripple though the material processing system, potentially affecting the other elements, system, and processes as well”.
The specification discusses how the system handles the effect of entropy on the cycle time with the following on page 7:
A next step 58 involves estimating or accounting for an effect of entropy on the cycle time of the conveying system 14 to produce the future cycle time estimate for the conveying system 14. Step 58 may perform a stochastic simulation step 60 which uses historical cycle time data to simulate the cycle time of the system in a way that takes into account the random or stochastic variations in the historical cycle time data. Step 58 may be performed at least in part by the cycle time and variance module 48 in conjunction with stochastic simulator 40.
Similar statements are made in relation to the material processing time on page 7:
A next step 62 of method 54 involves estimating an effect of entropy on the material processing time to produce a future material processing time estimate for the material processing system 26. Step 62 may perform a stochastic simulation step 64 to account for the effect of entropy on the particular material processing system 26. Step 62 may be performed at least in part by the processing system performance module 50 in conjunction with stochastic simulator 40.
I do not understand how steps 58/60 and 62/64 could possibly be distinct. As just noted, ”variations resulting from entropy… ripple through…”. I consider that these ‘steps’ can only be read as items that the system accounts for, not literally actions taken in sequence.
Although it is awkward, I am comfortable with this understanding. The specification should not be read overly literally in relation to entropy being calculated or the ordering of steps.
The specification also states that the system is provided with historical data which measures cycle times and material processing times. These measured times are apparently improved by estimating the effect of entropy. Given these are measurements from a live system, it is not readily apparent how the measurements could be anything but all inclusive. What is it that a simulation includes that a measurement from a live site cannot?
This issue is highlighted in FIG.9a which I have reproduced below:
FIG. 9a indicates that the idle time averaged approximately 3.8 minutes at an actual site. However, the simulation predicts the idle time to be around 4 minutes. This discrepancy presents a challenge as the specification appears to suggest that data from real operations is less reliable for predictive purposes that the proposed simulation. I conclude that the simulation apparently accounts for a kind of entropy that is not adequately captured in operational data.
Historical data is plainly measured at real sites with a specific number of resources, say X haul trucks and Y crushers. It appears that the simulation is being used to determine what will happen when there are X + n haul trucks and Y + m crushers. In this sense, accounting for entropy seems be a reference to the fact that variability or randomness on a mine site is tied to dynamic operations. Previous data for equipment cycle times could be inaccurate when the amount of equipment changes and this seems to be what FIG.9a shows, that truck idle time will increase in the situation being modelled by comparison to the historical data.
Returning now to the stochastic simulator, notably, the Applicant overtly stated that the details of how to implement such a Monte Carlo simulator are well-known and do not require discussion. See the following on page 14:
However, because Monte Carlo simulators are well-known in the art and could be readily provided by persons having ordinary skill in the art after having become familiar with the teachings provided herein, the particular Monte Carlo simulator that may comprise stochastic simulator 40 will not be described in further detail herein.
Moving on to other terminology, the specification discusses production constraints and provides several examples including shift changes and blasting operations. These seem to represent a plain meaning of constraint, which is a confinement or restriction.
Cycle time, material processing time, and delay estimates seem to have plain meanings. Delay estimates have been defined by the Delay Hazard Function Module which is shown in equation form on page 17 of the specification as:
P(t1,t2) ≡ h(t2)Δt
In this equation the specification notes that “P is the probability of a delay occurring between times t1 and t2 given no current delays”. This is consistent with my understanding of probability density functions.
I have no further difficulties with any of this terminology.
Claims
The application contains 25 claims with 1, 7, 13, and 25 being independent. Claims 1 and 25 are directed toward a system whereas claims 7 and 13 are directed toward a method. I will initially focus on claim 1 which reads as follows:
1. A system for deploying equipment for mining operations, comprising:
a plurality of material loading systems comprising one or more shovels;
a plurality of material conveying systems comprising one or more haul trucks;
a plurality of material processing systems comprising one or more ore crushers, stockpiles and/or extraction systems;
a production constraint module, said production constraint module generating at least one of a process delay time and a planned downtime for at least one of the plurality of material loading systems and at least one of the plurality of material processing systems;
a stochastic simulator;
a cycle time and variance module operatively associated with said stochastic simulator, said cycle time and variance module providing historical cycle time data to said stochastic simulator, said stochastic simulator using the historical cycle time data to estimate an effect of entropy on a cycle time of the at least one of the plurality of material conveying systems, said cycle time and variance module producing a future cycle time estimate for the at least one of the plurality of material conveying systems based on the estimated effect of entropy on the cycle time;
a processing system performance module operatively associated with said stochastic simulator, said processing system performance module providing historical material processing time data to said stochastic simulator, said stochastic simulator using the historical material processing time data to estimate an effect of entropy on a material processing time of the at least one of the plurality of material processing systems, said processing system performance module producing a future material processing time estimate for the at least one of the plurality of material processing systems based on the estimated effect of entropy on the material processing time;
a delay hazard function module operatively associated with said stochastic simulator, said delay hazard function module predicting whether a delay will occur during the operation of at least one of the plurality of material loading, conveying, and processing systems and estimating a duration of the predicted delay, said delay hazard function module:
defining a probability density based on historical delay data associated with the at least one of the plurality of material loading, conveying, and processing systems;
applying the probability density to a Hazard Function to predict whether a delay will occur in the at least one of the plurality of material loading, conveying, and processing systems;
if a delay is predicted to occur, then providing the historical delay data to said stochastic simulator, said stochastic simulator using the historical delay data to estimate a duration of the predicted delay in the at least one of the plurality of material loading, conveying, and processing systems;
a processing system operatively associated with said production constraint module, said cycle time and variance module, said processing system performance module and said delay hazard function module, said processing system determining a loading system capacity and a conveying system capacity required to meet a defined production target for the material processing system based on at least one of the process delay time and the planned downtime generated by said production constraint module, the future cycle time estimate produced by said cycle time and variance module, the future material processing time estimate produced by said processing system performance module, and the delay duration estimate produced by the delay hazard function module; and
an equipment deployment system operatively associated with said processing system, said equipment deployment system deploying one or more of the plurality of material loading systems to meet the determined loading system capacity and one or more of the plurality of material conveying systems to meet the conveying system capacity.
Claim 1 essentially mimics what is shown in FIG.3. Similarly to the specification, no order is implied to the systems or modules which are claimed.
The claim is directed toward a system for deploying equipment for mining. The Macquarie dictionary defines ‘deploy’ in military terms which is clearly not appropriate in the present context. A more general definition from the Meriam-Webster dictionary which I consider to be appropriate is:
to put something into use
With this definition, the claim defines a system which puts equipment for mining to use. I note that this is subtly different to the invention which has been described, which as I noted earlier is directed to providing a rapid and accurate estimate of equipment capacity required to meet a set production target in a mining operation.
The claim follows by setting out the types of equipment involved. Note that these pieces of equipment are claimed to be a part of the system, not simply a list of equipment which the system models.
The claim then sets out constraints, cycle times, and material processing times which are being modelled. These are plain and do not require discussion.
The claim then defines a stochastic simulator, initially in name only. I consider that the term ‘stochastic simulator’ has a technical meaning to the person skilled in the art, with an appropriate explanation from Wikipedia being as follows:
A stochastic simulation is a simulation of a system that has variables that can change stochastically (randomly) with individual probabilities
The stochastic simulator is later defined to estimate the effect of entropy on cycle/processing times and the length of delays, without further definition as to what that entails. I conclude that it uses random variables to estimate the effect of entropy. Similarly to the specification, I consider that this means accounting for entropy rather than calculating it.
A cycle time and variance module, processing system performance module, and delay hazard function module are defined to provide historical data to the stochastic simulator. After the stochastic simulator has estimated an effect of entropy, the relevant module produces an estimate of future cycle time, material processing time, and delay duration. The claim does not define how, or on what basis this estimate is made.
The claim then set out that a processing system determines the loading system and conveying system capacity which is required to meet a defined production target based on the future cycle/processing times and the length of delays which have been calculated. With that, the claim specifies that equipment required to meet that capacity is deployed.
Claim interpretation
There are several issues which confuse me at this point:
·I am unclear on how the modules generate future times using entropy which has been accounted for but not specifically calculated.
·I am also unclear on how the system calculates future cycle time, processing time, and delay durations independently given that they are interrelated and changes to one will impact the others. Repeating the content from page 9 again “variations resulting from entropy in one element, system, or process will ripple though the material processing system, potentially affecting the other elements, system, and processes as well”
From reading the specification, I understand how the claimed invention is intended to operate. Rather than persist with what could be a futile attempt to construe the claim, I will instead interpret the claim consistent with my understanding of the invention such that I can decide the present matter.
I have no issue with the preamble, equipment, production constraint module, and equipment deployment systems and will continue to construe them as written and noted above.
I understand that the stochastic simulator, cycle time and variance module, processing system performance module, delay hazard function module, and processing system are all aspects of a simulator which must:
·Use historical cycle time, material processing time, and delay data.
·Employ random sampling in the adoption of cycle times, material processing times, and delay durations.
·Use a probability density function and a hazard function to model failure.
·Output a loading system capacity and a conveying system capacity which is required to meet a defined production target.
While more could be inferred from the specification and assumed to be part of claim 1, I consider that any further assumptions about the claim are not necessary for me to decide the present matter. For example, the claim does not define:
·The modelling of X + n haul trucks or Y + m crushers as discussed earlier.
·Repeated random sampling as would typically be used in the Monte Carlo method.
·Modelling of roads, bottlenecks, or dynamic operations of any kind beyond failure.
·Repetition such that a series of equipment arrangements are modelled.
Similar issues exist with all independent claims. I do not consider that further construction of those claims will yield a different outcome and so will proceed with my current understanding of claim 1 noting that the claims are sufficiently similar that any decision I make in relation to claim 1 will apply equally to all claims.
The Examiner’s objection – Manner of Manufacture
A single objection item number 4 remains outstanding from examination report number 4 which can be summarised as follows:
The Applicant's submissions have been fully considered but are not found persuasive. I maintain that the claimed invention, as a matter of substance, is a scheme for deploying equipment or material loading systems in a material processing system according to loading and conveying system capacities to meet defined production targets, and that this is not a manner of manufacture in the meaning of Section 18(1)(a) of the Patents Act.
This is followed by a rebuttal of the Applicant’s submissions which I have not repeated.
The Applicant’s submissions – Manner of Manufacture
The Applicant has submitted that the substance of the present invention lies outside a computer in the deploying of an optimal number of resources. The key point seems to be that National Research Development Corporation v Commissioner of Patents [1959] 102 CLR 252; [1961] RPC 134 (“NRDC”) and Grant v Commissioner of Patents [2006] FCAFC 120 (“Grant”) are more relevant to the present case than later caselaw such as Research Affiliates LLC v Commissioner of Patents [2014] FCAFC 150 (“Research Affiliates”) or Commissioner of Patents v RPL Central Pty Ltd [2015] FCAFC 177 (“RPL”). The submission is concluded with:
The present invention results in an artificially created state of affairs (i.e. a “useful product” as meant in Grant), in the sense that a material effect (as detailed within the specification) is realised - efficient and optimized use of shovels and haul trucks, thereby preventing accumulation of ore due to lack of available shovels or haul trucks/shovels standing idle due to an excessive number of available haul trucks/shovels. This is analogous to the invention in NRDC where the material effect was observed in fewer weeds. This is a material effect achieved outside of the computer.
The significance of the invention corresponds to a ‘remarkable advantage’ in that the operating costs / inefficiencies associated with one or more haul trucks or shovels standing idle for extended periods is minimised while still meeting the required production target. This advantage is realised by deploying the material loading systems and the material conveying systems by the equipment deployment system so as to meet the loading or conveying system capacity, which are configured to meet the production target.
This is followed by further submissions directed toward Bio-rad Laboratories, Inc. [2018] APO 24 (“Bio-rad”) which has been discussed in examination reports. The submissions address the level of detail in relation to calculations which are made and concludes with:
The Applicant respectfully submits that the patent-eligibility of the present application cannot be predicated on the lack of “concrete mathematical details for formulae” in instances where systems have “variables that change stochastically or randomly with individual probabilities” (page 14, lines 4-5). Stated somewhat differently, the fact that the systems being modelled by the claimed invention are not analytically tractable cannot be used to say they are not patent eligible.
The Applicant finishes by reiterating what they consider to be the substance of the invention which can be summarised with:
…As noted above, the ‘material effect’ of the claimed invention is achieved outside of the computer, with the substance of the invention relating to optimal deployment of mining equipment to meet production targets, such that idle time for each equipment or possibility of lack of sufficient equipment when required is minimized.
Legal principles – Manner of Manufacture
Section 18(1)(a) of the Patents Act 1990 states:
(1) Subject to subsection (2), an invention is a patentable invention for the purposes of a standard patent if the invention, so far as claimed in any claim:
(a)is a manner of manufacture within the meaning of section 6 of the Statute of Monopolies;
The broad principles to consider regarding manner of manufacture have been set out in National Research Development Corporation v Commissioner of Patents [1959] HCA 67 (‘NRDC’). At [14]:
The right question is: “Is this a proper subject of letters patent according to the principles which have been developed for the application of s. 6 of the Statute of Monopolies?”
Further guidance was provided in D'Arcy v Myriad Genetics Inc [2015] HCA 35 (‘Myriad’) to look for the substance of the invention. This is reflected in [87] and [88] by the majority and repeated by the minority at [144] quite succinctly:
Whatever words have been used, the matter must be looked at as one of substance and effect must be given to the true nature of the claim.
Aristocrat Technologies Australia Pty Limited [2016] APO 49 (Aristocrat ‘16) summarised considerations appearing in Research Affiliates, and RPL at [35] which are relevant to assessing whether a computer-implemented invention, is in substance, a manner of manufacture as follows:
I conclude that it is relevant to consider a range of matters. Without seeking to be exhaustive, these include:
othere must be more than an abstract idea, mere scheme or mere intellectual information;
ois the contribution of the claimed invention technical in nature;
odoes the invention solve a technical problem within the computer or outside the computer;
odoes the invention result in improvement in the functioning of the computer, irrespective of the data being processed;
odoes the application of the method produce a practical and useful result;
ocan it be broadly described as an improvement in computer technology;
odoes the method merely require generic computer implementation;
ois the computer merely an intermediary or tool for performing the method while adding nothing of substance to the idea;
ois there ingenuity in the way in which the computer is utilised;
odoes the invention involve steps that are foreign to the normal use of computers; and
odoes the invention lie in the generation, presentation or arrangement of intellectual information.
I note that later Full Court decisions including Encompass Corporation Pty Ltd v InfoTrack Pty Ltd [2019] FCAFC 161 (‘Encompass’), and Repipe Pty Ltd v Commissioner of Patents [2021] FCAFC 223 (‘Repipe’) have not diverted from this approach in any meaningful way.
Aristocrat Technologies Australia Pty Ltd v Commissioner of Patents [2022] HCA 29 (17 August 2022) (‘Aristocrat ‘22’) left previous Full Court decisions in relation to manner of manufacture undisturbed.
Considerations
The Applicant has focussed on NRDC and Grant in submitting that the present invention is for a manner of manufacture. Later caselaw has been discussed such as Research Affiliates and RPL along with a suggestion that these are primarily relevant to computer implemented inventions, whereas the present invention lies outside a computer.
I think this misrepresents the teaching of recent caselaw which is essentially a refinement of the words in Myriad “Whatever words have been used, the matter must be looked at as one of substance and effect must be given to the true nature of the claim.”
Computer implemented inventions are not a special category of invention for which manner of manufacture law is different. This has been acknowledged by the High Court across both sets of reasons in Aristocrat ’22 with the following from [77]:
…It is not apparent in the present case that asking whether the claimed invention is an advance in computer technology as opposed to gaming technology, or indeed is any advance in technology at all, is either necessary or helpful in addressing that issue…
And the following from [152]:
The question of whether a claim, as properly characterised, is the proper subject matter of a patent should not be deconstructed to require, separately from the general principles of patentability, consideration of whether the subject matter is "computer‑implemented"…
Decisions such as Research Affiliates, RPL, and Aristocrat ’16 seek to identify the substance of the invention and whether that is patentable. I consider that those principles are relevant to all inventions but need to be applied appropriately for the matter at hand.
Note the following comments which the Applicant made in submissions:
The significance of the invention corresponds to a ‘remarkable advantage’ in that the operating costs / inefficiencies associated with one or more haul trucks or shovels standing idle for extended periods is minimised while still meeting the required production target. This advantage is realised by deploying the material loading systems and the material conveying systems by the equipment deployment system so as to meet the loading or conveying system capacity, which are configured to meet the production target.
Therefore, the Applicant submits that the substance of the claimed invention satisfies the requirements for a manner of manufacture.
There is a leap here from the system being configured to meet production targets to the substance of the invention being for a manner of manufacture without addressing what the substance of the invention is.
I will now use the established approaches to determine what the substance of the invention is and whether the application is for a manner of manufacture or not. Note that I have not considered any question of whether the present invention solves a problem within a computer or not. Whilst the invention is computerised, the substance of the invention does not lie in that computerisation and noting the Applicant’s submissions this point does not appear to be disputed.
There must be more than an abstract idea, mere scheme or mere intellectual information.
The invention improves mining operations by identifying the optimal set of equipment to use so that actual capacity matches planned capacity. It uses a stochastic simulator to model random events and account for variability, which is referred to as entropy. I will note here that equipment capacity is complex. For example, whilst the amount of material a haul truck can hold is well known, the amount of material it can move from one place to another is impacted by how quickly it can move, idle time, and delays for example, each of which vary stochastically.
The specification promises to provide a rapid and accurate estimate of the equipment that is required in a mining operation based on these more accurate estimates of capacity.
As claimed, the invention defines a simulation being used to estimate various aspects of a proposed mining operation and calculate loading and conveying system capacities required to meet a production target, with the calculated set of equipment being deployed.
The claimed invention is about using a specific approach to simulation which improves the forecasting of mine equipment operations. As a result of the calculation, a tangible amount of equipment will be deployed into operation. That same equipment will be capable of extracting a volume of material which can later be measured directly.
This is not simply a plan or concept which exists in theory. The invention relates to the identification of a particular amount of equipment which is going to be deployed in order to achieve a set production target. The output of that equipment will depart from reality in a tangible, measurable way. To use the words of Grant:
It is necessary that there be some "useful product", some physical phenomenon or effect resulting from the working of a method for it to be properly the subject of letters patent.
That physical effect is that actual mine output will match calculated output more closely and thus a system can be arranged which will output the planned production target.
Another way to view the invention is that it is a scheme to improve mining operations by simulating forecasting outputs instead of using trial and error. In this way there is nothing physical and tangible, merely an idea about the optimal way to conduct a mining operation.
These alternatives differ in substance. Is the invention just the idea of using simulation, or a specific, more accurate simulation? The specification highlights how existing methods fail to account for entropy (variability) suggesting that in substance, the invention is a more accurate simulation. Noting that the quantity being estimated (e.g., how much material a given set of equipment can extract) is real and measurable, I consider that in substance, the present invention is more than an abstract idea or intellectual information. Whether it is a scheme will come down to its technicality which I will address next.
Is the contribution of the claimed invention technical in nature?
One could argue that stochastic simulation itself is technical. It involves mathematics and the calculation of an objective result which does not have aesthetic appeal or belong to the creative arts. This presents positively. However, stochastic simulation is plainly not the Applicant’s contribution. I will address this point soon with extensive prior art demonstrating that stochastic simulation is well known.
A closer review of the simulation is needed which is where I encounter a problem; the claims lack detail on what is and how it is simulated. The claims define cycle time, processing time, and delay durations, but only define that a random variable uses historical data to predict future values. This basically defines an experienced guess which I couldn’t reasonably call technical. In truth the invention isn’t directed toward guessing, but that has not yet been set out in the claims. At present the claims define using a broadly defined mathematical algorithm to calculate what equipment is considered optimal to meet a production target.
Beyond using a stochastic simulator there is practically no information about what is being modelled. I find this troublesome because it seems that any technicality to the present invention lies in the modelling, which is missing. For example, I would assume that road networks, queues, weather conditions, and the like would all be modelled in a sophisticated simulation of a mining operation. However, nothing of that kind is mentioned. Where the specification addresses that “haul trucks will tend to periodically 'bunch up’,” which undoubtedly relates to road design among other things, nothing has been discussed.
I cannot be satisfied that the claimed invention provides a technical contribution. While the claims do not define anything overtly non-technical, neither do they define a contribution which is technical.
I conclude that there is not presently a contribution which is technical in nature.
Does the application of the method produce a practical and useful result?
There is clearly a useful and practical result, an electronic forecasting solution which provides for rapid and accurate estimate of what pieces of equipment should be used in a mining operation to enable the meeting of a production target. This presents positively.
Summary
As the Applicant has submitted, there is no doubt that the substance of the present invention lies outside a computer. There is no suggestion that the Applicant has invented a new computer or ability to process information. Instead, the Applicant has suggested a focus on the concrete, tangible effect of the calculation and deployment of equipment.
In substance the invention is not directed to merely deploying equipment but instead to a rapid and accurate estimate of the correct amount of equipment. I will emphasise that in this context, correct is the amount of equipment which can deliver a specific amount of extracted material rather than the amount which optimises profit, customer satisfaction, appeal or any other similarly abstract concept.
However, it is not clear what is being modelled. Despite extensive discussion of stochastic simulation, it is not clear how the invention uses random variables. This is true of both the claimed invention and the specification. Where I have looked for information about how the stochastic simulator works, all I have found is a statement that the person skilled in the art could have implemented it.
As it stands, while the invention is not purely abstract and does provide an invention that is useful, this alone is not enough to provide for patentability. There could be aspects of the stochastic simulation which are technical, but at the level it is presented, this is plainly not the Applicant’s contribution. Beyond this, I have not been able to find any material which provides patentable subject matter and so as a matter of substance, I am not satisfied that the present invention is patentable.
Other matters: inventive step
Before finalising the present matter, having reviewed prior art to understand the field of stochastic simulation I have concerns that claimed invention may not be inventive. Noting that the Applicant has not had a chance to respond to the prior art I have seen, I consider that the best course of action is for the application to return for further examination of these potential issues.
I offer the following observations about prior art which can be considered and raised by the examination section if appropriate:
D3: Askari-Nasab, Hooman (2013), Mining Optimization Laboratory (MOL) – Report Five, © MOL, University of Alberta, Edmonton, Canada, Pages 230, ISBN: 978-1-55195-327-4, pp. 123-136.
D4: Applications of Queuing Theory for Open-Pit Truck/Shovel Haulage Systems [Viewed on internet on 8 May 2025] <URL: Published on 19 December 2012
D5: Dilip Sembakutti, “Analysing equipment allocation through queuing theory and Monte-Carlo simulations in surface mining operations”, Int. J. Mining and Mineral Engineering, Vol. 8, No. 1, 2017
D6: Dumakor-Dupey, N. K., Temeng, V. A. and Bansah, K. J. (2017), “Optimising Shovel-Truck Fuel Consumption using Stochastic Simulation”, Ghana Mining Journal, Vol. 17, No. 2, pp. 39 – 49
It appears that D3 is directed toward the efficient use of loading and hauling fleet in open pit mines. It seems to disclose modelling material loading, conveying and processing systems (“In the simulation model, trucks, shovels, waste dumps, stockpiles, and crushers are modeled as resources of the truck-and-shovel operations.” page 107-4), constraint modelling (“This means that the mine employs 3 shovels and 11 trucks during the year, but in odd months it does not use one of the trucks because of scheduled maintenance.” page 107-7), stochastic simulation, accounting for entropy, and historical data “The simulation model deals with the uncertainties associated with the operations of trucks and shovels. Each stochastic variable is represented with a probability density function. Most of the probability density functions are obtained by performing data analysis on historical dispatching data gathered from a Jigsaw dispatching database.” (page 107-5), and delay hazards (Table 2 see stochastic variables, probability density functions and failure modes).
D3 does not appear to explicitly teach the use of a hazard function, however, that seems to be inherent in the disclosure of using a probability density function to model failure, and in any case may be well known. I note that Survival Functions are discussed in a Wikipedia article titled the same.
D4, D5, and D6 provide similar disclosure of stochastic simulation usage in the modelling of mining operations. Each varies in relation to the aspect of operations which are being modelled, how the model is setup, and the factors which are incorporated.
Conclusion
For the above reasons I find that claim 1 is not for a manner of manufacture. While I have not formally addressed other claims, they do not add material which would overcome this issue.
While it is not clear to me what form an amendment might take to provide patentability, I remit the application for further examination. Noting that I have also discussed inventive step, I consider it appropriate to invoke Regulation 13.4(3) and provide the Applicant 6 (six) months from the date of this decision to bring the application in order for acceptance.
Tim Gillett
Delegate of the Commissioner of Patents
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