System and methods for controlling any operation, such as grinding and flotation, and their equipment

Abstract

The present invention relates to a method and system for controlling and optimising an industrial or civil engineering works operation involving: the process, the product, a device, works, a complementary device (or peripherals), a component, and / or operational components. The invention is based on at least one of multiple possible parameters, in an automated (or semi-automated), smart, reliable and verifiable manner throughout the entire operational chain. The system includes: devices, computer vision, sensors and actuators; databases containing a pattern acquired in the operation, a standard pattern to be achieved, quality control and historical 3D models; software, a digital twin, a cloud, artificial intelligence and / or a remote control.

Description

[0001] SYSTEM AND METHODS TO CONTROL ANY OPERATION WITH ITS EQUIPMENT, SUCH AS: GRINDING AND FLOTATION.

[0002] DESCRIPTIVE MEMORANDUM.

[0003] This patent application discloses a system for controlling and optimizing an operation on land, in the air, on liquid and under liquid, involving a: process, a product, equipment, a work, complementary (or peripheral) equipment, components thereof or operational components; based on one, several or a combination of multiple possible quality parameters, pattern, in a corrective, preventive, predictive and / or prescriptive manner, in an automated, intelligent and reliable way.

[0004] To optimize a mining operation, it's necessary to align operational efforts with the business's strategic objectives. Operational performance is directly linked to the inspection and quality control of production assets and the products themselves. The business depends on the performance of equipment, infrastructure, ancillary (or peripheral) equipment, components, and operational components, based on a series of operational quality parameters. The success of a mineral extraction operation depends on its transaction value on the stock exchange and the efficiency of its infrastructure and equipment in extracting a specific mineral. This value typically fluctuates due to various factors external to the operation, requiring the operation to take the most efficient actions and restructure its approach accordingly.In a generic example, if a Cu and Mo operation initially recovers more Cu, it may need to recover more Mo in the future. To achieve this, it will have to rethink and optimize its infrastructure and equipment, controlling the series of quality controls and said equipment to achieve the strategic objective. It will need to control the quality of the ore in flotation, mobilize the drilling equipment at the face, and project the various scenarios for part and / or all of the operational chain of infrastructure and equipment until it finds the operation with the highest return on investment.

[0005] Quality control involves comparing products to a standard, evaluating defects in relation to the process chain, and then controlling the variable to improve the process. In mining, downtime of static and rotating equipment in the grinding and flotation areas affects the upstream and downstream process chain, directly impacting the productivity of the mining operation and the cost per ton of ore processed. In grinding, the SAG (semi-autogenous) and / or ball mills, and especially their liners, are highly critical; in a vertical mill, the worm gear and its liners are critical; in flotation, the impeller is critical in the flotation cells, and the rake is critical in a thickener.Even more important than its components are the process and the effects it seeks to achieve to optimize the process: in the SAG and / or ball mill it is comminution, in the vertical mill it is the agitation of grinding balls and slurry, in a flotation cell it is the quality of froth and bubbles to recover a certain mineral, and in a thickener it is the recovery of water and concentration of solids at the bottom, and all of which depend on the control of the components and variables of the operational components of each particular process, where the components in a mineral grinding mill are the mill linings and the operational components are the process water.

[0006] To optimize operational continuity and the performance of a process and / or project, it is necessary to control the quality of the equipment, the work itself, and the process. Maintaining dimensional control of the thickness of a lifter in a SAG and / or ball mill liner is as important as the amount of fresh water required for proper equipment operation to optimize the process; even more crucial is the original design particle size distribution of the process.Wear and tear on SAG and / or ball mill liners necessitates shutting down the mill for replacement until the next production run. This run is typically projected to last several months, but due to the actual hardness of the feed material at the grinding face, the original plan becomes unrealistic. Therefore, one method for ensuring operational continuity and minimizing the impact on the resulting product, which is of lower quality than when the SAG and / or ball mill liners are new, is to vary the speed of the drive unit. This allows the worn lifting angle of the hoist to lift the ore and grinding media, achieving better comminution with the available resources, resulting in a better product and thus a more profitable operation.

[0007] The equipment and / or a work can be any type of equipment for operation: concentric or eccentric rotary, static, mobile and / or that carries out a process, can be in operation or stopped, motorized and non-motorized, open, semi-closed and / or closed, which can be independent or several linked in a series of a part or complete of a process line or production line, such as: an industrial work, a process equipment, the process and its components;equipment, any equipment: equipment, machine, device, vehicle, autonomous vehicle, robot, robotic cell, device, not limited to: a horizontal mill, a vertical mill, a reactor, a flotation cell, a column cell, a Jameson cell, a flotation battery, a centrifugal pump, a haul truck, a wheel excavator, an electric or hydraulic shovel, a hydrocyclone battery, a crusher, a conveyor belt or apron feeder, an agitator or mixer, a grinding or regrinding mill circuit, a gas scrubber, a dust filter, sedimentation equipment: thickener, clarifier or settling tank;Complementary (or peripheral) equipment, such as: an actuator, a vehicle, a crane, a drone, a robotic arm, a robot and / or cobot for manipulation, probing, a specific predefined or multitasking task, a transfer, feeding or unloading chute, a structural work and any component thereof.;

[0008] The multiple possible quality parameters in a construction operation and its process can be: dimensional, physical, mechanical, chemical, biological, structural, functional, operational, and financial, such as: a KPI (Key Performance Indicator), NPV (Net Present Value), EBITDA (Earnings Before Interest, Taxes, Depreciation and Amortization), ICF (Instant Cash Flow), ROI (Return on Investment), mineralogy, concentrate grade, ore hardness, RPM (Revolutions Per Minute), comminution cascade, mill liner lifter angle of attack, liner thickness, dimensions, and surface finish.Dry film thickness, hardness, wear level on a steel component, weld inspection using ultrasonic and radiographic methods, determining the alkalinity of a liquid, determining the chemical composition of solids, liquids, slurries, and powders. The following are a series of examples that illustrate, but are not intended to limit, the purpose of this request:

[0009] An operator checks inside a mill that a liner is wearing down. Upon verifying that a certain amount has been used, they determine that the angle of attack of the liner changes the cascade and cataract effect. To achieve a beneficial effect on the process, they will adjust the variable speed drive of the drive unit so that, despite the wear, appropriate comminution is achieved. Then, a programmed shutdown of the process equipment will be performed. If an operator checks the flocculant density in the froth of a flotation cell is not adequate, they will activate a valve to increase the flocculant flow rate. If the thickness of the flotation cell liner is deteriorated to the point that the internal structure is visible, an experienced operator will determine that there is a significant loss in froth formation, and the recovery of the target mineral will not be adequate.If a quality control technician checks parameters in a RAS (Recirculating Aquaculture System) tank and the oxygen level drops and the pH exceeds the established range, they must notify the system operator. The operator will then notify another operator in the oxygenation, ozone, and nitrification area so that the levels can be adjusted according to pre-established parameters based on the operating biomass. This will activate a valve upstream of the tank. If the camber deviation of a pre-assembled structure is outside of standard specifications, a series of actions must be taken in the activity schedule. An administrator will then be responsible for implementing the necessary measures to improve the current state of the structure.If the surface quality and tolerance of a large aircraft component do not meet specifications, an operator will notify the technical manager of the deviation. The technical manager will then develop a new work plan and inform the operator on the previous line of the production chain. Operational problems affect the operation's financial profitability.

[0010] Quality aspects are multiple, they can be geometric (change in thickness in a component, etc.), mechanical (welded joints and thickness in a metallic or polymer component, etc.), as well as physicochemical (the electrochemical potential Eh, pH or conductivity, in a cellulose or mineral process) and have direct effects on the processes of a work, both to carry out quality controls, raise parameters or control an operational variable; these can optimize or harm an operation.

[0011] Controlling an operational variable, thereby establishing parameters and performing quality controls, depends on mitigating errors in human actions. In all the previous cases, to control an operational variable in the project or process, the process equipment must typically be shut down, and other equipment must be opened, which is very costly for the operation. Furthermore, the deployment of personnel requires safety protocols and training to prevent fatal accidents due to inherent risks, which is also costly for the operation.

[0012] Currently, to control an operational variable, quality controls must be carried out, parameters must be set and then an operational variable of a work or process must be controlled, which are done in isolation, and it involves technical deployment, complexity and operational skill, being a challenge for the operators of an operation.

[0013] Given the above difficulties, it is desirable to have a distributed system that allows controlling an operation along with controlling the quality of one or multiple parameters, such as: metrological, mechanical and physicochemical, operational and financial; and that intelligently evaluates the process and the work, to control an operational variable and control a piece of equipment from its components and deviations in such a way as to control them, optimize the process and make the operation profitable.

[0014] The disclosed system resolves the quality control of multiple parameters and the intelligent control of the operational variables of a work or process, in open, closed, semi-closed or open field, mobile, semi-mobile, static or rotating, by means of: vehicles, equipment and devices, to collect multiple parameters and samples of the environment, and that feed databases that are analyzed by software, and that the entire chain of operations are improved by a digital twin (simulation and emulation), artificial intelligence and / or Blockchain.

[0015] The field of application of the invention therefore pertains to the overall control and quality control of an operation, including its equipment, process, and product, whether it be a piece of equipment, a structure, complementary equipment (or peripherals), a component, or an operational component. It can also be applied for instructional and educational purposes, such as for induction training for internal or external personnel involved in an operation.

[0016] The system of the invention and its methods can be used to ensure the resumption of operations, operational reliability, operational continuity, and to control an operation involving a process, a product, equipment, a work, complementary (or peripheral) equipment, components thereof, or operational components; in a corrective, preventive, predictive, and / or prescriptive manner, throughout the operation: pre-assembly, assembly, pre-commissioning, commissioning, start-up, no-load testing, initial load testing, and in the case of mining operations: during plant start-up and shutdown or a campaign, normal start-up, and after an emergency shutdown.In a non-limiting example, such an advantage is the invention that reduces downtime, reduces ramp-up, optimizes operational continuity, increases throughput, minimizes downtime, maximizes productivity, maximizes ROI (Return on Investment), maximizes the performance and mass and energy balance of processes, and in mining and cement operations achieves an increase in TPH (Tons per hour) of ore.

[0017] The invention and methods can be used in factories and industrial processes, general industry, construction and buildings; mining operations, such as open-pit and underground mines, and concentrator plants; production lines, such as automotive, aerospace, aeronautical, naval, robotics, food, agricultural, forestry, pharmaceutical, and military; industrial process plants, such as metallurgical, mining and cement, petroleum, gas, nuclear, chemical, and pulp and paper; aquaculture, such as offshore fish farming and RAS; and recycling, water treatment, industrial liquid waste (ILW) or solid waste treatment; it can also be used in induction, instruction, and education, both on and off the job site. It can encompass the disciplines of control engineering, mechanical, structural, civil, metallurgical, hydraulic, biological, chemical, nanotechnology, electronics, robotics, electrical, automation, communication, and power engineering.BACKGROUND OF THE INVENTION - STATE OF THE ART.

[0018] Currently, the state of the art for performing component control in a piece of equipment and / or work, in one case, is done by sending a team of people to the work site and to perform quality control, in one case, it is done by sending another specialized team of people to the work site, and on the other hand, another team analyzes the data and the operational and financial impact for the operation, then, with the results, another team will activate a component in the operation.

[0019] For example, to collect a point cloud in the grinding area of ​​a mining plant and determine the wear thickness of the SAG and / or ball mill liners, the rotating equipment must first be stopped. The SAG and / or ball mill is then opened, and a specialized team deploys a 3D laser scanner, such as a FARO, which is deployed by an operator. After a period of exposure to capture the internal 3D geometry, the equipment is retracted and the operator leaves the work site. The grinding area manager then restarts the operation of the SAG and / or ball mill. This point cloud is processed by software and imported into a program like Geomagic Design X, where it is further processed to obtain longitudinal and transverse 2D sections of the SAG and / or ball mill. Finally, Geomagic Control X software is used to generate a wear map.The area representing wear on the liner is selected manually. In a parallel stage, a team of professionals uses Altair EDEM software to simulate the operation, including simulating and optimizing the RPM and fill level of the SAG and / or ball mill. Subsequently, Tavares software is used to model the crushing process. EDEMpy is then used to quantify the mill's return flow and analyze particle collision energies. Finally, Python is used for post-processing and analysis of the EDEM data to quantify the particles entering and leaving the SAG and / or ball mill. In a later stage, after defining the lifter geometry, a team of professionals and technicians develops an action plan to utilize the worn profile of the liners according to the desired comminution effect and its impact on upstream and downstream processes.In another stage, the data and the operational and financial impact of the equipment and product on the operation were analyzed. Then, at the operating site, professionals and technicians perform corrective actions on valves and drive units of the equipment, such as opening or closing a valve and supplying a specific flow rate, or varying the RPM of an engine. These are isolated tasks, lacking coordination between: data collection, databases, 3D modeling, analysis to improve the equipment and / or the process and / or one of its components, and their operation.

[0020] Based on the above, it is desirable that the equipment be integrated, autonomous, and intelligent, including a remote control mode, and that the operations manager be able to approve or reject a given action based on optimal quality control and the expected effect. It is also desirable that what occurs in reality be reflected in the 3D model; that there be an interface where the operator and specialists can immerse themselves in the 3D model; that there be integrated analytics to simplify the workflow and the iterations of effects and impacts on the equipment and the process chain; that there be multiphysics simulation to increase the fidelity of the design based on the input data and improve performance; that there be assistance that can learn from the design stages without needing to be programmed; and that there be reliability in each process and / or report executed throughout the entire operation control chain.

[0021] The closest prior art is invention patent W02017093608A1 “A method and arrangement for controlling a crushing process”, which describes; the present invention relates to the field of mineral and metallurgical processes, to comminution processing or disintegration in general and to comminution processing by means of crushers and rotary mills, and more particularly to a method and arrangement for controlling a crushing process.An arrangement for controlling a crushing process according to the present invention has a system for monitoring the flow of ore (11) before entering a grinding circuit (10), (19) of said crushing process, wherein said monitoring system of said control arrangement comprises an imaging system (12), (20), said imaging system (12), (20) measuring 3D reconstruction measurement data (21) for the reconstruction of a three-dimensional image profile (32) of said ore (11); wherein said control arrangement comprises a control block (27), (46) receiving calculated rock size distribution data (23) from said ore (11), said rock size distribution data (23) being calculated based on said measured 3D reconstruction measurement data.(21); and wherein said control block (27), (46) receives one or more distinct property values ​​for one or more rock size variables, said one or more distinct property values ​​being calculated based on said measured 3D reconstruction measurement data (21).

[0022] The invention patent, CN112742591A “Intelligent control system and method for a vertical agitator mill”, describes an intelligent control system and method for a vertical agitator mill related to the field of mining machinery, comprising a data acquisition system and an OPC (OLE for process control) DCS (Distributed Control System) server, wherein the acquisition system comprises the acquisition of feed flow, concentration, variable frequency motor rotation speed, motor current, power, pump pool liquid level, slurry pump frequency, cyclone feed pressure, cyclone feed concentration, cyclone feed flow, cyclone overflow concentration, and granularity parameters of the vertical agitator mill.Acquisition of online height detection information for steel balls in the vertical agitator mill and acquisition of online abrasion detection information for spiral liner plates; the acquired information is sent to the DCS OPC server on-site via a data acquisition terminal. The controller in the DCS OPC server adopts a fuzzy controller, and the output variables of the fuzzy controller are the quantity of steel balls added to the vertical agitator mill, the rotation speed of the motor, the amount of makeup water for the grinding ore, the amount of makeup water for the pump pool, and the frequency of the slurry pump. The invention avoids hysteresis and instability caused by manual adjustment and ensures that the mill operates more stably and saves energy.

[0023] The invention patent, CN116871015A, “Method and System for Optimizing Mineral Grinding Process Parameters,” describes a method and system for optimizing mineral grinding process parameters, applicable to the technical field of mineral processing. This method involves constructing an objective function for the wet grinding work index and optimizing the technological parameters of the objective function using an improved particle swarm optimization BP neural network algorithm. The goal is to obtain an optimization scheme for the technological parameters under the condition that the resulting wet grinding work index is the lowest possible. According to the invention, by establishing an optimized prediction model of the relationship between mineral grinding concentration, medium filling rate, ball ratio, sand return ratio, rod ratio, and grinding ball ratio,An optimal result is achieved, mill / ball mill, open / closed circuit mineral grinding, mill diameter, large ore feed particle size, ore grinding fineness, rod mill crushing ratio, ball mill crushing ratio and wet ore grinding work index. An improved particle swarm optimization BP neural network algorithm is adopted to perform wet ore grinding work index optimization. Intelligent optimization of technological parameters is carried out in the ore grinding process, and under the condition that the obtained wet ore grinding work index is the lowest, a scheme of optimization of the technological parameters of ore grinding is fed back to a mineral grinding system, improving the ore grinding effect and reducing the energy consumption of ore grinding.

[0024] The invention patent, DE102005036945A1, “Automatic dosing of additives in the fine grinding process by controlling the pressure in the grinding vessel,” describes an automatic dosing system for fine grinding processes that measures the pressure inside the grinding vessel and uses this value to regulate the dosage of additives. This reduces clumping effects and ensures a consistent degree of grinding. The additive can be added continuously or in discrete quantities.

[0025] Also some of the techniques mentioned above:

[0026] US7237735B2 “Angle-based method and device for protecting a rotating component.”

[0027] US10412275B2 “Apparatus for controlling the interior of the mill during operation.” WO2023044592A1 “System for controlling and coordinating a set of equipment.” However, no part of the prior art discloses the features disclosed below in this description.

[0028] The technical problem posed is to control and optimize an operation involving one, several, or a combination of equipment (502), a work (600), complementary equipment (or peripherals), a component (503) and / or an operational component (504), based on one, several, or a combination of possible multi-parameters of operational quality, a pattern (200), in a corrective, preventive, predictive, and / or prescriptive manner, until the desired effect is achieved in accordance with a standard pattern (250), such as: a quantitative property, a qualitative, operational, or financial property, a KPI (Key Performance Indicator), an NPV (Net Present Value), an EBITDA (Earnings Before Interest, Taxes, Depreciation, and Amortization).ICF (Instant Cash Flow), mineralogy, concentrate grade, ore hardness, RPM (Revolutions Per Minute), comminution cascade, angle of attack of a mill liner lifter, liner thickness; by controlling one, several, or a combination of the equipment (502), the work (600), the complementary (or peripheral) equipment, the components (503), and / or the operational components (504); said equipment (502) may be: concentric or eccentric rotary, static, mobile, semi-mobile, and / or carrying out a process, may be in operation or stopped, motorized and non-motorized, open, semi-closed, and / or closed, which may be independent, several linked together, or several alternated, in a series, in a part or complete of a process line or production line, such as: a horizontal mill, a vertical mill, a reactor,a flotation cell, a Reflux™ Flotation Cell (RFC™), a Reflux™ Concentrating Classifier (RCC™), a column cell, a Jameson cell, a flotation battery, a centrifugal pump, a hydrocyclone battery, a crusher, a conveyor belt or apron feeder, an agitator or mixer, a grinding or regrinding mill circuit, a gas scrubber, a dust filter, sedimentation equipment: thickener, clarifier or a settling tank; a work (600) such as: an industrial work, a production line, a mining operation, a concentrating plant, the process and its products; Complementary (or peripheral) equipment, such as: an actuator, a vehicle, a crane, a drone, a robotic arm, a robot and / or a cobot for manipulation, probing, a specific predefined or multitasking task, a transfer, feeding or unloading hopper,a structure and any one of these components; operational components (504), such as: particle size, density (of pulp), grinding media size, process media, such as grinding media (balls, rods), temperature, filling level, superficial gas velocity, peripheral agitation speed, feed and discharge flow of: the product, process material, clear water or process water, flocculant, etc.; and where the product may be any matter and its states or phases of aggregation: organic and inorganic matter, chemical compound, organic and inorganic, mineral, chemical element, rocks, pulp, sludge, organisms, living or dead beings, animals (including meat), vegetables, pharmaceuticals, food, fish, compounds, simple and compound substances, an electronic component, an electronic artifact, a device, a drone, a vehicle, a machine, a weapon, a ship, a robot, a housing; the operation may be: industrial, mining,Oil and gas, automotive, aerospace, naval, military, pharmaceutical, chemical, energy, robotics; and also applied for training, instructional, and educational purposes. In one non-limiting example, in the grinding area of ​​a mining plant, a SAG and / or ball mill, equipment collects at least one of multiple possible parameters, builds a database, which, together with a database of the process equipment and / or the structure, is processed by software that builds a digital twin (simulation and emulation). A multiphysics model then designs, redesigns, and / or creates, in a corrective, preventive, predictive, and / or prescriptive manner, various iterations that are finally reported to a control center where a remote control can take an action or variable and select and / or adjust an iteration. In one of many possible cases, the existing geometry of the lifting mechanism, which has already been worn down by comminution, is utilized.Where a quality control module establishes the deviation from the standard according to an integrated process quality standard module that establishes a standard pattern, in this case the wear condition is determined qualitatively and quantitatively, and coupled with another analysis module, iterations are performed where various ways to optimize processing according to said deviation are resolved. In one solution, of multiple possible solutions, the mill's RPM will be reduced to optimize the process. For this, the control module will activate one, several, or a combination of actuators to reduce the speed, so that feedback can be given back to the equipment that monitors at least one of multiple possible parameters, in such a way as to achieve the effect of optimizing the comminution process based on said deviation in the mill liner lifter. In another case, in the same way, or in conjunction with this,Any other operational component can be activated, for example, the feeding of grinding balls by a robotic arm and the counting of grinding balls, sensing the fill level by one, several, or a combination of sensors, and providing feedback to the system to correct one, several, or a combination of deviations. Similarly, or in conjunction with this, a solenoid valve can be activated to introduce slurry or process water, or to increase the flow rate to the sprinklers on the trommel side. In another case, in the grinding circuit, in several SAG and ball mills, a deviation in the particle size and mineralogy of the SAG mill feed can be detected. The control base, along with the quality control module, establishes a pre-set standard, and through the analytics module, several simulations and alternatives to increase fracturing will be established. The system will divert a batch of feed to a pebble crusher.For this purpose, it will activate drive units and actuators, and provide feedback to the system with a metallurgical analyzer, such as the IMA Engineering FCA (Fast Conveyor Analysis) conveyor belt analyzer, which performs online mineral measurement on conveyor belts, or BeltMetrics™ cameras that use 3D stereoscopic imaging to analyze particle size, until the optimal process is achieved in the grinding circuit. In another case, in the flotation circuit, a deviation in the mineralogy of the overflow launders of one of the flotation cell circuits can be detected. The control base, along with the quality control module, pre-establishes a standard for the mineral composition; from the data collected online by an AnStat-220 sampling station, the mineral composition analysis (Cu, Mo, Fe,etc.) of the pulp based on x-ray fluorescence, whereby the analysis module establishes the origin of the deviation in the loading face or quarry, and therefore develops an exploration plan; the control base sends equipment such as drilling vehicles and a drilling rig, for which it will activate drive units and actuators in these respectively, and together with a series of metallurgical analyzers will define an appropriate exploration face to achieve the desired mineral composition in the flotation circuit; drilling rig and metallurgical analyzers, such as the NOMAD vehicle, from Godelius of the Sigdo Koppers Group, which has an integrated multisensor platform and can analyze various aspects of the samples, such as their chemical composition and mineral content, and such as,The IMA Engineering BSA (Blast Hole Sampler-Analyzer) blast hole analyzer provides analysis and measurement data during drilling, collects samples and data from dense drill cuttings in production wells, and generates 3D maps of blast benches. The analytics will develop various iterations of the plan to improve the metallurgical quality of the face or a new exploration face, up to the flotation circuit. It will present models and digital twins of the optimized options that allow the mining operation to achieve the best results. It can display 3D models and digital twins (simulation and emulation) projected over time and, if a remote-controlled module decides, can correct or provide feedback on automatic, predetermined, or regulated decisions. Closed or open control loops can be established, and the various resulting scenarios can be simulated.In corrective, preventive, predictive, and / or prescriptive modes, for each stage of processing, from the exploration face to the flotation circuit, including grinding, crushing, a particular piece of equipment, or a specific operational component or components. In another case, in a flotation cell, a deviation in the geometry and distribution of the froth can be detected, and it has also been detected by a series of sensors that the rotor blades have lost their original condition due to wear of their coating. The quality control module establishes the deviation from the standard according to an integrated process quality standard module that establishes a standard pattern for both the froth and the rotor. The analysis module simulates iterations where various ways to optimize flotation are explored based on these two deviations. One solution involves increasing the RPM of the rotor drive unit to optimize the process.To achieve this, the control module will activate the power variable frequency drive on the motor to increase its speed. The analytics are then fed back with images and sequences of the foam's movement to determine the correct speed, geometry, and size, thereby optimizing the flotation process based on these deviations.

[0029] In the previous technique, for example, to perform dimensional quality control on enclosed equipment and structures, a 3D model was introduced to create a 3D survey of the interior surface. However, the information, design, and iterations required to generate a surveyor depend on a lengthy process and a slow response time before a new lining can be delivered and installed. Another approach involves using software to compare the surveyed 3D surface against the original 3D model and simulate adverse production effects (particle size and mineralogy). However, there is no correlation between the 3D models and the effect that must be achieved in the mill to maintain productivity with worn linings, nor is there a way to coordinate and operate the equipment, much less an analytical framework for making informed decisions.

[0030] In the previous technique, in semi-enclosed process equipment and structures where a liquid and / or gaseous medium is exposed, especially in tanks, thickeners, clarifiers, and similar facilities, there is no direct link between quality control of physical, chemical, and biological parameters and corrective action. For example, an operator positioned above a tank unwinds a wired probe with a specific sensor at its end. If the operator detects an urgent deviation in the parameters, they will follow a series of steps to reach the process manager for correction. Typically, the analysis is done after returning from the inspection, and after evaluation by specialists, the information is delivered to a department that will eventually make a decision. It is a slow procedure to send an operator to the work site and deploy the specific sensor.There is no intelligence and speed in the relationship that exists between the team, the process and the specific parameter, and no corrective or predictive action can be taken in the process.

[0031] In the previous technique, drones perform aerial inspections. Apellix is ​​a UAV that operates multiple tools in flight, using a lance at a distance from a construction site. The Voliro robotic flying platform is a UAV that tilts to position itself perpendicular to a work surface and deploys a sensor. There are other reports of UAVs and UGVs with robotic arms that operate multiple tools for various tasks. However, they do not evaluate deviations or make intelligent decisions to control any component, such as actuating a valve to normalize an operational variable on a construction site.In the previous technique, there is no intelligence to evaluate and / or predict the consequences of out-of-standard quality control, nor to trigger an actuator in the variables involved in the process of a work and / or a work to repair, mitigate or change said deviation, nor to deploy vehicles, equipment and machines to produce the desired effect on the product.

[0032] In the previous technique, there is no intelligence to evaluate and / or predict the consequences of out-of-standard quality control, nor to trigger an actuator in the variables involved in the process of a work and / or a work to repair, mitigate, or change said deviation.

[0033] These examples illustrate the need for industry as a whole to control and optimize equipment based on the quality of multiple parameters within a process, process equipment, and / or project, and to intelligently and reliably control the operational variables that correct deviations. Current equipment is not capable of controlling quality while simultaneously controlling the elements that cause or contribute to deviations. With the previous technology, it is not possible to deploy high-performance equipment on-site to control the quality of multiple parameters in a process and / or project, automatically analyze its impact on the process and / or project, and simultaneously control the operational variables that correct these deviations.

[0034] There is a need in the industry for an operation, which involves: a process, a product, a piece of equipment, a project, complementary (or peripheral) equipment, components of these or operational components; to control the quality of multiple parameters, and that, in an intelligent and reliable way for the operation, analyze the impact of the physical, operational and / or financial deviation, in order to act on any component of the operation that corrects said deviation.

[0035] OBJECTIVES OF THE INVENTION.

[0036] The purpose of this invention application relates to a system that allows for the control and optimization of a process, process equipment, and / or a structure, and any complementary component of part or all of the operating chain, including one, several, or a series of pieces of equipment, on a line or in motion, based on multiple and any possible quality parameters. This system identifies and takes corrective action against deviations by controlling any of these components. For illustrative and non-limiting examples, this could include: establishing the wear deviation of SAG and / or ball mill liners, analyzing the cascade and cataract effects, and controlling an operational variable, such as regulating the fresh water feed and / or increasing the RPM of the drive unit.A major advantage is the ability to simultaneously establish the deviation of one or multiple parameters from a quality standard using a series of convenient databases. Software analyzes, optimizes, and evaluates the best course of action on the operational variables that address deviations in SAG and / or ball mills, in a corrective, preventive, predictive, and / or prescriptive manner. This has the advantageous consequence of reducing the impact of any defect that disrupts any operation. These features lead to significant improvements in the productivity of any process, piece of equipment, and / or industrial project.

[0037] To achieve the above, the system comprises: physical entities: process, process equipment and / or a work, vehicles, equipment and devices, equipment that collects one or more parameters; databases of: sensors, machine vision, historical 3D models of the physical entities and the standard models of the multiparameters, normal parameters and their deviations; analytics: software, digital twin, Cloud, Artificial Intelligence, and remote control; a controller over the actuators of the operational variables of said process, the process equipment and / or the work; and a mechanism configured to verify the authenticity and origin of the data through blockchain or similar structures with cryptographic signatures throughout the entire operation.

[0038] A first object of the present invention is to provide a system for controlling and optimizing one, several, or a combination of equipment (502), a structure (600), complementary (or peripheral) equipment, components (503), and / or operational components (504), based on at least one standard pattern. A second object of the present invention is to provide a system for controlling any equipment—machinery, artifact, vehicle, autonomous vehicle, robot, robotic cell, or device—to correct a deviated quality parameter.

[0039] A third object of the present invention is to provide a method for discriminating quality parameters.

[0040] A fourth object of the present invention is to provide an analytics that allows, in a corrective, preventive, predictive and / or prescriptive manner, according to a standard quality pattern, to define the deviation and control one or all of the components involved, such as an operational and / or financial variable of an operation.

[0041] A fifth object of the present invention is to provide a digital twin (simulation and emulation).

[0042] A sixth object of the present invention is to provide Artificial Intelligence.

[0043] A seventh object of the present invention is to provide a Virtual Reality.

[0044] An eighth object of the present invention is to provide a mechanism configured to verify the authenticity and origin of data using blockchain or similar structures with cryptographic signatures throughout the entire operation.

[0045] A ninth object of the present invention is to provide Machine Learning.

[0046] A tenth object of the present invention is to provide data acquisition both inside and outside the operation.

[0047] An eleventh object of the present invention is to provide a system for creating, adding, subtracting, and / or replacing a pattern. A twelfth object of the present invention is to provide for the acquisition of physical, production, operational, and financial data.

[0048] A thirteenth object of the present invention is to provide a system to be controlled in various ways: by remote control, from the control base, from any vehicle that collects parameters, from Artificial Intelligence and by means of Virtual Reality.

[0049] A fourteenth object of the present invention is to provide a system for communicating, instructing, training, and educating internal or external operators of the operation.

[0050] It should be understood that not all implementations can be configured to achieve each and every one of the aforementioned objectives. However, specific implementations may demonstrate the ability to achieve or satisfy at least one or more of the objectives mentioned above.

[0051] Other preferred objects of the present invention will become apparent from the following description. These and other objects of the present invention will be evident from the drawings and description included herein. Although it is believed that each object of the invention is achieved by at least one embodiment of the invention, there is not necessarily one embodiment that achieves all the objects of the invention. BRIEF DESCRIPTION OF THE FIGURES.

[0052] Other features and advantages of the invention will become apparent from the following description of its preferred embodiment, and various embodiments, given only as illustrative and non-limiting examples, will be described with reference to the accompanying drawings, in which:

[0053] Figure 1: is a block flow diagram of how the system operates (1000).

[0054] Figure 2: illustrates an aerial sounding vehicle (662) at the exploration front.

[0055] Figure 3: illustrates a borehole drill (663) at the loading face (639) or quarry. Figure 4: illustrates a shovel (661) for loading onto a haul truck (673).

[0056] Figure 5: illustrates a haul truck (673) in controlled transit.

[0057] Figure 6: illustrates a haul truck (673) in transit.

[0058] Figure 7: illustrates a crusher (675).

[0059] Figure 8: illustrates a stockpile of ore (676).

[0060] Figure 9: illustrates a mill (650).

[0061] Figure 10: illustrates a vertical mill (652).

[0062] Figure 11: illustrates an agitator (672) or mixer.

[0063] Figure 12: illustrates a conveyor belt (674).

[0064] Figure 13: illustrates a leaching (654).

[0065] Figure 14: illustrates some grinding circuits (500) in operation.

[0066] Figure 15: illustrates a stopped mill (650).

[0067] Figure 16: illustrates a mill (650) in motion, with intelligent control.

[0068] Figure 17: illustrates a mill (650) in motion, with intelligent control.

[0069] Figure 18: illustrates a mill (650) in motion under intelligent quality control.

[0070] Figure 19: illustrates a detail of the mill lining (651) (650), with intelligent control. Figure 20: illustrates an operating flotation circuit (641).

[0071] Figure 21: illustrates a thickening (645) in operation. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT:

[0072] In the following detailed description, several example realizations of a system (1000) will be described in detail.

[0073] The invention discloses a method for controlling and optimizing an operation involving one, several, or a combination of equipment (502), a work (600), complementary equipment (or peripherals), a component (503), and / or an operational component (504), based on one, several, or a combination of possible multi-parameters of operational quality, a pattern (200), in a corrective, preventive, predictive, and / or prescriptive manner, until the desired effect is achieved in accordance with a standard pattern (250), such as: a quantitative property, a qualitative, operational, or financial property, a KPI (Key Performance Indicator), an NPV (Net Present Value), an EBITDA (Earnings Before Interest, Taxes, Depreciation, and Amortization).ICF (Instant Cash Flow), mineralogy, concentrate grade, ore hardness, RPM (Revolutions Per Minute), comminution cascade, angle of attack of a mill liner lifter, thickness of a liner, by controlling one, several or a combination of the equipment (502), the work (600), the complementary (or peripheral) equipment, the components (503) and / or the operational components (504); and where the product can be any matter and its states or phases of aggregation: organic and inorganic matter, chemical compound, organic and inorganic, mineral, chemical element, rocks, pulp, sludge, organisms, living or dead beings, animals (including meat), vegetables, pharmaceuticals, food, fish, compounds, simple and compound substances, an electronic component, an electronic artifact, a device, a drone, a vehicle, a machine, a weapon, a vessel,a robot, a dwelling, which at a first level comprises the following steps:,

[0074] a) in a piece of equipment (502) and / or work (600) have at least: a location and communication unit (50) and a control unit (100), equipment (501), a series of sensors (70), machine vision (60) and / or a metallurgical analyzer (80); wherein the equipment (501) includes one, several or a combination of: a UAV, a UGV, an AGV, a Rover, a USV, a UUV and / or an ROV, quadruped robots such as Spot from Boston Dynamics, a biped robot of the Digit type from Agility Robotics, a humanoid robot of the Atlas type from Boston Dynamics, Optimus from Tesla or Valkyrie from NASA and / or an operator manipulating a scanner of the FARO ® Orbis mobile scanner type;

[0075] b) storing and processing the parameters, pattern (200), by means of the control unit (100), and sending the parameters and data by means of a Wi-Fi link from the location and communication unit (50) to a Software (1009), which processes the database (4001), a database (4002), a database (4003), a database (4004) and / or a database (4005); the control unit (100) may be a distributed control system (DCS); wherein the database (4001) includes 3D models and historical data of: the sensors (70), machine vision (60), metallurgical analyzer (80) and the equipment (501); the database (4002) includes 3D models and historical data of: the equipment (502), component (503), operational components (504), operational variables, process media, such as grinding media (balls, rods); The database (4003) includes 3D models and historical data of: the work (600), the process and the product;The database (4004) includes 3D models and historical data of: quality control parameters (2000); and / or the database (4005) includes 3D models and historical data of: actuators (300) and complementary (or peripheral) equipment; wherein the actuators (300) act on any of the operational components (503) and / or components (504) in the equipment (502), the work (600), the process or the process media, such as the grinding media (balls, rods) in the grinding (500); they can be configured to communicate with a distributed control system (DCS) via a bus or network;

[0076] c) define and / or predefine a standard pattern (250) using Software (1009);

[0077] d) control the quality of at least one, several, or a combination of multiple possible parameters, by means of a quality control module (2000) of the equipment (502) and / or the work (600); as in horizontal grinding (500), compare the database (4001) of sensors (70) and metallurgical analyzer (80) of the equipment and the database (4002) of the 3D models of the equipment and the online process, determining: the trajectory (700) of balls and pulp of the cascade, the point (701) of cascade start, the point (702) of impact, the line (703) of start, line (704) of attack, the angle A between the horizontal line (705) of the mill and the point (701) of cascade start, the angle B of attack of the lining, the distance L1 from the center of the mill to the point (701) of cascade start, the distance L2 from the center of the mill to the point (702) of impact, the predominant edge (750) of the cascade and the predominant edge (751) of the cataract;

[0078] e) compare, approve or reject a pattern (200) with a predefined standard pattern (250) of the quality control (2000) of a piece of equipment (502), a work (600), a complementary piece of equipment (or peripherals), a component (503) and / or an operational component (504), by means of the Software (1009), in a non-limiting example, such as the path of the cascade (900) of the comminution of the grinding (500); if the quality control (2000) rejects a defined parameter, then an alert is issued to the control base (1001) and the corrective, preventive or predictive action is carried out and in such a way that an IIoT actuator (1005) is executed in an actuator (300) of the equipment (502), such as: a valve, a motor, a gate; a solenoid valve for the inlet of process water or pressurized air, a power variator on a drive system or dosing pumps for feeding flocculant, a discharge gate for balls from the feed hopper;an actuator, a vehicle, a crane, a drone such as: a UGV, a Rover, a UAV, a USV, a UUV; a robotic arm, a robot, a cobot, a humanoid robot or a quadruped robot, for: manipulation, probing, predefined specific task or multitasking; on land, in the air, over liquid and / or under liquid, until the desired effect is achieved, standard pattern (250), in the equipment (502);

[0079] f) execute an analytics (506) that includes: a Software (1009), a Cloud (1011), Reports (1016) and a remote control (1014), which they acquire;

[0080] g) At a first level, integrating the databases (4001), (4002), (4003), (4004), and / or (4005) and feeding them into the Software (1009), which, by means of a control algorithm, performs corrective, preventive, and / or predictive optimization on the equipment (502) until the desired effect and / or operation is achieved. The invention also discloses a method, which, at a second level, comprises the step:

[0081] a) integrate the databases (4001), (4002), (4003) (4004) and / or (4005) feed and run the Software (1009) and an Artificial Intelligence (1012).

[0082] The invention also discloses a method, which, at a third level, comprises the following steps:

[0083] a) integrate databases (4001), (4002), (4003), (4004) and / or (4005) and build a digital twin (1010); and

[0084] b) couple and run a multiphysics model (400), linear and nonlinear, multispecies or multiphase flow modeling (physical states of matter solid, liquid and gaseous), which is achieved by at least the import of a point cloud (401) and a scenario in a 3D model (402) and which includes the analysis of one, several or a combination of multiple possible aspects, such as structural, mechanical, fluid-mechanical, immiscible fluids (e.g., water and oil), non-Newtonian materials, electromagnetic, chemical, temperature, turbulence, heat transfer, chemical reactions, aeroacoustics, turbomachinery, fluid flow;to couple and execute one, several or a combination of the modules: DEM analysis (Discrete Element Method) (403), and / or CFD analysis (Computational Fluid Dynamics) (404), such as fluid dynamic analysis, such as Ansys Chemkin-Pro, and / or FEA analysis (Finite Element Analysis) (405) and / or DPM analysis (Discrete Phase Model) (406).;

[0085] The invention also discloses a method, which, at a fourth level, comprises the step:

[0086] a) integrate the databases (4001), (4002), (4003), (4004) and / or (4005) and build a Virtual Reality (1015), which includes at least the construction of a human-computer interface simulation scene: VR (Virtual Reality), AR (Augmented Reality) and / or MR (Mixed Reality); which acquire gestural remote control, Mixed Reality and AI (Artificial Intelligence), with a holographic device of the Microsoft HoloLens 2 type glasses, through the integration of motors of the Evergine 3D motor type, Holo-Robot from Plain Concepts.

[0087] The invention also discloses a method, which, at a fifth level, comprises the step:

[0088] a) Integrate the databases (4001), (4002), (4003), (4004), and / or (4005) and build a Blockchain (1017), using a Ledger system that stores all data transactions, as a design parameter resulting from the Software (1009) and / or an Artificial Intelligence (1012), which creates at least one Report (1016), one or more of multiple possible notifications and / or reports, to the control base (1001), and where the control base (1001) has or determines who has a Wallet, which is a digital interface that allows sending, receiving, and storing digital assets securely, where the entire process is certified and audited by generating NLTs (Non-fungible Tokens), which are unambiguous representations of assets, both digital and physical. as physicists.It uses JS, Solidity and HTML languages; it issues corrective, preventive, predictive and / or prescriptive reports.

[0089] The invention also discloses a method, which, at a sixth level, comprises the step:

[0090] a) integrate the databases (4001), (4002), (4003), (4004) and / or (4005) and build the digital twin (1010) by means of Machine Learning (1013) (which means “automatic learning”), makes decisions and / or makes predictions, and which acquires supervised, unsupervised, semi-supervised and / or reinforcement learning control algorithms; and which can acquire a CNN (abbreviation CNN or ConvNet, from the English “Convolutional Neural Network” which means “Convolutional Neural Network”) deep learning algorithm, such as in a non-limiting example, for object recognition, such as classification, detection and segmentation of images and 3D models.The invention also discloses a method for discriminating quality parameters and controlling an actuator (300), by means of a Software (1009) in a piece of equipment (502) and / or a work (600), and / or the complementary (or peripheral) equipment, components thereof or the operational components, based on one, several or a combination of multi-parameters of quality, which may be independent or several linked in a series of a part or complete of a process line, in a corrective, preventive, predictive and / or prescriptive manner, where it can resolve one or several of multiple aspects that optimize the product, process, functioning, operation and / or maintenance, until achieving the desired effect at the place of operation, comprising the following steps:.

[0091] a) obtaining one, several, or a combination of multiple possible parameters from, a piece of equipment (502), a work (600), the complementary (or peripheral) equipment, components of these and / or the operational components, pattern (200), by means of: the sensors (70), artificial vision (60), the equipment (501) and / or a metallurgical analyzer (80);

[0092] b) identify at least one pattern, pattern (200), such as: dimensional, 3D surface comparison, surface finish, visual, thermographic, acoustic, temperature, humidity, vibrations, using a Software (1009);

[0093] c) build a database (4004) of quality control parameters, and predefine and establish standard pattern (250);

[0094] d) contrast the parameter, pattern (200) with one, several or a combination of standard patterns (250);

[0095] e) correlate the pattern (200) with a defined position of a team (502) and / or a work (600) using the Software (1009);

[0096] f) determine qualitatively and quantitatively how far the pattern (200) is from the standard pattern (250), using the Software (1009), according to database (4001), (4002), (4003) and / or (4005); g) send a report and / or an alert of the results to quality control (2000), and establish whether it is correct “Y” and incorrect “N”,

[0097] h) if “N” is incorrect, send notification to the control base (1001), and re-execute steps b) d) and f);

[0098] (i) operate an IIoT (Industrial Internet of Things) actuator (1005) of the actuators (300) to control equipment (502), a work (600), complementary (or peripheral) equipment, components thereof and / or operational components, including but not limited to: an actuator of a gate in a ball feeder (683) and a rotary unit (693) for the drum housing (653) of a mill (650); a rotary unit (693) of the impeller (681) and the valve in the air line of a reactor (669) flotation cell; a rotary unit (693) of the rake and scrapers (678) and a valve for the flocculant line in a thickener (671); and achieve a satisfactory quality parameter; and

[0099] j) if “Y” is correct, send notification to the control base (1001), and;

[0100] k) execute in each operation of the chain of operations in all the previous steps, a notification and certificate by Blockchain (1017) issued to the control base (1001).

[0101] Detailed description of the system components.

[0102] The equipment (501), which can operate on land, in the air, on water, or underwater, includes at least: a UAV, a UGV, an AGV (automated guided vehicle) for cargo, a rover, a quadruped robot such as Boston Dynamics' Spot, a bipedal robot such as Agility Robotics' Digit, a humanoid robot such as Boston Dynamics' Atlas, and / or Tesla's Optimus or NASA's Valkyrie. In other embodiments, the equipment (501) includes: a USV (unmanned surface vehicle), a UUV (unmanned underwater vehicle), and / or an ROV (remotely operated vehicle) that are controlled by a human operator who is not physically inside the vehicle.It can also collect data through operators who move sensors or 3D vision devices to a point of interest.

[0103] Regarding a process, a product, a piece of equipment, a work, the complementary (or peripheral) equipment, components of these or the operational components, there is a location and communication unit (50), a series of sensors (70) and a control unit (100), which deliver signals and establish communication with the equipment and systems of the system (1000).

[0104] The equipment (501) includes a control unit (100) configured for: ground, surface, and underwater driving maneuvers, flight paths, communication, data storage, monitoring, task operation, and system control. These functions are transmitted via a Wi-Fi link, enabling data to be sent to the Cloud (1011) and operations to be enhanced through Artificial Intelligence (1012). The control unit (100) allows for the measurement of at least one parameter at the work site.The control unit (100) enables the operation of machines, vehicles, equipment, devices, static, rotating, mobile and motorized equipment (502), a work (600), complementary equipment (or peripherals), a component (503) and / or an operational component (504), actuator (300), and equipment (501) because the actuators, such as linear actuators and motorized rotation units, have encoders, such as linear, angular, optical by blue light or wired, or any other type.

[0105] Actuators (300) may include: a speed, frequency or power variator, an on / off switch, a reversing switch, a potentiometer, a timer; Wi-Fi controller; for: a valve, a solenoid valve, a drive unit, a pump, a dosing pump, a linear actuator, a rotary unit, etc.; a gate of the type; pneumatic, rotary piston pneumatic, diaphragm balance, motorized or hydraulic; which may be of the type: electric, mechanical, electromechanical, electro-hydraulic, pneumatic, hydraulic; may include: encoders, such as: linear, angular, optical by blue light or wired, or any other type.Vehicles, equipment, devices, and equipment specific to a process, product, piece of equipment, or project, as well as complementary (or peripheral) equipment, components thereof, or operational components, are equipped with a location and communication unit (50) comprising a high-precision GPS (Global Positioning System). The described implementation communicates via Wi-Fi signals. Various wireless means exist. Data can be communicated via low-power RF (radio frequency) emissions at a low duty cycle (e.g., once a day) to the dedicated reader of the control unit (100), which will transmit the information via the higher-power GSM (Global System for Mobile communications) network to a cell phone or smartphone for a site supervisor or control center (1001).Data transmission is also achieved via low-energy radio waves (Bluetooth, Zigbee, Z-Wave, etc.). Therefore, communication and data can be connected to a smartphone, tablet, computer, immersive reality headset (such as Apple's Vision Pro mixed reality headset), etc. Other implementations may include wireless communication technology that combines ultra-low power consumption with a long effective range, such as LoRa (Long Range), for long-distance connections and when sensors without access to mains power are required. Communication is achieved through first transmission signals, second reception signals, and third control signals, via a wireless radio link. The communication interface is achieved using various interfaces: 3G, 4G, 5G, Ethernet, optical network, MODBUS, PROFIBUS, CAN bus, RS485, TCP / UDP, and HART and OPC UA communication protocols.

[0106] The series of sensors (70) and artificial vision (60), collect data such as: vibration, audiometry, temperature, 3D images, pulp thickness and mineralogy (901) in a piece of equipment (502) of the work (600); Physical, chemical, and biological parameters, organic, inorganic, contaminants, toxicity, viruses, and bacteria, of water, air, and equipment: microphone, a gyroscope / accelerometer sensor, and an IMU; distance, speed, acceleration, vibration, temperature, humidity, wind speed, pressure, load, liquid currents, atmospheric pressure, liquid level, liquid pressure, position, speed and acceleration of moving objects, salinity, carbon dioxide (CO2), dissolved oxygen (O2), acidity (pH), mass, density, and viscosity of liquids and gases (Coriolis mass flow meter), liquid velocity, turbidity, electrical conductivity, total dissolved solids (TDS), nitrites (NO2), nitrates (NO3), ammonium (NH4), calcium, potassium, and metal ions.Chlorides, Free and Total Chlorine, Copper, Chromium, Nickel, Iron, Silica, Bromine, Manganese, Magnesium in seawater, Phosphate in seawater, Fluorides, Phosphorus in seawater, Water color, Biosensors, Virus and bacteria sensor, Photonic sensor for contaminants, Optical biosensors for toxicity, Fluorometers for chlorophyll parameters, Photometers, Ammonia gas (NH3), Hydrogen sulfide (H2S); obtaining a quality parameter associated with a position; or any other possible type.

[0107] The machine vision unit (60) includes a series of: a 3D ToF camera (time-of-flight), an omnidirectional camera, a CDD camera array (charge-coupled device), a high-resolution thermal imaging camera, multispectral cameras, a 3D scanner, a LIDAR system (Laser Imaging Detection and Ranging), a solid-state laser, high-power LED spotlights, high-definition radar (radio detecting and ranging), and a laser pointer (not shown); or any other possible type.

[0108] Machine vision (60), in other embodiments, considers a high-accuracy, high-resolution, and high-speed 3D laser scanner that covers large ranges of surface sizes, such as a Leica RTC360 3D laser scanner, which has an accuracy of 1.9 mm.

[0109] In some embodiments, the machine vision (60), and / or equipment (501), perform the acquisition of at least one or more parameters or data collected, from a series of multiple possible parameters or data collected by means of one, several or a combination of: a LiDAR system, 3D camera, multispectral cameras, hyperspectral cameras, a series of high resolution and speed thermal imaging cameras, 3D ToF camera, a series of multidirectional cameras, a set of high power LEDs, high definition radar and a laser pointer, RGB and multispectral cameras, a hyperspectral camera of the type Baldur V-1024 N® from HySpex and / or a LiDAR, such as Ouster OSO®, or a high bandwidth stereoscopic depth camera, such as the Intel® RealSense™ D457 depth sensor camera.

[0110] The vehicles, equipment, devices, and other components of a process, process equipment, or construction project are equipped with a range of instrumentation and sensors. These sensors (70) comprise a variety of types for measuring various parameters: wind speed, ambient temperature, air temperature, humidity, dust particles, gas sensors, surface temperature of objects being inspected, color, weight, speed, flow, pressure, load, object proximity, depth, altimetry, etc. They include ultrasonic, inductive, and capacitive sensors, as well as gyroscopes, accelerometers, high-performance and high-resolution microphones, and sound level meters. The equipment also includes an Inertial Measurement Unit (IMU).

[0111] In some embodiments, the sensors (70), metallurgical analyzer (80), machine vision (60), and / or equipment (501) acquire at least one, several, or a combination of parameters or data collected from a series of multiple possible parameters or data collected from: the environment, such as: soil, water, liquid, sludge, acid mist, tailings, air, sea; the infrastructure, such as: factory, concentrator plant, grinding area; a process line, such as: serial and regrinding mills, recirculating mills, flotation cell bank; equipment, such as: industrial equipment, a device, a vehicle, a robot; a component, such as: parts and pieces of those described above, electronic, mechanical, biological, composite, coating, nanoparticle, linings, cladding, coating, heat treatments, surface finish, and paints; characteristics or patterns, such as: size, length,Materials, weight, arrangement and / or disposition, profile geometry in the lifter, physical, chemical, mechanical, and biological properties; and / or processing media, such as: pulp, rocks, grinding media (balls, rods), packaging, electronic items, biological materials, manufacturing inputs, and waste; possible collected parameters or data: physical, structural, mechanical, chemical, biological, inorganic, and organic parameters; such as: geometric, weight, dimensions and 3D surface, surface finish, material thickness, paint and coating thickness, weld cracks, oxidation level, temperature, distance, acceleration, vibration, pressure, load, liquid currents, atmospheric pressure, liquid level, liquid pressure, position, speed and acceleration of moving objects, salinity, carbon dioxide (CO2), dissolved oxygen (O2), pH, and mass.Density and viscosity of liquids and gases (Coriolis mass flow meter), liquid velocity, electrical conductivity, total dissolved solids (TDS), nitrites (NO2), nitrates (NO3), ammonium (NH4), calcium, potassium, metal ions, chlorides, free and total chlorine, copper, chromium, nickel, iron, silica, bromine, manganese, magnesium in seawater, phosphate in seawater, fluorides, phosphorus in seawater, water color, wind and liquid speed and direction, humidity, vibrations, audiometry, odors, concentrations of volatile organic compounds in air, density of solids and turbidity in liquid media, mineral concentration in solids, rocks, dust, liquids, pulp or tailings, ammonia gas (NH3), hydrochloric acid, nitrogen dioxide and / or hydrogen sulfide (H2S), contaminants, toxicity, viruses and bacteria, biosensors, virus and bacteria sensor Photonic sensors for contaminants, optical biosensors for toxicity, fluorometers for chlorophyll parameters, photometers,radiometric sensors (radiation detector), photometric sensors (light source and detector), electromagnetic sensors (source and detector or induced potential) or more high-energy electromagnetic sources / detectors such as X-ray source types (fluorescence or transmission) or gamma ray source; includes at least a microphone, a gyroscope sensor and / or an accelerometer and an IMU (Inertial Measurement Unit); for sedimentation equipment to check the sludge blanket level, such as: Sludgewatch 715 portable sludge blanket gauge, Partech, which uses a range of infrared sensors, which detect the sludge interface and PUA SmartDiver from PUA Process Analysers, a self-submersible sludge probe that collects suspended solids and density data; the metallurgical analyzer (80) such as: SamStat-30 type sampling stations, an AnStat-220 sampling station, which performs the mineral composition analysis (Cu,Mo, Fe, etc.) of the pulp based on X-ray fluorescence, a multi-flow analyzer, of the type XRF Elemental Pulp Analyzer, MSA Mk5.2 Multi-Flow, which performs the mineral composition analysis (Cu, Mo, Fe, Sol.), a particle size monitor by ultrasonic attenuation of the type Thermo Scientific™ PSM-400MPX, to determine p80 handling between 290 and 25 microns, and pulp density or percentage of solids and / or reverse sampling stations, of the type SamStat-30R; and such as, to measure the elemental composition of bulk materials on a conveyor belt Fast Conveyor Analyzer from IMA Engineering, uses XRF technology; and a gamma ray sensor of the type Medusa Radiometrics; or any other possible type; the sensors can be as diverse as possible, without limitation, such as: Pat. W02017113027A1, Submersible system and method for measuring the density and / or concentration of solids in a dispersion, Pat. US10412275B2,Apparatus for monitoring the interior of the mill during operation, Pat. WO2014187824A1, Apparatus for monitoring the interior of the mill during operation; gear alignment systems for measuring gear load distribution according to ISO-6336, such as the Astute™ from Transmission Dynamics; bolt tension monitoring, such as the Load Monitoring Fastener+® from Transmission Dynamics; or any other.

[0112] For vehicles and equipment, it is necessary to protect the actuators and instrumentation with enclosures rated at least IP67, as mining operations typically involve environments with aggressive agents. If the vehicle or equipment is in an environment with design conditions for explosives, for example, in a mining extraction environment with specific hazardous gases, the electrical and mechanical components and protection systems must meet ATEX explosion protection standards (an abbreviation of the French, “ATmosphère Explosible,” meaning “Explosive Atmosphere”).

[0113] The database (4001) includes data and parameters collected during the operation of: machine vision (60), sensors (70), equipment (501) and / or metallurgical analyzers (80); it includes the databases and parameters: historical data of the operation or other operations, maximum and minimum levels, frequency and amplitude, exposure time, intensity, concentration, descriptors, operational risk level, risk level (high, medium, negligible), associated operational observations, associated recommendations; 3D models from: images, ultrasound, laser, thermal, vibrational, sound measurement, odorimetry, mineralogical, viscometry, or any other possible type.

[0114] The database (4002) includes data and parameters collected during the operation of the equipment (502), the component (503), and / or operational components (504). It includes the databases and parameters: the 3D models of the operation, historical data, and reference data. It includes one or more of the following possible aspects, such as: materials, volume, composition, center of gravity, surface finishes, physicochemical properties, mechanical, operational, and functional properties, criticality to the operation, performance, performance observations, durability, replacement date, major shutdown date for replacement, and replacement time. The equipment (502) includes mechanical, physical, operational, and functional properties, such as: operating speed, operating load, operating ore size (F80), product size, power of the rotating unit, and type of grinding operation.The components (503) include mechanical, physical, operational and functional properties, such as: new and worn 3D geometry and surface, manufacturing and assembly tolerance, position and spatial orientation in the equipment, material, chemical composition, mechanical properties, center of gravity, wear level.The operational components (504) include operational variables such as: RPM (Revolutions Per Minute); direction of rotation, percentage of solids, rotational and critical speed of rotating equipment, feeding and discharge of operational components, residence time of the process material, superficial gas velocity, peripheral agitation speed, mineralogy, particle size, density (of pulp), grinding media size, temperature, filling level, dosage and feed and discharge flow of: the product, process material; dosage and flow of: clear water or process water, flocculant, solution, reagent, pH modifiers, aeration, foam height, etc., also process media, such as grinding media (size of balls, rods).For example, the database of operational variables for SAG milling: fresh feed (measured with a weight gauge and speedometer), feed particle size (image analysis), solids concentration (measured with a Marcy balance), SAG power (measured with an ammeter), water flow to SAG (measured with a flow meter).

[0115] The database (4003) includes the databases of: a process, a product and a work (600); it includes the databases and parameters of: current, historical and reference 3D models; current, historical and reference flow diagram of the process and / or the processes of the operation; current, historical and reference physical-chemical properties of the process and the product, such as: physical-chemical properties, speed, volume, weight, particle size, viscosity, hardness; mass and energy balances, material balances, metallurgical balance of a process: of grinding, of a flotation circuit, of a leaching operation; particular field testing and sampling equipment, such as bond bars in a laboratory; relevant operational features of the process, such as: comminution cascade, pulp characteristics, actual filling level, trajectory, “catarrh”, “feed foot”, and “shoulder” of comminution.The work (600) includes: an infrastructure, a civil work, a building, a shed, which complement the equipment (502), the network of pipes, conduits, channels, ducts, supports, structures that connect and make the process possible.

[0116] The product, in a broad sense, encompasses matter and its states or phases of aggregation: organic and inorganic matter, chemical compounds, minerals, chemical elements, rocks, pulp, sludge, organisms, living beings, fish, compounds, and simple and compound substances. Therefore, the product's databases, which are the subject of a specific operation, include physical properties such as specific weight, density, porosity, permeability to liquids and gases, heat capacity, thermal conductivity and expansion, etc. Chemical properties include, for example, resistance to acidic and alkaline solutions, and reactions induced by the presence of salts.

[0117] The process or processes of the operation, to obtain the given product, in a broad sense; consists of a sequential set of actions executed to achieve a given product through equipment, for example: comminution in the grinding of ore to reduce and classify ore, flotation to separate by overflow and recover ore and water, sedimentation or thickening to separate by compaction and recover pulp and water, screening to classify and grade the particles of ore, crushing to reduce and make homogeneous, leaching to extract from a mineral by means of solvents.

[0118] The databases (4001), (4002) and (4003) are at least one, several and / or a combination of parameters from a series of multiple possible parameters: of the environment, of the infrastructure, of a process line, of a piece of equipment, of a component, characteristics or patterns, physical, chemical, mechanical, biological properties; and / or means for the process, possible collected parameters or data: physical, structural, mechanical, chemical, biological, inorganic and organic parameters; in a non-limiting example, such as, in the case of the mill (650): the infrastructure in the concentrator plant, the equipment upstream and downstream of the mill (650), pulp mineralogy (901), a lining (651), the grinding media (balls, rods), grate, pads and their grooves.

[0119] The databases of the different data and parameters can be compared and contrasted, in a non-limiting example, the dimensions and areas of highest temperature of the lifters in the wear lining between two campaigns (or stops for maintenance).

[0120] The database (4004) consists of at least one, several, or a combination of predefined quality control parameters (2000), created by Artificial Intelligence (1012), created by Machine Learning (1013), co-created with the remote control (1014), historical data, 3D models, a database of quality standards for any aspect of equipment (502), a structure (600), complementary equipment (or peripherals), a component (503), and / or an operational component (504). This includes operational quality databases such as: UNE-EN ISO 17637 Visual examination of fusion-welded joints or UNE-EN 17666 Maintenance Engineering Requirements. It also includes operational databases such as: mass and energy balances, material balances, metallurgical balances for a grinding circuit, metallurgical balances for a flotation circuit, and metallurgical balances for a leaching operation.Quality databases that define economic benefits, business profit and operations, such as: KPIs (Key Performance Indicators), NPV (Net Present Value), EBITDA (Earnings Before Interest, Taxes, Depreciation and Amortization), ICF (Instant Cash Flow), Balanced Scorecard (BSC, Robert Kaplan and David Norton), Operational Scorecard (OSC, Robert Kaplan and David Norton), CapEx (Capital Expenditures), OpEx (Operational Expenditures).For example, the flotation balance: Grade, Feed Grade, Concentrate Grade, Tailings Grade, operating index, metallurgical recovery, yield, concentration ratio, enrichment ratio. For example, the Flotation area KPIs: Plant Recovery, Treatment (TpH), F80, Concentrate Grade; the Grinding area KPIs: Treatment (TpH), P80, F80, Available time of the mills involved, Resting pressure, Ore hardness, fluctuation database and the price of minerals in dollars per metric ton, the allowable recovery percentage required at the Cu and Mo plant. This includes the London Metal Exchange database, daily and monthly, for example, Copper (US$ / Ton) 9,000 on 11 / 15 / 2024.

[0121] The database (4005) consists of at least one, several, or a combination of the current, historical, and reference 3D models, data, and parameters of the actuators (300) on the equipment (502) on the construction site (600) and / or on complementary (or peripheral) equipment, such as: effectors, actuators, grippers (of robot arms, machines, or autonomous machines), valve, solenoid valve (for feeding and discharging), frequency converter (for rotation units), a vehicle, a crane, an overhead crane, a drone, a robot arm, a robot, and / or a cobot for a specific predefined or multitasking manipulation or task, and any component thereof.In the same way as the databases (4002), in a non-limiting example, the databases (4005) can be the geometry of the series of manual and automatic valves of the mill circuit (650) or operational properties such as: flow rate and transport speed of the product they process, operational performance, performance observations by an operator.

[0122] The databases (4001), (4002), (4003), (4004), and (4005) generally comprise positive and negative experiences, successes and failures, success stories, deviations, observations, and internal and external references from any component of the operation and other reference or parallel operations. They can receive feedback from the control base (1001), remote control (1014), or Virtual Reality (1015) via text, protocols, images, gestures, voice, icons, or any other HMI (Human Machine Interface).

[0123] The analytics (506) takes the databases (4001), (4002), and (4003) and compares them with the quality control (2000). The quality control (2000) defines a predefined standard parameter that is built as the process, process equipment, and / or project performs well. It is a database of quality standards for at least one parameter; for example, the UNE-EN ISO 17637 standard, Visual examination of fusion-welded joints. Quality standards can, of course, be included internally, or an international standard can be replaced with a local one to achieve good performance. The analytics (506) is the computer process, based on at least one control algorithm, that performs simulation and emulation, allowing for the improvement of operations in accordance with the quality control (2000). In this realization, the analytics (506) depend on the control basis (1001), where a human being is the one who makes the final decision on the quality control of a process.In other realizations, the analytics (506) is completely autonomous.

[0124] Databases (4001), (4002), (4003), (4004), and (4005) can be structured, semi-structured, and unstructured databases, SQL (Structured Query Language), NoSQL data, and even spreadsheets. NoSQL databases are highly scalable and offer excellent performance for large, unstructured datasets, such as network and IIoT (1005) (Industrial Internet of Things) data.

[0125] Databases (4001), (4002), (4003), (4004), and (4005) can be enhanced and integrated with ERP (Enterprise Resource Planning) databases. An ERP is a software system that includes all the tools and processes necessary to manage a company, covering aspects such as manufacturing, supply chain, and finance. They can also be enhanced and integrated with construction management software for on-site execution and BIM (Building Information Modeling) project management, such as Autodesk Construction Cloud (ACC), a cloud-based platform for managing construction projects. Finally, they can be enhanced and integrated with machine monitoring software, such as Schaeffler's OPTIME.They can be strengthened and integrated into a type of remote machinery operation, such as TeleOp, from Hexagon, or monitoring of the HxGN APM, Monitor Asset Twin, type, from Hexagon.

[0126] The analytics (506) inputs the databases (4001), (4002), (4003), and (4005) and integrates them into the multiphysics model (400), which is linear and nonlinear, and multispecies or multiphase flow modeling (physical states of matter: solid, liquid, and gas). The result is the control and optimization of equipment (502), a structure (600), complementary (or peripheral) equipment, components (503) of these, and / or operational components (504), based on one, several, or a combination of multiple possible quality parameters, using a standard pattern (250). The analytics (506) is the computer process, based on at least one control algorithm, that allows for the simulation, emulation, and improvement of performance, according to the multiphysics model (400).In this embodiment, the analysis (506) depends on the control basis (1001), where a human being makes the final decision regarding the quality control of a process, process team, and / or project. This human being may belong to the company that owns the process, process team, and / or project, a company that provides services to the company that owns the process, process team, and / or project, or another commercial entity. In other embodiments, the analysis (506) is completely autonomous.

[0127] The multiphysics model (400), analytics (506), and digital twin (1010) construct one, several, or a combination of models in a simulation or emulation mode. Simulation predicts how a system will behave in different situations and allows for the analysis of its behavior under various conditions. Emulation copies or imitates the behavior in different situations, accurately replicating the functions and operations of the original system. The various versions, revisions, or iterations of the models, as well as graphics and infographics, can be used for induction, instruction, and education, both within and outside of operational settings.

[0128] In this implementation, the databases (4001), (4002), (4003), and (4005) are the logical model reflecting the physical model, using at least one software (1009). Then, a digital twin (1010) is constructed in a corrective, preventive, predictive, and / or prescriptive mode. This involves three-dimensional modeling of the physical entity, where the structure, geometry, materials, boundary conditions, and at least one finite element analysis are modeled. This is achieved by importing the point cloud from a 3D scanner of the equipment (501) and / or machine vision (60) from at least one of the vehicles and devices, such as Recap software. This data is then imported into 3D modeling software, such as 3DS Max, to integrate more complete and multi-layered work scenarios. The rotating equipment of the construction process is analyzed using DEM (Discrete Element Method). In a non-limiting example,For the mill (650) and its lining (651), such as Altair EDEM or Ansys Rocky software, after the DEM simulation the scene is fed back into 3DS Max. In another aspect, the process ducts of the work are worked on in parallel with a CFD analysis (from the English "Computational Fluid Dynamics") for the feed and discharge of the mill (650), and the scene is fed back into 3DS Max. In another aspect, the supporting structures are worked on in parallel with an FEA analysis (from the English "Finite Element Analysis"), and the scene is fed back into 3DS Max. In another aspect, the particles of the "waterfall", "foot of the load" and "shoulder" effect of the comminution are worked on in parallel with a DPM analysis (from the English "Discrete Phase Model") (706).

[0129] At the next level, the 3D models and boundary conditions are iterated by Artificial Intelligence (1012). The data is sent to the Cloud (1011), either in backup or direct service mode. Using an open-source virtual reality simulation engine, such as Unreal Engine, the 3DS Max scenes are acquired, and a simulation scene is built with human-computer interfaces: VR (Virtual Reality), AR (Augmented Reality), and MR (Mixed Reality), according to the analytics decisions (506) or in a remote control mode (1014). The visualization and design interface incorporates gesture-based remote control, Mixed Reality, and AI (Artificial Intelligence), with a Microsoft HoloLens 2 holographic device, through the integration of the Evergine 3D engine and Plain Concepts' Holo-Robot.

[0130] Simultaneously with the entire chain of operations, each piece of data in at least one of the databases and / or decision-making processes generates a Blockchain (1015).This is achieved through a Ledger system that stores all data transactions in this implementation; including, but not limited to, reading multiple parameters from at least one vehicle, piece of equipment, or device; design control statuses; and notification and / or reporting to and from the control base (1001) of the process, the process equipment, and / or the work site. The control base (1001) has, or determines who has, a Wallet, which is a digital interface that allows for the secure sending, receiving, and storage of digital assets. The entire process is certified and audited through the generation of NFTs (Non-Fungible Tokens), which are unambiguous representations of both digital and physical assets. JavaScript, Solidity, and HTML compatible with IIoT (1005) are used.

[0131] Although it is stated that each module of the multiphysics model (400) works in a concatenated manner, in the realization, it does not exempt that, by itself, each module performs a certain task independently in other varied realizations, and with this it is possible to control and optimize the operation that includes: any equipment, machine, artifact, vehicle, autonomous vehicle, robot, robotic cell, device; a piece of equipment (502), a work (600), the complementary (or peripheral) equipment, components (503) of these and / or the operational components (504).

[0132] It should be understood that the invention application, the method provides as a result the control and optimization of an operation, which involves some equipment (502), a work (600), some complementary (or peripheral) equipment, the components (503) of these or the operational components (504), based on one, several or a combination of standard pattern (250), based on quality control, parameters and data; quantitative and qualitative quality: physical, performance, operational, productive, financial; which can be of one piece of equipment, a series of interconnected pieces of equipment, one of multiple characteristics or possible patterns of the same;non-limiting, such as: the optimal trajectory of the comminution cascade with worn lifters in the mill liners in order to extend optimal comminution and thereby extend the next mill shutdown in a programmed manner based on the profitability of the operation. In this case, the quality control of the mill liner lifter thickness and the quality control of the comminution cascade effect have been compared, and the mill RPM has been controlled based on these two quality controls to maximize performance. In this embodiment, non-limiting, the Software (1009) and / or the Artificial Intelligence (1012) executes an optimization program for the section of a profile and / or surface for at least one component of the work (600) and the equipment (502);In this embodiment, the Software (1009), Artificial Intelligence (1012), and / or the digital twin (1010), and / or Machine Learning (1013) executes a program to optimize the section of a profile and / or surface for at least one component of the work (600) and the equipment (502); not limiting, such as optimizing the RPM according to the cross-section and / or longitudinal section and / or impact surface in a casing lifter based on the process and performance KPI of said equipment (502), see Fig. 1, 14, 15, 16, 17, 18 and 19.

[0133] In this embodiment, the Software (1009), Artificial Intelligence (1012) and / or the digital twin (1010) and / or Machine Learning (1013) executes an optimization program to control and optimize performance in a piece of equipment (502); not limited to: flow dynamics in a flotation unit, comminution in a horizontal and / or vertical mill, and thereby actuate the actuator (300) to control the RPM of the drive unit.

[0134] In this embodiment, the Software (1009), Artificial Intelligence (1012) and / or the digital twin (1010) and / or Machine Learning (1013) executes an optimization program, to control and optimize performance, in a work (600); not limited to: the dynamics of flows in a network of pipes, conduits or channels, and thereby actuate an actuator (300) to control the opening and closing of a valve.

[0135] In this embodiment, the Software (1009), Artificial Intelligence (1012) and / or the digital twin (1010) and / or Machine Learning (1013) executes an optimization program to control and optimize performance in complementary (or peripheral) equipment; not limited to: the dynamics of flows in a feed or discharge hopper, and thereby actuate the actuator (300) to control the opening and closing of a gate.

[0136] In this embodiment, the Software (1009), Artificial Intelligence (1012), and / or the digital twin (1010), and / or Machine Learning (1013) executes an optimization program to control and optimize the performance of certain components (503), including, but not limited to, the flow dynamics in the linings of SAG or ball mills, or in the impeller of a flotation cell, thereby actuating the actuator (300) to control the RPM and direction of rotation of the drive unit. In this embodiment, the Software (1009), Artificial Intelligence (1012), and / or the digital twin (1010), and / or Machine Learning (1013) executes an optimization program to control and optimize the performance of certain operational components (504). non-limiting, such as: the flow dynamics in grinding media, balls in a SAG mill, or the flocculant in a flotation cell, and thereby actuate actuator (300) to control the opening and closing of a valve.

[0137] In this embodiment, the Software (1009), Artificial Intelligence (1012) and / or the digital twin (1010) and / or Machine Learning (1013) executes an optimization program to control and optimize the performance of the product; not limited to: flow dynamics according to the granulometry and mineralogy in the transport from mine to crushing, from crushing to grinding and from grinding to flotation, and thereby actuate one, several or a combination of actuators (300) to control the RPM and direction of rotation of a series of driving units, and control the opening and closing of a series of valves in a series of vehicles, robots, machines, equipment, devices, works, complementary (or peripheral) equipment, components and operational components.

[0138] Machine Learning (1013) employs a neural network, interconnected nodes in a layered structure, creating an adaptable system that learns from its mistakes and continuously improves. It utilizes supervised, unsupervised, semi-supervised, and / or reinforcement learning algorithms. In the unsupervised model, the system receives an unlabeled dataset and learns the underlying structure, exploring the data, identifying patterns, and grouping similar data without prior knowledge of the correct answer. The goal is to discover hidden patterns, structures, or relationships within the data. The semi-supervised model uses a partially labeled dataset to understand parameters and interpret the unlabeled data.The reinforced model observes its environment and uses that data to identify the ideal behavior that will minimize risk or maximize the solution. It has an iterative approach that requires a reinforcement signal to help better identify the appropriate action. The supervised model has a labeled set of data that allows it to learn how to perform a human task. Algorithms in predictive mode are multivariable control algorithms, a technique used to solve the problem of matching manipulated and controlled variables. The control algorithm establishes the relationship between the input and output variables of a controller. The controlled variable is the quantity or condition that is measured and controlled, while the manipulated variable is the quantity or condition that the controller modifies to affect the value of the controlled variable.In some implementations, the interactions between loops are strong, where multivariable control techniques based on decouplers are executed, which are control elements that reduce the intensity of the interactions, among which there is a Smith predictor.

[0139] In some implementations, DCS (Distributed Control System) centralization is performed using a deep learning algorithm.

[0140] Acquire a CNN (Convolutional Neural Network), a deep learning algorithm designed primarily for tasks requiring object recognition, such as classification, detection, and segmentation of images and 3D models. It allows you to identify and extract patterns and features from data regardless of variations in position, orientation, scale, or translation. Pre-trained CNNs include VGG-16, ResNetóO, Inceptionv3, and EfficientNet.

[0141] The neural network is previously trained in the following aspects: extracting data of interest from the equipment (501), the series of sensors (70), the artificial vision (60) and / or the databases (4001), (4002), (4003), (4004) and / or (4005); establishing a pattern (200) and controlling the components in a corrective, preventive, predictive and / or prescriptive manner, of a piece of equipment (502) and / or the work (600), according to the established standard pattern (250) by quality control (2000) and the desired effect; coupling when appropriate the analytics (506): Software (1009), digital twin (1010), Cloud (1011), Artificial Intelligence (1012); Attach the multiphysics model (400) when appropriate: point cloud (401), 3D modeling (402), DEM analysis (403), CFD analysis (404), FEA analysis (405) and / or DPM analysis (406); issue Reports (1016) and / or Blockchain (1017) when appropriate; open interaction instance and store data of interest, by means of: remote control (1014) and / or Virtual Reality (1015).The data collected by the equipment (501), the sensor array (70), the machine vision (60), and / or the databases (4001), (4002), (4003), (4004), and / or (4005) are classified into possible categories, such as, but not limited to, “good,” “distorted,” and “unrecognizable.” Data not classified as “good” can be discarded or stored in a database for later manual review by an operator.

[0142] The training of iterations for performing quality control and monitoring, in a corrective, preventive, predictive, and / or prescriptive mode, of a piece of equipment (502) until the desired effect of quality control (2000) is achieved on the equipment (502) and / or the work (600), is classified into possible categories, in a non-limiting example, such as: “optimal,” “successful,” and “discardable.” Iterations not classified as “successful” can be discarded or stored in a database for later manual review by an operator.

[0143] The training for efficiently coupling analytics (506) classifies possible categories, such as, but not limited to, “correct,” “optimal,” and “discardable.” Couplings not classified as “optimal” can be discarded or stored in a database for later manual review by an operator.

[0144] Training for efficiently coupling the multiphysics model (400) classifies possible categories, such as, but not limited to, “successful,” “optimal,” and “discardable.” Couplings not classified as “optimal” can be discarded or stored in a database for later manual review by an operator.

[0145] The training for issuing Reports (1016) and / or Blockchain (1017) when applicable classifies possible categories, such as, but not limited to, “critical,” “alert,” “informational,” “low value,” and “negligible.” Links classified as “low value” can be discarded or stored in a database for later manual review by an operator.

[0146] The training for opening interaction instances and storing data of interest, using remote control (1014) and / or Virtual Reality (1015), classifies possible categories, such as "necessary" and "unnecessary." Interaction and data storage instances categorized as "unnecessary" can be discarded or stored in a database for later manual review by an operator.

[0147] The training of Machine Learning neural networks (1013), in a specific example, of the iterations of carrying out quality control and control, in a corrective, preventive or predictive way, of the operational components (503) and components (504) of the equipment (502) and / or the work (600) until achieving the desired effect, through quality control (2000) in a profile of the wear liner lifter of a SAG and / or ball mill, allows discarding “successful” iterations that are not “optimal”, that is, the false positives.The process assumes a series of input problems, based on one, several, or a combination of previously collected data, such as the intersection of the heat signature and the effective wear of a given mill, the programmed wear time, and the ideal comminution cascade; an algorithm establishes a series of possible RPMs while maintaining the transverse and longitudinal profiles of the SAG and / or ball mill; a series of simulations and iterations by the analytics (506) delivers 3D models in relation to the liner's angle of attack (see Figs. 20 and 21); an algorithm from analytics (506) weighs the comminution efficiency according to current (worn), historical, and reference 3D models from other campaigns, iterates these parameters with various RPMs of the mill's rotation unit (693) (650), and delivers a series of predictive 3D models with the optimal comminution cascade (900) based on "optimal", "correct", and "discardable" RPMs.Similarly, the training of Machine Learning neural networks (1013) is provided in the training: of the efficient coupling of analytics (506), of the efficient coupling of the multiphysics model (400), the issuance when appropriate of Reports (1016) and / or Blockchain (1017), opening of interaction instance and storing data of interest, by: remote control (1014) and / or Virtual Reality (1015).

[0148] In this realization, the Software (1009), Artificial Intelligence (1012) and / or the Reports (1016), execute a program to create a pattern to control quality and thereby control the operation, in a non-limiting example, such as: deciding to establish as a standard pattern the recovery of mineral at 5% Cu 2% Mo for a mining operation in the flotation area, or deciding to establish as a standard pattern an energy consumption of the grinding area of ​​3% less than the historical minimum.

[0149] In other implementations, the vehicles, equipment, and devices are adapted with radiation protection, allowing the system to be used to monitor construction projects in nuclear disaster zones. It can also be adapted to operate in low-pressure or vacuum atmospheres and in the presence of ionizing radiation, potentially enabling its use for monitoring construction projects on the Moon, Mars, or other locations beyond Earth.

[0150] Although it is stated that each module: actuator (300), standard pattern (250), analytics (506), multiphysics model (400), quality control (2000); works directly with the system (1000), it does not exempt each module from performing a specific task independently.

[0151] Detailed description according to figures.

[0152] To carry out the detailed description of the preferred embodiment of the invention, continuous reference will be made to the Figures in the drawings, of which Figure 1 is a block flow diagram of how the system (1000) of the following invention operates.

[0153] From a control base (1001) or company, a control request is received to improve the performance of an operation; where the operation includes: a process, a product, a piece of equipment, a work, complementary (or peripheral) equipment, components of these and / or operational components; communication is established with a control unit (100) in equipment (501); where the equipment (501) may include any vehicle, equipment or monitoring or inspection device, in any environment (land, air, above or below liquid surface); the equipment (501) collects multiple possible parameters in the operation, such as: dimensional, structural and physicochemical; the equipment (501) together with some sensors (70) of the equipment (501), an artificial vision (60) and / or metallurgical analyzer (80), build a database (4001);The database (4001) together with a database (4002), (4003), (4004) and / or (4005) are processed by an analytics (506) and a multiphysics model (400), and a quality control module (2000); where the quality control module (2000) relates a raised parameter with a pattern (200) and compares them with a standard pattern (250) that quantitatively and qualitatively establishes the deviation to actuate an actuator (300) and perform an effect on the operation; the quality control (2000) approves or rejects said parameter; if the parameter is approved “Y” it will execute an action on the actuator (300), if the parameter is “N” it does not perform an action; This approval is done through the control base (1001) which enables an IIoT (Industrial Internet of Things) actuator (1005) which drives the actuator (300);in one, several or a combination of any possible component of the operation, not limited to: equipment (501), gear (502), a work (600), complementary equipment (or peripherals), a component (503) and / or an operational component (504); analytics (506) includes: Software (1009), digital twin (1010), Cloud (1011), Artificial Intelligence (1012) and Machine Learning (1013); the multiphysics model (400) includes: point cloud (401), 3D modeling (402), DEM analysis (403), CFD analysis (404), FEA analysis (405) and DPM analysis (406); analytics (506) issues Reports (1016) based on control (1001); The analytics (506) is also assisted by remote control (1014) and Virtual Reality (1015) from the control base (1001); in parallel and throughout the entire operation chain, a reliable Blockchain traceability (1017) associated with it sends certified data from each stage of the system (1000) and actuator activation (300) on the operation.

[0154] The control base (1001) should be understood as the control instance that is operated from any enabled point, from a company, home, mobile device, remote manual control, or, in the case of the mining industry, in an integrated operations center, under physical and digital interaction, such as: VR (Virtual Reality), AR (Augmented Reality), MR (Mixed Reality), etc. In other embodiments, the control base (1001) adopts the direct control of at least one piece of equipment (501) to operate at least one actuator (300), in order to synchronize and coordinate equipment, a project, complementary (or peripheral) equipment, their components, and / or operational components, thereby optimizing the product and the process.

[0155] In a non-limiting example, the UAV takes the quality control data and parameters (2000) that were raised by the metallurgical analyzer (80) in the flotation discharge (641), the analysis (506) determines that the raised parameter of Cu is insufficient to make the operation profitable.The analysis performed a metallurgical balance of the product where the equations for metal content and grades of the ore, in this case Cu, were incorporated into the database. The value was compared with the London Metal Exchange database, and ROI (Return on Investment) was projected with the various iterations. In this way, the analysis creates scenarios and simulations to improve this rejected quality parameter. The analysis determines that the exploration of the ore in the quarry must be redirected. From the UAV, equipment (501), a series of actuators (300) are controlled in a series of UAVs and a drilling rig (663) beyond the loading face (639) or quarry of the operation, in order to detect improvements in the rock and a new mine to optimize the operation.

[0156] Figure 2: An aerial sounding vehicle (662) on the exploration face is controlled by the system (1000) by means of actuator (300). The aerial sounding vehicle (662) has a machine vision system (60) and a radiometrics-type Medusa gamma-ray sensor attached.

[0157] In Figures 2 through 20, M corresponds to a drive unit, without limitation, such as: a drive arrangement of one or a series of motors; direct current (DC) motors and alternating current (AC) motors; they may be linear or rotary actuators; they may be a combination of a series of linear actuators and rotary units; including gearboxes; motors: synchronous, asynchronous, servomotors and high-voltage motors; such as: gearless mill drives, from the company Innomotics; they may be mechanical, electric, hydraulic or pneumatic; for example, high-torque motors of the Maxon type; they may be for moving or providing a particular action of a vehicle or machine, for example: the electric motor to move a vehicle, in turn, the hydraulic linear actuator moves a hopper in said vehicle, or a 150 hp (110 kW) electric motor with pulley reducer, of 1784 RPM, for a mixer.

[0158] Figure 3: A drilling rig (663) at the loading face (639) or quarry is controlled by the system (1000) via actuator (300). The drilling rig (663) is equipped with a metallurgical analyzer (80), in this case, a BSA (Blast Hole Sampler-Analyzer) from IMA Engineering. This analyzer provides analysis and measurement data during drilling, collects samples and data from dense drill cuttings from production wells, and allows for the creation of accurate 3D maps of the blast benches. In other implementations, a NOMAD vehicle from Godelius, part of the Sigdo Koppers Group, is used. This vehicle has an integrated multi-sensor platform and can analyze various aspects of the samples, such as their chemical composition and mineral content.

[0159] Figure 4: At the loading face (639) or quarry, a shovel (661) for loading onto extraction truck (673) rock object (800), is controlled by the system (1000) by means of actuator (300).

[0160] Figure 5: A haul truck (673) transporting rock material (800) travels from the loading face (639) or quarry to a crusher (675), which is controlled by the system (1000) via actuator (300). Simultaneously, equipment (501), in this case a UAV, records parameters of the haul truck (673) and the surrounding environment, which is controlled by the system (1000) via actuator (300).

[0161] Figure 6: Similar to Figure 5, a haul truck (673) in transit travels from the loading face (639) or quarry to a plant, specifically a crusher (675). Simultaneously, equipment (501), in this case, a portal with machine vision (60), collects data on the haul truck (673) and its surroundings.

[0162] Figure 7: A crusher (675) in operation, where a haul truck (673) unloads rock material (800) into the crusher (675), which reduces the size of the rock material (800) and discharges it onto a conveyor belt (674) or apron feeders, which are controlled by the system (1000) by means of a series of actuators (300). This process equipment (502) and components (503) and the linings (651) are monitored by a series of machine vision (60) and sensors (70) collecting data and input parameters to the system (1000).

[0163] Figure 8: An operating ore stockpile (676), where a conveyor belt (674) feeds the ore stockpile (676) of rock material (800), and a discharge hopper (677) discharges it onto a conveyor belt (674) or apron feeders, which are controlled by the system (1000) by means of a series of actuators (300). These process equipment (502) and components (503) and the linings (651) are monitored by a series of machine vision (60) and sensors (70) collecting data and input parameters to the system (1000).

[0164] Figure 9: A mill (650) in operation, inside a closed process unit, longitudinal section of a stationary SAG and / or ball mill. FE is the feed at the inlet of the mill (650), and DE is the discharge at the mill (650) discharge into the trommel (666). FL is the theoretical fill level, and CL is the centerline of the rotating equipment. A feed hopper (664) supplies rock material (800) to the mill (650) next to a trommel (666). The drum casing (653) shows the material (801) balls and rock, the actual mill fill level (902), the liners (651), the pulp (901) on the liners, and the rotating unit (693). The feed hopper (664), the mill (650), and the trommel (666) are controlled by the system (1000) by means of a series of actuators (300).These process equipment (502) and components (503) and coatings (651) are monitored by a series of machine vision (60) and sensors (70) collecting data and input parameters to the system (1000).

[0165] Figure 10: A vertical mill (652) in operation, inside a closed process unit, longitudinal section. FE is shown as the feed, DE as the discharge, FL as the theoretical fill level, and CL as the centerline of the vertical rotating equipment, which is common to the vertical mill spindle (670) and, in this case, the object (801) – balls, rock, and pulp – the liners (651), the pulp (901) on the liners, and the rotating unit (693). The vertical mill (652) is controlled by the system (1000) by means of a series of actuators (300). This process equipment (502), components (503), and the liners (651) are monitored by a series of machine vision devices (60) and sensors (70), collecting data and input parameters to the system (1000).

[0166] Figure 11: An agitator (672) or mixer in operation, showing the blades (679) and the rotating unit (693). The agitator (672) or mixer is controlled by the system (1000) by means of a series of actuators (300). This process equipment (502) and components (503) are monitored by a series of machine vision devices (60) and sensors (70), collecting data and input parameters to the system (1000).

[0167] Figure 12: A conveyor belt (674) in operation, showing rollers (680) and the rotating unit (693), transporting a rock object (800). The conveyor belt (674) is controlled by the system (1000) by means of a series of actuators (300). This process equipment (502) and components (503) are monitored by a series of machine vision devices (60) and sensors (70), collecting data and input parameters to the system (1000).

[0168] Figure 13: An operating leaching unit (654), showing: a curing heap (655), a leaching heap (656), a PLS (Pregnant Leach Solution) pool (657), sprinklers (668), a centrifugal pump (686), and hot air lines (660). The operational component (504) is a liquid solution (sulfuric acid and water, hydrochloric acid, among others). The contents of the PLS pool (657) are fed by solvent extraction (658), and the PLS pool (657) is fed from a refining heap (659) and solvent extraction unit. The leaching unit (654) is controlled by the system (1000) using a series of actuators (300). The process equipment (502) and components (503) are monitored by a series of machine vision (60) and sensors (70) collecting data and input parameters to the system (1000).

[0169] Figure 14: An operating grinding circuit (500), showing: a conveyor belt (674), a mill (650) and its rotating unit (693), a ball feeder (683), a feed hopper (664), a mill (650), a trommel (666), a discharge hopper (665), a screen (684), a transfer tank (688), a centrifugal pump (686), a hydrocyclone battery (687), and a secondary ball mill (685). The operational components (504) include clean water lines, lime slurry lines, and others. Pebbles (644) is another process area corresponding to crushing.Where the rock object (800) comes from mine (640) to feed hopper (664), after comminution in mill (650) the classified rock object (800) passes to trommel (666) where water is added with a series of sprinklers (668), and then to the screen (684) where a part of rock object (800) with defined granulometry passes to transfer tank (688) and reject rock object (800) passes to pebbles (644). From transfer tank (688) the rock object (800) is sent to hydrocyclone battery (687) by means of centrifugal pump (686), where a part of rock object (800) with defined granulometry passes to flotation (641) and the rejection passes to secondary ball mill (685), also together with, and from recirculation (642) or review and from pre-crushing (643).The grinding (500), its circuits, lines, process equipment (502) and components (503) are controlled by the system (1000) by means of a series of actuators (300) and are monitored by a series of machine vision (60) and sensors (70) collecting data and input parameters to the system (1000).

[0170] Figure 15: A mill (650), cross-sectional view of its interior and rotating unit (693) at rest, with equipment (501), a machine vision system (60), and sensors (70) inside and outside. Here, MC is the mill center, FL is the theoretical filling level, 902 is the actual filling level of the mill, 651 is the mill lining (650), and 801 is the balls and rocks. The interior and exterior of the mill (650), the rotating unit (693), and the surrounding environment are monitored by a series of machine vision systems (60) and sensors (70), which collect data and construct databases (4001), (4002), (4003), and (4005). The mill (650) is controlled by the system (1000) using a series of actuators (300).

[0171] Figure 16: Mill (650) in motion, with intelligent control, where, in addition to Fig. 15, the cascade (900), cataract (904), charge foot (905), and comminution shoulder (908) are shown. A sensor (70) is part of the comminution cascade (900). The analytics (506), quality control (2000), control base (1001), and control unit (100) enable an IIoT (Industrial Internet of Things) actuator (1005) that drives a series of actuators (300).

[0172] Figure 17: Mill (650) in motion, with intelligent control, where, in addition to Fig. 15 and 16, a predominant waterfall edge (750) and a predominant cataract edge (751) are shown. This predominant geometry is the result of the analysis of the machine vision series (60) and the sensor series (70) using the analytics (506) and quality control (2000) of the system (1000). Figure 18: Mill (650) in motion, under intelligent quality control, where, in addition to Fig.Figures 15, 16, and 17 show the quality control (2000), the resulting geometry from multiparameter processing by analytics (506) using data collected from machine vision (60) and sensors (70): the trajectory (700) of balls and pulp in the cascade, the cascade start point (701), the cascade impact point (702), the start line (703), the attack line (704), the horizontal line (705) of the mill, angle A, which is the angle between the horizontal line (705) of the mill and the cascade start point (701), angle B, which is the angle of attack of the lining, distance Ll, which is the distance from the center of the mill to the cascade start point (701), and distance L2, which is the distance from the center of the mill to the cascade impact point (702).

[0173] Figure 19: This is a detail of Fig. 18, detail of the mill lining (651) (650), with intelligent control. Where, in addition to Figs. 15, 16, 17, and 18, the detail of the quality control of the geometry resulting from multiparameter processing by the analytical unit (506) is shown, using the collected data: the trajectory (700) of balls and pulp in the cascade, the cascade start point (701), the start line (703), and the attack line (704), which determine angle B, which is the angle of attack of the lining.Thus, in a non-limiting example, the system (1000) determines to increase the RPM in the mill's drive unit (650) by means of a series of actuators (300), in order to maximize the processing of ore based on the wear of the lining (651), pattern (200), until reaching the desired comminution, cascade effect and the KPIs required by the operation for the grinding area in said equipment, standard pattern (250), with the benefit that the comminution has been optimized and the operation extended, delaying the scheduled shutdown of the equipment without compromising operational efficiency and increasing operational continuity.

[0174] Figure 20: An operating flotation circuit (641), showing: a feed tank (689), a flotation battery (698) of flotation cells, a reactor (669), a flotation cell feed box (694), a flotation cell transfer box (695), a flotation cell discharge box (696), a flotation cell dart valve (697), a rotation unit (693), an impeller (681), a diffuser (682), a recirculation (642) or rework, a concentrate thickener (646), a tailings thickener (647), a chute (699), and linings (651). Where it is shown that FE., is the feed, to the feed box (694) of the flotation battery (698) of the flotation cells and DI., is the discharge, from the discharge box (696) that goes to tailings and also a DI., discharge in channel (699) of flotation battery (698) of flotation cells, which goes to concentrates.Where, from grinding (500) it feeds the feed tank (689) and operational components (504) include reagent and air lines, among others. Where OL is the Overflow Level, FT is the Froth Thickness, and CL is the Center of Line of the rotating unit (693). The interior and exterior of the flotation circuit (641), its equipment (502), components (503), operational components (504), and complementary (or peripheral) equipment are monitored by a series of machine vision systems (60), sensors (70), and a metallurgical analyzer (80), collecting data on the product, process, and equipment, which are used to build databases (4001), (4002), (4003), and (4005). The flotation circuit (641) is controlled by the system (1000) through a series of actuators (300).

[0175] Figure 21: A thickening (645) or sedimentation unit in operation, showing: a feed tank (689), a centrifugal pump (686), a thickener (671) or sedimentation equipment: a thickener, a clarifier, or a sedimentation tank, a rotary unit (693), a feedwell (692), rakes and scrapers (678), a reclaimed water pool (690), and a discharge box (691). Process water (648), filter plant (649), and a feed tank (689) are illustrated. FE is the feed from flotation (641), and operational components (504) are connected to the feedwell (692). OL is the overflow level (DI). It is the upper discharge of the thickener (671) that goes to the recovered water pool (690) and then to process water (648), while DI.In the lower discharge of the thickener (671) that goes to the discharge box (691) and then to the filter plant (649), and CL is the Center Line of the rotating unit (693). Where CW is a Clarified Water Layer, S is a Sedimentation Layer, and CB is a Compressed Bed Layer. The operational components (504) are flocculant lines, collectors, modifiers, frothers, among others. The interior and exterior of the thickener (645), its equipment (502), components (503), operational components (504), and complementary (or peripheral) equipment are monitored by a series of machine vision systems (60), sensors (70), and metallurgical analyzers (80), collecting data on the product, process, and equipment, which are used to build databases (4001), (4002), (4003), and (4005). Thickening (645) is controlled by the system (1000) by means of a series of actuators (300).

[0176] Experts in the field will understand that the foregoing refers only to a preferred embodiment of the invention, the description of which focuses on the core of the system and methods, and therefore there are a number of details not shown and certainly omitted that mechanical, robotic, hydraulic, pneumatic, electrical, electronic and computer techniques allow today to be achieved without much effort; these are normal engineering problems that are well known to experts in the field, and will not be explained in more detail in this document.

[0177] Experts in the field will also understand that the foregoing refers only to a preferred embodiment of the invention, which is subject to modification without departing from the scope of the invention, as defined by the claims that follow.

Claims

CLAIMS:

1. A method for controlling and optimizing an operation involving one, several, or a combination of equipment (502), a work (600), complementary (or peripheral) equipment, a component (503), and / or an operational component (504), based on one, several, or a combination of possible multi-parameters of operational quality, a pattern (200), in a corrective, preventive, predictive, and / or prescriptive manner, until the desired effect is achieved in accordance with a standard pattern (250), a quantitative property, a qualitative, operational, or financial property, such as: ROI (Return on Investment), mineralogy, concentrate grade, ore hardness, RPM (Revolutions Per Minute), comminution cascade, angle of attack of a mill liner lifter, liner thickness, by controlling one, several, or a combination of the equipment (502), the work (600),Complementary (or peripheral) equipment, components (503) and / or operational components (504); such equipment (502) may be: concentric or eccentric rotary, static, mobile, carry out a process, may be in operation or stopped, motorized and non-motorized, open, semi-closed and / or closed, which may be independent, several linked or several alternated, in a series, in a part or complete of a process line or production line, any equipment: equipment, machine, device, vehicle, autonomous vehicle, robot, robotic cell, device, not limited to, such as: horizontal mill, vertical mill, a reactor, a flotation cell, a column cell, Jameson cell, a flotation battery, a centrifugal pump, a hydrocyclone battery, a crusher, conveyor belt or apron feeders, an agitator or mixer, a grinding or regrinding mill circuit, a gas scrubber,a dust filter, sedimentation equipment: thickener, clarifier or a sedimentation tank; a work (600) such as: an industrial work, a production line, a mining operation, underground mining, a concentrator plant, the process and its products; complementary (or peripheral) equipment, such as: an actuator, a vehicle, a crane, a drone, a robotic arm and / or a robot for handling, drilling, a specific predefined or multitasking task, a transfer, feeding or discharge hopper, a structure and any component thereof; operational components (504), such as: particle size, density (of pulp), size of grinding media, process media, such as grinding media (balls, rods), temperature, filling level, feed and discharge flow of: the product, process material, clear water or process water, flocculant, etc.; and where the product can be any matter and its states or phases of aggregation: organic and inorganic matter, chemical compound, organic and inorganic, mineral, chemical element, rocks, pulp, sludge, organisms, living or dead beings, animals (including meat), vegetables, drugs, food, fish, compounds, simple and compound substances, an electronic component, an electronic artifact, a device, a drone, a vehicle, a machine, a weapon, a ship, a robot, a dwelling; the operation on land, in the air, on liquid and / or under liquid, can be: industrial, mining, oil and gas, automotive, aerospace, naval, military, pharmaceutical, chemical, energy, robotics, and also applied for training, instructional and educational purposes, CHARACTERIZED because at a first level a method is provided that comprises the following steps:. a) in a piece of equipment (502) and / or of the work (600) have at least: a location and communication unit (50) and a control unit (100), some equipment (501), a series of sensors (70), an artificial vision (60) and / or a metallurgical analyzer (80); where the equipment (501) includes one, several, or a combination of: a UAV (Unmanned Aerial Vehicle), such as the Elios 3 UT Payload flyability system, a UGV (Unmanned Ground Vehicle), an AGV (Automated Guided Vehicle), a Rover (referring to an unmanned vehicle specially configured to explore the terrain of a planet or other celestial body other than Earth), a USV (unmanned surface vehicle), a UUV (unmanned underwater vehicle),which means “unmanned underwater vehicles”) and / or an ROV (acronym for “remotely operated vehicle”, which means a remotely operated vehicle that is controlled by a human operator who is not physically inside the vehicle), a quadruped robot such as Boston Dynamics' Spot, a biped robot such as Agility Robotics' Digit, a humanoid robot such as Boston Dynamics' Atlas, Tesla's Optimus or NASA's Valkyrie and / or an operator manipulating a scanner such as the FARO® Orbis mobile scanner; b) storing and processing the parameters, pattern (200), by means of the control unit (100), and sending the parameters and data by means of a Wi-Fi link from the location and communication unit (50) to a Software (1009), which processes the database (4001), a database (4002), a database (4003), a database (4004) and / or a database (4005); the control unit (100) may be a distributed control system (DCS); wherein the database (4001) includes 3D models and historical data of: the sensors (70), machine vision (60), metallurgical analyzer (80) and the equipment (501); the database (4002) includes 3D models and historical data of: the equipment (502), component (503), operational components (504), operational variables, process media, such as grinding media (balls, rods); The database (4003) includes 3D models and historical data of: the work (600), the process and the product;The database (4004) includes 3D models and historical data of: quality control parameters (2000); and / or the database (4005) includes 3D models and historical data of: actuators (300) and complementary (or peripheral) equipment; wherein the actuators (300) act on any of the operational components (503) and / or components (504) in the equipment (502), the work (600), the process or the process media, such as the grinding media (balls, rods) in the grinding (500); they can be configured to communicate with a distributed control system (DCS) via a bus or network; c) define and / or predefine a standard pattern (250) using Software (1009); d) control the quality of at least one, several, or a combination of multiple possible parameters, by means of a quality control module (2000) of the equipment (502) and / or the work (600); as in horizontal grinding (500), compare the database (4001) of sensors (70) and metallurgical analyzer (80) of the equipment and the database (4002) of the 3D models of the equipment and the online process, determining: the trajectory (700) of balls and pulp of the cascade, the point (701) of cascade start, the point (702) of impact, the line (703) of start, line (704) of attack, the angle A between the horizontal line (705) of the mill and the point (701) of cascade start, the angle B of attack of the lining, the distance L1 from the center of the mill to the point (701) of cascade start, the distance L2 from the center of the mill to the point (702) of impact, the predominant edge (750) of the cascade and the predominant edge (751) of the cataract; e) compare, approve or reject a pattern (200) with a predefined standard pattern (250) of the quality control (2000) of a piece of equipment (502), a work (600), a complementary piece of equipment (or peripherals), a component (503) and / or an operational component (504), by means of the Software (1009), in a non-limiting example, such as the path (903) of the cascade (900) of the grinding (500); If quality control (2000) rejects a defined parameter, then an alert is issued to the control base (1001) and corrective, preventive, predictive and / or prescriptive action is performed, and in such a way that an IIoT actuator (1005) is executed on one, several or a combination of the actuator (300) in any equipment: equipment, machine, artifact, vehicle, autonomous vehicle, robot, robotic cell, device, of the equipment (502), such as, but not limited to: a valve, a motor, a gate; pneumatic, rotary piston pneumatic, balancing diaphragm, motorized or hydraulic;a solenoid valve for the inlet of process water or pressurized air, a power variable frequency drive on a drive system or dosing pumps for flocculant feeding, a discharge gate for balls from the feed hopper; an actuator, a vehicle, a crane, a drone such as: UGV (from the English “Unmanned Ground Vehicle” which means unmanned ground vehicle), Rover (refers to an unmanned vehicle specially configured to explore the terrain of a planet, or other celestial body other than Earth), UAV (from the English “Unmanned Aerial Vehicle” which means unmanned aerial vehicle), USV (acronym for the English “unmanned surface vehicle”, which means “unmanned surface vehicle”), UUV (acronym for the English “unmanned underwater vehicle”, which means “unmanned underwater vehicles”); and / or a robotic arm, a robot, a humanoid robot or a quadruped robot, for: manipulation, sounding, a specific predefined task or multitasking;on land, in the air, on liquid and / or under liquid, until the desired effect is achieved, standard pattern (250), on the equipment (502); f) execute an analytics (506) that includes: a Software (1009), a Cloud (1011), Reports (1016) and a remote control (1014), which they acquire; g) at a first level, integrate the databases (4001), (4002), (4003), (4004) and / or (4005) and feed the Software (1009), which executes by means of an algorithm the optimization in a corrective, preventive, predictive and / or prescriptive manner, in the equipment (502), until achieving the desired effect and / or operation in the equipment (502).

2. Method for controlling any component of an operation, CHARACTERIZED in that at a second level, it includes the step: a) integrate the databases (4001), (4002), (4003) (4004) and / or (4005) feed and run the Software (1009) and an Artificial Intelligence (1012).

3. Method for controlling any component of an operation, CHARACTERIZED in that at a third level, it includes the following steps: a) integrate databases (4001), (4002), (4003), (4004) and / or (4005) and build a digital twin (1010); and b) couple and run a multiphysics model (400), linear and nonlinear, multispecies or multiphase flow modeling (physical states of matter solid, liquid and gaseous), which is achieved by at least the import of a point cloud (401) and a scenario in a 3D model (402) and which includes analysis of one, several or a combination of multiple possible aspects, such as structural, mechanical, fluid-mechanical, immiscible fluids (e.g., water and oil), non-Newtonian materials, electromagnetic, chemical, temperature, turbulence, heat transfer, chemical reactions, aeroacoustics, turbomachinery, fluid flow;to couple and execute one, several or a combination of the modules: DEM analysis (Discrete Element Method) (403), and / or CFD analysis (Computational Fluid Dynamics) (404), such as fluid dynamic analysis, such as Ansys Chemkin-Pro, and / or FEA analysis (Finite Element Analysis) (405) and / or DPM analysis (Discrete Phase Model) (406).; 4. Method for controlling any component of an operation, CHARACTERIZED in that at a fourth level, it includes the step: a) integrate the databases (4001), (4002), (4003), (4004) and / or (4005) and build a Virtual Reality (1015), which includes at least the construction of a simulation scene Human-computer interfaces: VR (Virtual Reality), AR (Augmented Reality) and / or MR (Mixed Reality); which acquire gestural remote control, Mixed Reality and AI (Artificial Intelligence), with a holographic device of the Microsoft HoloLens 2 type glasses, through the integration of motors of the Evergine 3D motor type, Holo-Robot of Plain Concepts.

5. Method for controlling any component of an operation, CHARACTERIZED in that at a fifth level, it includes the step: a) integrate the databases (4001), (4002), (4003), (4004) and / or (4005) and build a Blockchain (1017), using a Ledger system that stores all data transactions, as a design parameter resulting from the Software (1009) and / or an Artificial Intelligence (1012), which creates at least one Report (1016), one or more of multiple possible notifications and / or reports, to the control base (1001), and where the control base (1001) has or determines who has a Wallet, which is a digital interface that allows sending, receiving and storing digital assets securely, where the entire process is certified and audited by generating NLTs (Non-Fixable Tokens) which are unambiguous representations of assets, both digital and physical.It uses JS, Solidity and HTML languages; it issues corrective, preventive, predictive and / or prescriptive reports.

6. Method for controlling any component of an operation, CHARACTERIZED in that at a sixth level, it includes the step: a) integrate the databases (4001), (4002), (4003), (4004) and / or (4005) and build the digital twin (1010) using Machine Learning (1013) (which means “automatic learning”), makes decisions and / or makes predictions, and which acquires supervised, unsupervised, semi-supervised and / or reinforcement learning algorithms; and which can acquire a CNN (abbreviation CNN or ConvNet, from the English “Convolutional Neural Network” which means “Convolutional Neural Network”) deep learning algorithm, as in an example not limiting, for object recognition, such as classification, detection and segmentation of images and 3D models.

7. Method for any component of an operation, CHARACTERIZED in that it comprises the following steps: a) obtaining one, several, or a combination of multiple possible parameters from, a piece of equipment (502), a work (600), the complementary (or peripheral) equipment, components of these and / or the operational components, pattern (200), by means of: the sensors (70), the machine vision (60), the equipment (501) and / or a metallurgical analyzer (80); b) identify at least one pattern, pattern (200); not limited to, physical operational, such as: dimensional, 3D surface comparison, surface finish, visual, thermographic, acoustic, temperature, humidity, vibrations; not limited to, operational financial: KPI (Key Performance Indicator), NPV (Net Present Value), EBITDA (Earnings Before Interest, Taxes, Depreciation and Amortization), ICF (Instant Cash Flow); using Software (1009); c) build a database (4004) of quality control parameters, and predefine and establish standard pattern (250); d) contrast the parameter, pattern (200) with one, several or a combination of standard patterns (250); e) correlate the pattern (200) with a defined position of a team (502) and / or a work (600) using the Software (1009); f) determine qualitatively and quantitatively how far the pattern (200) is from the standard pattern (250), using the Software (1009), according to database (4001), (4002), (4003) and / or (4005); g) send a report and / or an alert of the results to quality control (2000), and establish whether “Y” is correct and “N” is incorrect, h) If “N” is incorrect, send a notification to the control base (1001), and re-execute steps b), d), and f). (i) operate an IIoT (Industrial Internet of Things) actuator (1005) of the actuators (300) to control one, several, or a combination of any equipment: equipment, machine, artifact, vehicle, autonomous vehicle, robot, robotic cell, device, without limitation, such as: equipment (502), a work (600), complementary (or peripheral) equipment, components thereof and / or operational components; without limitation, such as: an actuator of a gate in a ball feeder (683) and a rotary unit (693) for the drum casing (653) of a mill (650); a rotary unit (693) of the impeller (681) and the valve in the air line of a reactor (669) flotation cell; a rotary unit (693) of the rake and scrapers (678) and a valve for the flocculant line in a thickener (671); a valve in the solution line for sprinklers (668) of a curing heap (655) in leaching (654); and achieve a satisfactory quality parameter; and j) if “Y” is correct, send notification to the control base (1001), and; k) execute in each operation of the chain of operations in all the previous steps, a notification and certificate by Blockchain (1017) issued to the control base (1001).

8. A system (1000), according to any of claims No. 1 to No. 7, CHARACTERIZED in that if there is a deviation from the standard (200), the analysis (506) is executed, which includes software (1009) to operate one, several, or a combination of actuators (300) in one, several, a combination, and as many as necessary of equipment (502) and / or a work (600), to correct the deviation from the standard (200) and achieve a standard standard (250), such as, but not limited to: a low concentration of a certain mineral in the flotation circuit (641): a protocol is enabled to mobilize a drilling rig (663) by means of an actuator (300) in the drive system and by means of a metallurgical analyzer (80) determine a richer exploitation area of ​​a certain mineral, operate a shovel (661) to load at the defined site, load a haul truck (673) to the crusher (675), which is then transported by conveyor belt (674) and by metallurgical analyzer (80) take an appropriate batch, passing through grinding (500) and achieve the mineral and mineral value in the metallurgical analyzer (80) in the feed and discharge of the flotation battery (698) of flotation cells. 9.- A system (1000), according to any of claims No. 1 to No. 7, CHARACTERIZED in that it can add, subtract, replace and / or create one or a series of pattern (200) and / or the standard pattern (250) by means of the Software (1009), an Artificial Intelligence (1012) and / or Machine Learning (1013). 10.- A system (1000), according to any of claims No. 1 to No. 7, CHARACTERIZED in that the pattern (200) and / or the standard pattern (250) may consist of any possible physical, operational and / or productive quality parameter, without limitation, such as: a KPI (Key Performance Indicator), a mineralogy, a concentrate grade, a mineral hardness, an RPM (Revolutions Per minute), a comminution cascade, an angle of attack of a mill liner lifter, and / or a liner thickness. 11.- A system (1000), according to any of claims No. 1 to No. 7, CHARACTERIZED in that the pattern (200) and / or the standard pattern (250) may consist of any possible quality parameter, operational, productive and / or financial, without limitation, such as: an NPV (Net Present Value), an EBITDA (Earnings Before Interest, Taxes, Depreciation and Amortization), an ICF (Instant Cash Flow), and / or an ROI (Return on Investment).

12. A system (1000), according to any of claims No. 1 to No. 7, CHARACTERIZED in that the control can be commanded from the control unit (100) of any of the equipment (501) such as, one, several or a combination of: a UAV, a UGV, a Rover, a USV, an ROV, a quadruped robot such as Boston Dynamics' Spot, a biped robot of the Digit type from Agility Robotics and a humanoid robot of the Atlas type from Boston Dynamics, Tesla's Optimus or NASA's Valkyrie; the control unit can be commanded from the control base (1001), telecommand (1014), Machine Learning (1013) together with a distributed control system (DCS), a tablet or a smartphone.

13. A system (1000), according to any of claims No. 1 to No. 7, CHARACTERIZED in that the databases (4001), (4002), (4003), (4004) and (4005) are at least one parameter, several and / or a combination of a series of multiple possible parameters: of the environment, such as: land, water, liquid, air, sea; of the infrastructure, such as: factory, concentrator plant, grinding area; of a process line, such as: recirculating and regrinding mills, flotation cell bank; of equipment, such as industrial equipment; of a component, such as: parts and pieces of those described above, electronic, mechanical, biological, composite, coating, nanoparticle, linings, cladding, coating, heat treatments, surface finish and paints;characteristics or patterns, such as: size, length, materials, weight, arrangement and / or disposition, the geometry of the profile in the lifter, physical, chemical, mechanical, biological properties; and / or process media, such as: pulp, rocks and grinding media (balls, rods); possible collected parameters or data: physical, structural, mechanical, chemical, biological, inorganic and organic parameters; in a non-limiting example, such as, in the case of the mill (650): the infrastructure in the concentrator plant, the equipment upstream and downstream of the mill (650), pulp mineralogy (901), a lining (651), the grinding media (balls, rods), grate, pads and their grooves; of the operation in operational terms, such as: the UNE-EN ISO 17637 Standard Visual examination of fusion welded joints;in terms of the product and the process, such as: the percentage of Cu and Mo admissible in a flotation plant, the mass and energy balance, material balances, metallurgical balance of a process; and of the financial operation, such as: a KPI (Key Performance Indicator), an NPV (Net Present Value), an EBITDA (Earnings Before Interest, Taxes, Depreciation and Amortization); amortization” of the Company), ICF (Instant Cash Flow), balanced scorecard (BSC, Robert Kaplan and David Norton), operational scorecard (CMO, Robert Kaplan and David Norton), CapEx (Capital Expenditures), OpEx (Operational Expenditure), the price of ore in dollars per metric ton, London Metal Exchange database, daily and monthly, For example, the flotation balance: Grade, Feed Grade, Concentrate Grade, Tailings Grade, operating index, metallurgical recovery, yield, concentration ratio, enrichment ratio; for example, the KPIs of the Flotation area: Plant Recovery, Treatment (TpH), F80, Concentrate Grade;The KPIs of the Grinding area: Treatment (TpH), P80, F80, Available time of the mills involved, Resting pressure, Mineral hardness, the admissible recovery percentage required to be obtained in the Cu and Mo plant.; 14.- A system (1000), according to any of claims No. 1 to No. 7, CHARACTERIZED in that the databases (4001), (4002), (4003), (4004) and (4005) can be accessed, strengthened, acquired or coupled to additional databases external to the operation, by means of: the control base (1001), Software (1009), remote control (1014), Machine Learning (1013) and / or Virtual Reality (1015); external databases, not limited to: London Metal Exchange, any type of: standard (for example, UNE-EN ISO Standard), KPI (Key Performance Indicator), CapEx (Capital Expenditures), OpEx (Operational Expenditure). 15.- A system (1000), according to any of claims No. 1 to No. 7, CHARACTERIZED in that by means of: the control base (1001), Software (1009), remote control (1014), Machine Learning (1013) and / or Virtual Reality (1015), it can be coupled to other monitoring, administration or management software, not limited to: ERP (Enterprise Resource Planning), BIM (Building Information Modeling), Autodesk Construction Cloud (ACC), machine monitoring, of the type, OPTIME from Schaeffler; remote operation of machinery, of the type, TeleOp, from Hexagon, or monitoring of the type HxGN APM. 16.- A system (1000), according to any of claims No. 1 to No. 7, CHARACTERIZED in that at least one of the sensors (70), the metallurgical analyzer (80), the machine vision (60), and / or the equipment (501), collects one, several or a combination of possible parameters that are processed by a Software (1009) and that actuates at least one IIoT (Industrial Internet of Things) actuator (1005) of the actuators (300) to control at least one, several or a combination of: a piece of equipment (502), a work (600), a complementary piece of equipment (or peripherals), a component (503) and / or an operational component (504), such as: RPM or direction of rotation of a drive unit, of a rake and scrapers (678), of blades (679), of an impeller (681); ball or rod filling level, feed and / or discharge speed of process media (balls or rods), clean water, process water, air, flocculant;any equipment: equipment, machine, artifact, vehicle, autonomous vehicle, robot, robotic cell, device, not limited to.; 17.- A system (1000), according to any of claims No. 1 to No. 7, CHARACTERIZED in that at least one of the sensors (70), the machine vision (60) and / or the equipment (501), raises one, several or a combination of parameters that are processed by a Software (1009) and that actuates at least one IIoT (Industrial Internet of Things) actuator (1005) of the actuators (300) to control a piece of equipment (502), a work (600), a complementary piece of equipment (or peripherals), a component (503) and / or an operational component (504);in a closed processing unit, such as a vertical mill (650) and mill (652), controls at least one of its operational components (504), such as: process water, percentage of solids, ball charge, ball size, rotation speed and critical speed, as a function of components (503) and / or other operational components (504), such as: a thickness of liners, angle of attack and thickness of a liner lifter, the geometry of the profile on the liner lifter, the lifespan of the profile on the liner lifter, ball filling level, RPM according to the geometry of the profile on the lifter, RPM of the unit as a function of the lifespan of the profile on the lifter, RPM of the unit as a function of the grinding media;in a semi-closed processing unit, such as a reactor (669), flotation cell, Jameson cell and column cell, controls at least one of its operational components (504), such as: air, pH or Redox (ORP), musical measurement, density, speed, bubble size and consistency, as a function of components (503) and / or other components; operational components (504), such as: impeller lining thickness and inner mantle linings; in a semi-closed processing equipment, such as a thickener (671) sedimentation equipment: thickener, clarifier, or a sedimentation tank, controls at least one of its operational components (504), such as: flocculant, clear water level, pH, turbidity, solids concentration, based on process components (503) and media, such as: lining thickness in troughs, sediment thickness in equipment. 18.- A system (1000), according to any of claims No. 1 to No. 7, CHARACTERIZED in that the actuators (300) of the equipment (502) and / or of the work (600) are controlled by the quality control module (2000) based on at least one metallurgical analyzer (80) located before and / or after a process, such as, before entering the grinding area (500), to a mill (650), after the grinding area (500), before entering the flotation area (641), to a reactor (669) or a flotation battery line (698) and / or after flotation (641); and arranged such as: on a belt, which is spliced ​​to a pipeline or pipe, on a vehicle, on a drilling tool or on any stationary or mobile sampling vehicle or unit.

19. A system (1000), according to any of claims No. 1 to No. 7, CHARACTERIZED in that at least one of the sensors (70), the metallurgical analyzer (80), the machine vision (60), and / or the equipment (501), performs the acquisition of at least one, several, or a combination of parameters or data collected from a series of multiple possible parameters or data collected: from the environment, such as: soil, water, liquid, sludge, acid mist, tailings, air, sea; from the infrastructure, such as: factory, concentrator plant, grinding area; from a process line, such as: series and regrinding mills, recirculating, flotation cell bank; from equipment, such as: industrial equipment, a device, a mass consumer product, a vehicle, a robot;of a component, such as: parts and pieces of those described above, electronic, mechanical, biological, composite, coating, nanoparticle, lining, cladding, coating, heat treatments, surface finish and paints; characteristics or patterns, such as: size, length, materials, weight, arrangement and / or disposition, the geometry of the profile on the lifter, physical, chemical, mechanical, biological properties; and / or; Process media, such as: pulp, rocks, grinding media (balls, rods), packaging, an electronic item, biological material, manufacturing input, waste; possible collected parameters or data: physical, structural, mechanical, chemical, biological, inorganic and organic parameters; such as: geometric, 3D dimensions and surface, surface finish, material thickness, paint and coating thickness, weld cracks, oxidation level, temperature, distance, acceleration, vibration, pressure, load, liquid currents, atmospheric pressure, liquid level, liquid pressure, position, speed and acceleration of moving objects, salinity, carbon dioxide CO2, dissolved oxygen O2, pH acidity, mass, density and viscosity of liquids and gases (Coriolis mass flow meter), liquid velocity, electrical conductivity, total dissolved solids (TDS), nitrites NO2, nitrates NO3, ammonium NH4, calcium, potassium, metal ions,Chlorides, Free and Total Chlorine, Copper, Chromium, Nickel, Iron, Silica, Bromine, Manganese, Magnesium in seawater, Phosphate in seawater, Fluorides, Phosphorus in seawater, Water color, speed and direction of wind and liquids, humidity, vibrations, audiometry, odors, concentrations of volatile organic compounds in air, density of solids and turbidity in liquid media, concentration of minerals in solids, rocks, dust, liquids, pulp or tailings, Ammonia gas (NH3), hydrochloric acid, nitrogen dioxide and / or hydrogen sulfide (H2S), contaminants, toxicity, viruses and bacteria, biosensors, virus and bacteria sensor, photonic sensor for contaminants, optical biosensors for toxicity, fluorometers for chlorophyll parameters, photometers, radiometric sensors (radiation detector), photometric sensors (light source and detector),electromagnetic (source and detector or induced potential) or more high-energy electromagnetic sources / detectors such as X-ray source types (fluorescence or transmission) or gamma-ray source; includes at least one microphone, one gyroscope sensor and / or one accelerometer and an IMU (Inertial Measurement Unit); for sedimentation equipment to check the sludge blanket level, such as: Sludgewatch 715 portable sludge blanket gauge, Partech, which uses a range of infrared sensors, which detect the sludge interface and PUA SmartDiver from PUA Process Analysers, a self-submersible sludge probe that collects suspended solids and density data; the metallurgical analyzer (80) such as: SamStat-30 type sampling stations, an AnStat-220 sampling station, which performs the analysis of the mineral composition (Cu, Mo, Fe, etc.) of the pulp based on X-ray fluorescence, a multi-flow analyzer,of the Analyzer type, Elemental analysis of pulps by XRF, MSA Mk5.2 Multi-Flow, which performs the mineral composition analysis (Cu, Mo, Fe, Sol.), a Thermo Scientific™ PSM-400MPX type ultrasonic attenuation particle size monitor, to determine p80 handling between 290 and 25 microns, and pulp density or percentage of solids and / or reverse sampling stations, of the SamStat-30R type; and as such, to measure the elemental composition of bulk materials on a conveyor belt, the Fast Conveyor Analyzer from IMA Engineering uses XRF technology; and a gamma ray sensor of the Medusa Radiometrics type.

20. A system (1000), according to any of claims 1 to 7, CHARACTERIZED in that at least one of the sensors (70), the metallurgical analyzer (80), the machine vision (60), and / or the equipment (501), performs the acquisition of at least one, several, or a combination of parameters or data collected from a series of multiple possible parameters or data collected: a LiDAR system (Laser Imaging Detection and Ranging), a 3D camera, multispectral cameras, hyperspectral cameras, a series of high-resolution, high-speed thermal imaging cameras, a 3D ToF camera (time-of-flight), a series of multidirectional cameras, a set of high-power LEDs, radar (acronym for RADAR,“radio detecting and ranging” (which means “detection and measurement of distances using radio waves”) high definition and a laser pointer, RGB and multispectral cameras, a hyperspectral camera such as the HySpex Baldur V-1024 N® and / or a LiDAR, such as Ouster OSO®, or a high-bandwidth stereoscopic depth camera, such as the Intel® RealSense™ D457 depth sensor camera.

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