Artificial intelligence-based system for sorting and remelting aluminum scrap with closed alloy control and distributed traceability

Abstract

A system for sorting aluminium scrap, controlled remelting, regulating alloy composition and traceable material processing, comprising: a scrap identification unit equipped with a sensor arrangement housed in a closed inspection chamber, wherein the sensor arrangement is designed to detect optical, electromagnetic, thermal and surface structural properties of individual aluminium scrap fragments transported on a conveyor system; a classification processor that is operationally coupled with the scrap identification unit and is configured to generate routing instructions based on the detected scrap characteristics; a deflection device with mechanically operated gates, which are arranged next to the conveyor system and serve to direct classified scrap into designated containers; a raw material processing device comprising a comminution device, a volumetric dosing device and a power cell controlled hopper arrangement, wherein the raw material processing device is configured to feed controlled quantities of sorted scrap to a remelting reactor; The remelting reactor consists of a refractory-lined melting chamber with integrated heating elements, an environmental insulation structure and a furnace control processor configured to regulate temperature profiles depending on the scrap properties and target alloy specifications; an in-situ composition analyzer for molten metal, consisting of a sampling port extending into the melting chamber, a fiber optic detection unit, a spectral measuring device and a composition processing unit configured to determine the chemical composition values ​​of the molten metal in real time; an alloy correction device comprising a multi-chamber storage arrangement for correction materials, a set of motor-driven metering mechanisms and a metering processor configured to introduce precise amounts of correction material into the melting chamber based on the chemical composition values; a casting discharge structure configured to transport chemically matched liquid metal to downstream forming equipment; and a traceability processor configured to generate a tamper-proof, chronologically linked data set that includes scrap identification data, furnace operating parameters, composition measurements, alloy correction transactions, and casting discharge data.

Description

TECHNICAL FIELD

[0001] The invention relates to industrial metallurgical plants and automated process control systems, in particular a hardware-integrated device for the high-precision sorting, remelting, alloy composition regulation, and distributed traceability of aluminum scrap. The invention falls within the fields of recycling machinery, instruments for molten metal chemistry, mechatronic automation, and digitally verifiable material origin documentation. BACKGROUND OF THE INVENTION

[0002] Conventional aluminum scrap recycling relies heavily on manual sorting, imprecise thermal processes, and offline analysis methods. These steps lead to significant variations in scrap purity, residual impurities, and the composition of the molten metal. Imprecise alloy formation during remelting increases the demand for primary metals, raises energy consumption, and reduces the consistent manufacturability of cast or extruded aluminum products. Existing systems also lack reliable documentation of scrap origin, chemical transformations, energy consumption, and material output. The absence of real-time control loops for alloy correction leads to deviations from target specifications, resulting in rejects and process inefficiencies.The uploaded reference specification shows that current technologies suffer from these limitations, particularly regarding scrap classification, adaptive melt control, and complete traceability along the recycling chain. To address these issues, the present invention proposes an integrated hardware device that combines advanced scrap identification, thermal processing, alloy balancing, and verifiable data logging.

[0003] Aluminum scrap recycling has long relied on a combination of manual processes, semi-automated sorting systems, and furnace-based processing systems. Each of these methods has fundamental weaknesses that negatively impact efficiency, alloy accuracy, and sustainability. Common industrial practice begins with crude sorting methods that depend heavily on the operator's visual assessment and experience. These methods roughly group scrap pieces based on appearance, magnetism, or simple density differences. Such methods are inherently subjective and cannot reliably detect subtle differences between wrought and cast alloys, coatings, residual impurities, multilayer structures, and alloy families with tight compositional tolerances.Mechanical pretreatment processes such as crushing, eddy current separation, and magnetic separation improve throughput but still do not provide the necessary analytical resolution to reliably separate aluminum grades that differ only in the trace amounts of magnesium, silicon, zinc, or copper. Handheld spectrometric analyzers, while providing more accurate readings, require manual operation, visual contact with each individual scrap fragment, and are impractical for large-scale industrial plants with continuous flow. As a result, the recycling scrap streams entering the furnaces are often heterogeneous, leading to unpredictable melt chemistries, higher levels of impurities, and alloy variations that must later be corrected by costly additions of primary metal.

[0004] Once scrap metal enters the melting phase in existing plants, operational complexity increases due to highly variable impurity levels and inconsistent scrap composition. Conventional remelting furnaces typically operate with approximate temperature controls and rely on operator judgment of the melting progress. The lack of high-resolution, real-time monitoring means that furnace conditions cannot dynamically respond to changing properties of the incoming scrap. This can lead to overheating, excessive oxidation, the formation of undesirable intermetallic phases, or inefficient flux delivery, all of which contribute to metal losses in the form of slag.Because conventional furnaces do not make decisions based on real-time feedback of the chemical composition, operators often wait until the melt is complete to take periodic samples for spectrographic laboratory analysis. These offline checks are inherently slow, meaning that process corrections are made only after deviations have occurred. Such delays require operators to add significant amounts of master alloys or expensive primary aluminum to correct the melt composition, resulting in material waste and increased operating costs.

[0005] Existing alloy correction strategies are reaching their limits because the furnace control system lacks predictive mechanisms that take the composition into account. When operators compensate for deviations from the alloy, they typically rely on experience or guesswork rather than systematically calculating the dosage. For example, if the magnesium content is below the target value, the operator estimates the required amount of magnesium-rich alloy. However, without precise knowledge of the melt volume or assurance of a uniform distribution, correction attempts often result in over- or under-deliveries. Repeated corrections degrade alloy homogeneity, increase melting time, and waste heating energy.Furthermore, conventional systems cannot account for oxidation losses of the scrap, variations in the burning off of impurities, or the dynamic thermochemical behavior of different scrap categories. Therefore, even after corrective additions, the final alloy composition may fall outside the permissible tolerances, necessitating rework or downgrading the melt to a lower-grade alloy category.

[0006] Another significant drawback of existing aluminum recycling infrastructures lies in the lack of integrated data capture and traceability mechanisms. Most facilities maintain records manually or via separate software systems isolated from the physical equipment. Scrap origin, composition, furnace performance parameters, alloy correction measures, and environmental data are often recorded retrospectively, are prone to manual transcription errors, or are not documented at all. This results in incomplete or unverifiable datasets and hinders the certification of recycled batches, the validation of sustainability claims, and compliance with increasingly stringent reporting requirements from regulators and customers. Because the material flow is not digitally recorded, the industry cannot provide a complete history of how each batch of scrap is transformed into a finished product.This gap is particularly problematic for industries such as transport and aerospace, where strict alloy standards apply and full traceability is essential.

[0007] Even the automated or semi-automated scrap identification systems introduced in recent years are reaching their limits. Sensor-based sorting machines with optical cameras, X-ray fluorescence, or near-infrared detectors do accelerate classification, but often operate as standalone units without integration into downstream melting processes. Due to this lack of networking, the classification data is rarely used for proactive optimization of the melt composition. Furthermore, many of these systems require calibration, controlled illumination, or uniform scrap geometry to ensure accuracy. Their performance deteriorates with heavily oxidized, painted, or composite materials. These systems also typically do not quantify the alloy composition but merely identify broad categories. As a result, furnaces must cope with significant compositional fluctuations during the melting process.The consequence is that improvements in sorting alone do not solve the challenges of alloy control in the furnace.

[0008] Thermal processing technologies also exhibit significant energy inefficiencies. Most conventional melting furnaces maintain a constant heating temperature regardless of the scrap's thermal mass, oxidation state, moisture content, or target alloy. Without intelligent energy management, the furnaces consume excess energy during idle periods or when melting low-impact scrap that requires less heat input. Heat recovery mechanisms are often inadequately integrated or entirely absent, resulting in the loss of valuable thermal energy that could otherwise be reused within the system. These inefficiencies directly increase production costs and CO2 emissions, thus undermining the sustainability goals of aluminum recycling.

[0009] In the context of alloy matching, common melt analyzers are typically standalone spectrometers requiring manual sampling. This interrupts furnace operation and poses safety risks. The time required for sampling, cooling, and analysis means that any compositional changes occurring during this period go undetected, further increasing the error rate. Attempts to automate sampling remain limited due to mechanical complexity and the harsh thermal environment near the furnace. Furthermore, conventional systems do not synchronize melt analysis with automated actuators capable of precisely timing and quantity the addition of corrective materials. This lack of synchronization introduces a delay between analysis and response, which can alter the melt composition as thermal reactions proceed uncontrollably.

[0010] The lack of a closed-loop control system, where furnace parameters and alloy additions are automatically adjusted based on real-time analytical data, is one of the biggest limitations of current systems. Real-time decisions require continuous measurement, calculation, and control, which most existing plants cannot provide due to outdated plant architecture. Manual monitoring dominates operational decisions and reduces consistency and repeatability between batches. Human intervention further increases the probability of errors, especially at high production volumes when operators have to monitor multiple furnaces simultaneously.

[0011] The current infrastructure for aluminum recycling remains fragmented and inefficient, failing to guarantee consistent alloy accuracy or verifiable sustainability indicators. To overcome the weaknesses of existing solutions, a unified, hardware-integrated system is needed that enables automated sorting, adaptive melting, real-time alloy regulation, and verifiable traceability. SUMMARY OF THE INVENTION

[0012] The present invention provides a fully developed device implemented as a single aluminum recycling machine. This machine consists of a housing for scrap identification, an automated feed preparation system, a controlled remelting reactor, an instrument for monitoring the composition of the melted metal, an actuator network for alloy control, and an interface for a distributed data storage system for traceability. In contrast to the prior art, this device enables continuous, automated scrap classification, precise dosing of the feed material, real-time spectral analysis of the melted metal in the reactor, and autonomously triggered alloy correction cycles.Using distributed ledger technology, the device also stores tamper-proof origin and environmental data, ensuring that every batch of recycled alloy has a verifiable history regarding its composition, origin, and energy consumption. The device represents the entire workflow as a unified mechanical-electronic system, rather than as a loose collection of subsystems.

[0013] The main objective of the invention is to provide an integrated aluminum recycling plant that enables highly precise alloy recovery from heterogeneous scrap streams by combining automated scrap identification, controlled remelting, and closed-loop alloy control in a single hardware structure. A further objective of the invention is to eliminate the inconsistencies and inaccuracies of conventional manual or semi-automatic sorting methods through a sensor and classification system integrated into the plant. This ensures the precise differentiation of each scrap piece based on its physical and chemical properties before it enters the melting phase. Another objective of the invention is to create a remelting environment in which thermal behavior, oxidation tendency, and melting progress are dynamically controlled through real-time monitoring.This allows the furnace to operate only at the required energy level, thereby minimizing heat losses and improving both energy efficiency and melt quality. The invention also aims to enable continuous in-situ chemical analysis of molten aluminum by integrating a spectral analyzer directly into the plant structure. This allows for the immediate detection of compositional deviations without the delays associated with manual sampling.

[0014] Another objective is the integration of an autonomous alloy correction mechanism into the device. This mechanism reacts immediately to real-time analytical data and adds precise amounts of correction metals or high-purity scrap fractions via actuator-controlled dosing systems to keep the melt within target parameters. The invention aims to eliminate reliance on operator intuition through a predictive and self-adjusting control strategy based entirely on real-time measurement and calculation. This improves consistency and reduces alloy defects. A further important objective is to ensure complete traceability of material flow, alloy composition adjustments, energy consumption, and process conditions by integrating a distributed traceability interface directly into the machine.This objective supports the creation of tamper-proof, audit-proof records that document every transformation of the material from raw scrap to finished alloy. This enables certifiable sustainability reporting and compliance with new regulatory requirements.

[0015] The invention aims to reduce overall operating costs by minimizing the need for primary aluminum, reducing melt corrections, decreasing slag formation, and improving the accuracy of scrap recycling. Integrating all processing stages into a single, unified device, rather than separate, loosely connected machines, is intended to optimize workflow, reduce downtime, and minimize human error. A further objective is to ensure the machine's compatibility with various downstream forming or casting systems, allowing the alloy to be transferred directly to ingot casting, extrusion, die casting, or continuous casting processes without intermediate steps.The invention also aims to create a robust and adaptable machine architecture that can cope with large fluctuations in scrap type, degree of contamination, scrap geometry and moisture content, thus ensuring stable operation in different industrial environments.

[0016] The overarching goal of the invention is ultimately to provide a technologically advanced, hardware-integrated and self-optimizing aluminium recycling device that overcomes the limitations of existing solutions while ensuring high purity, reduced energy consumption, full transparency and reproducible alloy quality across multiple batches without manual intervention. BRIEF DESCRIPTION OF THE IMAGE

[0017] These and other features, aspects and advantages of the present invention will be better understood if the following detailed description is read with reference to the accompanying drawing, in which the same symbols represent the same parts: Fig. Figure 1 shows a block diagram of a system for sorting aluminium scrap, controlled remelting, regulating alloy composition and traceable material processing.

[0018] Furthermore, those skilled in the art will recognize that the elements in the drawing are simplified and not necessarily drawn to scale. For example, the flowcharts illustrate the process by highlighting the main steps to facilitate understanding of the present disclosure. With regard to the construction of the device, one or more components may be represented in the drawing by conventional symbols. The drawing may show only those specific details relevant to understanding the embodiments of the present disclosure, so as not to clutter the drawing with details that are already apparent to those skilled in the art from the description contained herein. Detailed description of the invention

[0019] To facilitate understanding of the principles of the invention, reference is made below to the embodiment shown in the drawing, which is described using specific terms. It is understood, however, that this does not limit the scope of protection of the invention. Rather, modifications and further developments of the depicted system, as well as further applications of the inventive principles shown therein, are conceivable, insofar as they would normally occur to a person skilled in the art in the field of the invention.

[0020] It will be clear to those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the invention and are not to be understood as a limitation of it.

[0021] References to “an aspect”, “another aspect”, or similar phrases in this description mean that a particular feature, structure, or property described in connection with the embodiment is included in at least one embodiment of the present disclosure. Therefore, phrases such as “in one embodiment”, “in another embodiment”, and similar expressions in this description may, but do not necessarily, all refer to the same embodiment.

[0022] The terms "includes," "comprehensive," or similar expressions denote non-exclusive inclusion. Thus, a procedure or method containing a list of steps does not only include those steps but may also include further steps not explicitly listed or inherent in the procedure or method. Likewise, the statement "includes..." for one or more devices, subsystems, elements, structures, or components, without further limitations, does not preclude the existence of other devices, subsystems, elements, structures, or components.

[0023] Unless otherwise defined, all technical and scientific terms used herein have the same meanings generally known to those skilled in the art in the field to which this invention belongs. The systems, methods, and examples described herein serve only for illustration and are not to be understood as limiting.

[0024] Embodiments of the present disclosure are described in detail below with reference to the attached drawing.

[0025] Fig.Figure 1 shows a block diagram of a system for sorting aluminum scrap, controlled remelting, alloy composition regulation, and traceable material processing. The system 100 comprises: a scrap identification unit (102) with a sensor unit housed in a closed inspection chamber, which detects optical, electromagnetic, thermal, and surface structural properties of individual aluminum scrap fragments transported on a conveyor belt; a classification processor (104) coupled to the scrap identification unit, which generates routing instructions based on the detected scrap properties; and a diverting device (106) with mechanically actuated slides alongside the conveyor belt, which direct the classified scrap into appropriate containers.A raw material preparation device (108) with a comminution unit, a volumetric dosing unit, and a power cell-controlled hopper that feeds controlled quantities of sorted scrap to the remelting reactor. The remelting reactor (110) comprises a refractory-lined melting chamber with integrated heating elements, an environmental insulation structure, and a furnace control processor for regulating the temperature profiles depending on the scrap properties and the target alloy specifications; an in-situ melt metal composition analyzer (112) comprises a sampling port extending into the melting chamber, a fiber optic detection unit, a spectral analyzer, and a composition processing unit for real-time determination of the chemical composition of the melt metal;An alloy correction device (114) comprises a multi-chamber storage system for correction materials, a set of motor-driven metering mechanisms, and a metering processor for the precise metering of correction material into the melting chamber based on the values ​​of the chemical composition; a casting discharge structure (116) serves to transport the chemically adjusted molten metal to downstream forming equipment; and a traceability processor (118) configured to generate a tamper-proof, chronologically linked data set that includes scrap identification data, furnace operating parameters, composition measurements, alloy correction transactions, and casting discharge data.

[0026] In one embodiment, the scrap identification unit (102) comprises an illumination chamber with a controlled spectral illumination array and thermally stabilized detector channels. The illumination chamber is structurally isolated from the factory's ambient lighting by a vibration-damped mounting interface, so that fluctuations in external lighting and mechanical vibrations do not affect the detection of scrap surface properties. The classification processor is configured to perform multiple analyses of scrap fragments by synchronizing the conveyor belt speed with the sensor exposure intervals to ensure that each scrap fragment is evaluated from multiple perspectives before routing instructions are generated.

[0027] In one embodiment, the raw material preparation device (108) comprises a comminution unit with interlocking cutting blades configured to achieve a uniform particle geometry, and a moisture purge chamber located downstream of the comminution unit. The moisture purge chamber includes a thermally controlled airflow system that reduces the residual moisture in the scrap fragments before they are introduced into the remelting reactor, thereby preventing steam-induced splashing and thermal shock in the melting chamber during furnace operation.

[0028] In one embodiment, the remelting reactor (110) further comprises a multi-zone heating architecture with independently driven heating elements arranged in the lower, middle, and upper regions of the melting chamber. Each heating element is controlled by the furnace control processor using feedback from embedded thermocouple networks and temperature sensors in the refractory walls, thus achieving variable temperature gradients in the melting chamber that are optimized for scrap with heterogeneous levels of contamination and different melting intervals.

[0029] In one embodiment, the in-situ melt metal composition analyzer (112) comprises a sampling port made of high-temperature-resistant alloy material, which is mechanically sealed by means of a double-layer compression seal. The sampling port is configured to minimize the ingress of ambient oxygen into the melting chamber. The spectral analyzer is equipped with a cooled detector array that continuously compensates for thermal drift, enabling the composition processing unit to generate stable chemical composition values ​​even under rapid furnace temperature fluctuations.

[0030] In one embodiment, the alloy correction device (114) comprises a material metering line network extending from the multi-chamber storage arrangement to the melting chamber, each line containing a motor-driven screw conveyor configured to regulate the metering volume based on feedback of the metering torque, and the metering processor further configured to calculate the correction material quantities using a melt volume estimation technique that takes into account the oxidation loss due to scrap, the slag removal intervals, and the thermal evaporation of volatile alloying elements during melting.

[0031] In one embodiment, the casting discharge structure (116) comprises a tilt-controlled melt transfer trough mounted on a servo-driven swivel arm. The swivel arm is driven by a position-feedback actuator. The casting discharge structure is configured to coordinate the melt flow rate, the trough inclination, and the thermal buffering synchronously with the measurements of the final composition by the in-situ melt composition analyzer, ensuring that only chemically conformal melt is discharged to the downstream forming equipment.

[0032] In one embodiment, the traceability processor (118) is configured to acquire time-stamped operational data records from each hardware component via a dedicated data acquisition bus. The traceability processor further includes a cryptographic hashing device that converts the data records into blocks of immutable information. The traceability processor transmits the hashed blocks to an external distributed ledger device, so that each batch of scrap processed in the system is linked to a verifiable, tamper-proof record of composition changes, energy consumption intervals, furnace temperature states, scrap routing results, and alloy correction events.

[0033] In one embodiment, the deflection device (106) comprises a pneumatic gate drive system supported by pressure-controlled air ducts. The pneumatic gate drive system is configured to adjust the gate drive speed based on scrap mass measurements obtained from an upstream mass-sensing conveyor segment. This allows high-mass scrap fragments to be deflected with sufficient mechanical force while simultaneously reducing mechanical fatigue of the deflection device during prolonged operation.

[0034] In one embodiment, the conveyor belt assembly comprises an abrasion-resistant belt material reinforced with heat-insulating fibers and a motor drive with speed feedback sensors. The classification processor is further configured to control the acceleration and deceleration patterns of the conveyor belt to ensure stable alignment of irregularly shaped scrap fragments relative to the sensor assembly, thereby improving detection accuracy for fragments with complex geometries, oxidized layers, or multilayer composite structures.

[0035] The system described in the claims operates with a tightly integrated sequence of hardware-controlled processes and computational procedures, each coordinated by technical decision-making levels integrated into the system's various processors. The detailed description of the system begins with the operation of the scrap identification unit. Here, a conveyor system transports aluminum scrap fragments into a closed inspection chamber. Within this chamber, a spectrally controlled lighting arrangement illuminates the scrap under stable thermal and optical conditions. The sensor array acquires multidimensional data, including reflection spectra, electromagnetic response signatures, surface texture gradients, and variations in heat emission. This raw sensor data is transmitted to the classification processor, which performs a multi-stage pattern recognition procedure.This process performs a temporal alignment of successive sensor images to match the sensor exposure intervals to the conveyor belt speed. Subsequently, a geometric correction is applied to stabilize the orientation of irregular scrap shapes across different viewing angles. The processor then applies a hierarchical decision tree, comparing extracted reflection properties, surface microstructures, and electromagnetic properties to a stored feature space representing known aluminum alloy families and contamination patterns. The process converts each scrap fragment into a classification label, which is then passed to the diversion system's control logic to activate specific pneumatic gate actuators that direct the scrap into its designated containers.

[0036] After classification, the raw material processing plant uses its own control routines. A shredding unit reduces the scrap volume to uniform dimensions using interlocking cutting tools. The rotational speed of these cutting tools is technically controlled based on the scrap hardness. The processed scrap enters a humidity chamber with temperature-controlled air supply. The temperature of the air supply is regulated by a thermal management system that coordinates the air temperature, the residence time of the scrap, and the predefined humidity thresholds. The power cell-controlled hopper assembly meters the required mass flow to convey the exact amount of scrap into the remelting reactor. This calculation takes into account both the instantaneous weight difference in the hopper and preset alloy compositions derived from stored specifications.

[0037] In the remelting reactor, the furnace control processor dynamically controls the multi-zone heating architecture using a thermal adaptation process. This process receives real-time temperature data from thermocouple arrays in the refractory walls and correlates the temperature distribution patterns with the predicted melting progress. Based on the scrap geometry, the degree of fouling, and known melting intervals, the process adjusts the power of the lower, middle, and upper heating elements to generate optimized temperature gradients. These enable rapid melting while preventing overheating or uneven thermal stress in the refractory lining. Simultaneously, the surrounding insulation ensures heat retention, while air ducts modulate the exhaust gas flow according to the furnace pressure conditions calculated by the furnace control processor.

[0038] As soon as the aluminum transitions to a liquid state, the in-situ melt metal composition analyzer begins continuous operation. Its sampling port extends into the melting chamber, where the radiation emitted by the liquid metal enters the fiber-optic detection unit. The spectrometer acquires emission spectra with high temporal resolution. The associated composition processing unit utilizes a spectral decomposition technique that isolates characteristic emission lines of elements such as magnesium, silicon, copper, zinc, manganese, and iron. This technique compensates for thermal drift by referencing the internal calibration patterns of the cooled detector array, thus ensuring that fluctuations in furnace temperature do not distort the spectral measurements.After decomposition, the spectral characteristics are converted into quantitative values ​​of the chemical composition using an elemental calibration curve stored in the processor. The unit transmits the composition values ​​to both the furnace control processor and the dosing processor of the alloy correction device.

[0039] The alloy correction device utilizes a material balance method that determines the necessary correction allowances to adjust the melt composition to the target alloy specification. This method estimates the melt volume based on thermal expansion correlations, feedback from load cells on the incoming scrap, and known metal loss factors due to oxidation and slag formation. The calculation incorporates dynamic variables such as the evaporation rates of volatile elements, the measured deviation of the melt composition from the target values, and the current thermal state of the melt. Based on these calculations, the metering processor actuates the motor-driven screw conveyors of the individual material lines and regulates the metering torque to ensure precise delivery rates.This closed-loop correction process is continued iteratively, with each new composition measurement refining the estimates of the correction procedure until composition equilibrium is reached.

[0040] Once the preparation unit confirms that the molten metal meets the target alloy specification, the system transitions to the casting discharge phase. The casting discharge structure is controlled by a flow control system that synchronizes the tilt angle of the servo-controlled swivel arm with the viscosity parameters of the molten metal derived from the furnace temperature data. This system ensures that the discharge rate, trough tilt, and thermal buffering are tailored to the requirements of the downstream forming equipment, thus guaranteeing consistent solidification behavior of the discharged metal across different batches.

[0041] Throughout the entire operation, the traceability processor continuously captures the data generated at each component via a dedicated data acquisition bus. This data is divided into chronological transaction blocks containing scrap identification results, thermal profiles, spectral analyses, dosing operations, and casting processes. A cryptographic hashing process converts each block into a unique digital signature. These signatures are transmitted to an external distributed ledger system, where each block is immutably linked to the previous one. This creates a tamper-proof digital chain that documents the entire lifecycle of each scrap batch.

[0042] In this way, the system achieves a coordinated integration of computing power and mechanics, with technical decision-making processes controlling sorting, melting, alloying, and traceability. Sensor data, thermal feedback, and spectral measurements enable continuous adjustments at each stage, thus providing real-time control and self-correction without human intervention. The system therefore functions as a unified, intelligent device that maintains alloy consistency, reduces energy consumption, eliminates delays caused by manual sampling, minimizes scrap misclassification, and generates verifiable traceability datasets that document the transformation of aluminum scrap into precisely alloyed material.

[0043] The device is mounted as an integrated industrial structure on a robust chassis that supports the scrap identification housing. This housing contains a conveyor belt mechanism with a sensor array for measuring optical, electromagnetic, and surface structural characteristics of the incoming aluminum scrap. The housing contains an illumination chamber, detector channels, and integrated electronics for processing the sensor signals. This electronics converts the sensor signals into classification signals to direct the scrap to the designated discharge chutes. The mechanical structure includes pneumatic diverters or servo-controlled gates that physically sort the scrap into alloy-specific containers. The device also features a processing chamber where the sorted scrap is shredded and dosed according to a ratio determined by the desired alloy specification.This chamber is equipped with volumetric dosing units, load cell-monitored hoppers, and mechanically operated dosing valves.

[0044] Adjacent to the raw material preparation plant is a controlled remelting reactor. This consists of a refractory-lined furnace body with integrated heating elements that can adjust the temperature profiles to the scrap quality and the desired alloy yield. The reactor has a sampling port for the liquid metal, which is connected to an in-situ spectral analyzer. This analyzer uses the emission signatures of the melt to generate continuous chemical measurements. The analyzer includes a fiber optic probe, a cooled detector section, and a processing unit that determines the alloy composition in real time. These measurements are transmitted to an alloy regulating unit. This unit consists of motor-driven feeders that add minute quantities of corrective materials, such as virgin metal fragments, master alloy pellets, or high-purity scrap fractions, from designated chambers within the plant.

[0045] During operation, aluminum scrap is fed into the identification chamber, where sensors and classification electronics analyze each piece. The classified scrap is automatically sorted into separate containers via actuated slides. The processing unit determines the required scrap mixture and feeds it into the controlled remelting reactor. During the melting process, the in-situ spectral analyzer continuously monitors the alloy composition. Deviations from the target composition prompt the actuator network to add corrective additives. These adjustments are made in real time until the melt fully meets the programmed specification. Throughout the entire process, the distributed traceability system records every mechanical and chemical event, thus creating complete documentation of the product chain.Once chemical homogeneity is achieved, the melt is directed to the casting outlet, depending on further requirements, to be further shaped, solidified or extruded.

[0046] The drawing and the preceding description illustrate embodiments. Those skilled in the art will recognize that one or more of the described elements can be combined to form a single functional element. Alternatively, certain elements can be divided into several functional elements. Elements of one embodiment can be added to another. For example, the process flows described here can be modified and are not limited to the manner described herein. Furthermore, the actions of a flowchart need not be performed in the sequence shown; nor do all actions necessarily need to be carried out. Actions that do not depend on other actions can be performed in parallel with the other actions. The scope of protection of the embodiments is in no way limited by these specific examples. Numerous variations, whether explicitly stated in the description or not, such as...Differences in structure, dimensions, and materials are possible. The scope of protection of the embodiments is at least as comprehensive as described by the following claims.

[0047] The advantages, other benefits, and problem solutions have been described above with reference to specific embodiments. However, the advantages, benefits, problem solutions, and any components that can effect or enhance an advantage, benefit, or solution are not to be construed as critical, necessary, or essential features or components of the claims. REFERENCES 100 A system for sorting aluminium scrap, controlled remelting, regulation of alloy composition and traceable material processing. 102 Scrap identification unit 104 Classification Processor 106 Diversion assembly 108 Raw material processing device 110 remelting reactor 112 Melting metal composition analyzer 114 Alloy correction device 116 Pouring ejection structure 118 Traceability processor

Claims

[1] A system for sorting aluminium scrap, controlled remelting, regulation of alloy composition and traceable material processing, comprising: a scrap identification unit equipped with a sensor arrangement housed in a closed inspection chamber, wherein the sensor arrangement is designed to detect optical, electromagnetic, thermal and surface structural properties of individual aluminium scrap fragments transported on a conveyor system; a classification processor that is operationally coupled with the scrap identification unit and is configured to generate routing instructions based on the detected scrap characteristics; a deflection device with mechanically operated gates, which are arranged next to the conveyor system and serve to direct classified scrap into designated containers; a raw material processing device comprising a comminution device, a volumetric dosing device and a power cell controlled hopper arrangement, wherein the raw material processing device is configured to feed controlled quantities of sorted scrap to a remelting reactor; The remelting reactor consists of a refractory-lined melting chamber with integrated heating elements, an environmental insulation structure and a furnace control processor configured to regulate temperature profiles depending on the scrap properties and target alloy specifications; an in-situ composition analyzer for molten metal, consisting of a sampling port extending into the melting chamber, a fiber optic detection unit, a spectral measuring device and a composition processing unit configured to determine the chemical composition values ​​of the molten metal in real time; an alloy correction device comprising a multi-chamber storage arrangement for correction materials, a set of motor-driven metering mechanisms and a metering processor configured to introduce precise amounts of correction material into the melting chamber based on the chemical composition values; a casting discharge structure configured to transport chemically matched liquid metal to downstream forming equipment; and a traceability processor configured to generate a tamper-proof, chronologically linked data set that includes scrap identification data, furnace operating parameters, composition measurements, alloy correction transactions, and casting discharge data. [2] System according to claim 1, wherein the scrap identification unit comprises an illumination chamber with a controlled spectral illumination array and thermally stabilized detector channels, wherein the illumination chamber is structurally isolated from the ambient lighting of the factory by a vibration-damped mounting interface so that fluctuations in external lighting and mechanical vibrations do not affect the detection of the scrap surface properties, and wherein the classification processor is configured to perform multiple analysis of scrap fragments by synchronizing the conveyor belt speed with the sensor exposure intervals to ensure that each scrap fragment is evaluated from multiple perspectives before routing instructions are generated. [3] System according to claim 1, wherein the raw material preparation device comprises a comminution unit with interlocking cutting blades to achieve a uniform particle geometry and further comprises a moisture purge chamber arranged downstream of the comminution unit. The moisture purge chamber comprises a thermally controlled airflow system that reduces the residual moisture in the scrap fragments before they are introduced into the remelting reactor and thereby prevents steam-induced splashing and thermal shock in the melting chamber during furnace operation. [4] System according to claim 1, wherein the remelting reactor further comprises a multi-zone heating architecture configured with independently driven heating elements arranged along the lower, middle and upper regions of the melting chamber, each heating element being controlled by the furnace control processor using feedback from embedded thermocouple networks and refractory wall temperature sensors, such that the melting chamber achieves variable thermal gradients optimized for scrap with heterogeneous levels of contamination and different melting intervals. [5] System according to claim 1, wherein the in-situ melt metal composition analyzer comprises a sampling port made of high-temperature resistant alloy material which is mechanically sealed by means of a double-layer compression seal, wherein the sampling port is configured to minimize the ingress of ambient oxygen into the melting chamber, and wherein the spectral measuring instrument is equipped with a cooled detector arrangement which continuously compensates for thermal drift, so that the composition processing unit can produce stable chemical composition values ​​even during rapid furnace temperature fluctuations. [6] System according to claim 1, wherein the alloy correction device comprises a material metering line network extending from the multi-chamber storage arrangement to the melting chamber, each line containing a motor-driven screw conveyor configured to control the metering volume based on torque feedback, and wherein the metering processor is further configured to calculate the correction material quantities using a melt volume estimation technique that takes into account the oxidation loss due to scrap, the slag removal intervals, and the thermal evaporation of volatile alloying elements during melting. [7] System according to claim 1, wherein the casting discharge structure comprises a tilt-controlled melt transfer trough mounted on a servo-driven swivel arm, the swivel arm being driven by a position-controlled actuator, and the casting discharge structure is configured to coordinate the melt metal flow rate, the trough inclination and the thermal buffering synchronously with the final composition measurements of the in-situ melt metal composition analyzer, so that only chemically conformal melt metal is delivered to downstream forming equipment. [8] System according to claim 1, wherein the traceability processor is configured to capture time-stamped operational data records from each hardware component via a dedicated data acquisition bus, wherein the traceability processor further comprises a cryptographic hash device that converts the data records into blocks of immutable information, and wherein the traceability processor transmits the hashed blocks to an external distributed ledger device, so that each batch of scrap processed in the system is linked to a verifiable, tamper-proof record of composition changes, energy consumption intervals, furnace temperature states, scrap routing results, and alloy correction events. [9] System according to claim 1, wherein the deflection device comprises a pneumatic gate drive system supported by pressure-controlled air ducts. The pneumatic gate drive system is configured to adjust the gate drive speed based on scrap mass measurements obtained from an upstream mass-sensing conveyor segment. This allows high-mass scrap fragments to be deflected with sufficient mechanical force while simultaneously reducing mechanical fatigue of the deflection device during prolonged operation. [10] System according to claim 1, wherein the conveyor belt arrangement comprises an abrasion-resistant belt material reinforced with heat-insulating fibers and a motor drive with speed feedback sensors, wherein the classification processor is further configured to control the acceleration and deceleration patterns of the conveyor belt to ensure stable alignment of irregularly shaped scrap fragments relative to the sensor arrangement and thereby improve the detection accuracy for fragments with complex geometries, oxidized layers or multilayer composite structures.

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