Method for assessing the use of a bulk material within a process

Abstract

Method for assessing the use of a bulk material (3) within a process, which process at least includes the bulk material (3) being dosed by means of a metering device (1), the method includes the acquisition of at least one sample and / or parts of the bulk material (3), and at least partially based on the data of the acquisition, an assessment of the use of the bulk material (3) within the process is determined by means of an assessment module. wherein, by means of an evaluation module based on the data of the recording, at least one identifier and / or a classification of the bulk material (3) is determined, and the identifier and / or a result of the classification is included in the determination of the assessment, wherein the assessment involves determining, based on the identifier and / or the classification result, whether the bulk material (3) is a bulk material suitable for the dosing device (1) and / or the process.

Description

field of technology

[0001] The present invention relates to a first method for evaluating the use of a bulk material within a process, and a second method for monitoring a metering device provided within a process for metering a bulk material. The present invention further relates to a third method for obtaining an evaluation of the use of a bulk material within a process. The present invention also relates to a data processing device configured to execute the first and / or second method. The present invention further relates to a data processing device configured to execute the third method. State of the art

[0002] When operating a dosing device for dispensing bulk materials, it must be ensured that a suitable bulk material is used and vice versa. If the wrong bulk material is fed into the dosing device, for example, due to incorrect labeling or a mix-up, this can lead to impaired dosing performance and reliability, damage to parts of the dosing device, or even complete failure of the device. This results in costs for repairing the device. The process steps preceding and following the dosing can also be affected or even completely halted by unsuitable bulk material. Production downtime and associated economic losses can be the consequence.

[0003] DE 10 2019 104 293 A1 relates to a method for determining a configuration of a conveying device for granular material.

[0004] DE 10 2009 017 210 A1 relates to a device and a method for detecting impurities in bulk materials.

[0005] The WO 2018 / 050 525 A1 concerns a procedure for operating dosing equipment.

[0006] WO 2020 / 193 137 A1 concerns a method for the coarse classification of the particle size distribution of a bulk material. Summary of the invention

[0007] It is therefore an object of the present invention to overcome the described disadvantages of the prior art and in particular to provide means by which a process, including the operation of a dosing device, can be made safer and more reliable.

[0008] The object of the invention is achieved according to a first aspect by providing a method for assessing the use of a bulk material within a process, which process preferably comprises at least the metering of the bulk material by means of a metering device, the method comprising the acquisition of at least one recording of at least one sample and / or of parts of the bulk material, and the determination of the use of the bulk material within the process, preferably by means of an assessment module, based at least partially on the recording data, wherein an evaluation module determines at least one identifier and / or a classification of the bulk material based on the recording data, and the identifier and / or a result of the classification is included in the determination of the assessment, wherein the determination of the assessment comprisesIt is proposed to determine, based on the identifier and / or the classification result, whether the bulk material is a bulk material suitable for the dosing device and / or the process.

[0009] The invention is based on the surprising finding that by using information obtained from a recording of the bulk material, the determination of the suitability of the bulk material for use in a process can be based on actually existing circumstances.

[0010] Therefore, it is not necessary to rely on the accuracy of, for example, the material labeling or the decisions of the operating personnel. Instead, the data provided by the recording can be used as an objective information basis for the existing situation. Decision-making based on this can promote a safe and reliable assessment regarding the use of the bulk material in the respective process, especially in conjunction with the respective dosing device.

[0011] In other words, a recording of the bulk material allows for the assessment of the bulk material to be based on information that is inextricably linked to the bulk material and therefore reflects the actual conditions and cannot be accidentally falsified.

[0012] Therefore, if, for example, bulk material is fed from a supply labeled with an incorrect product name in the respective process, particularly in the dosing device, the proposed method can detect the error. This is because the proposed method can advantageously support an assessment based on data representing characteristics of the bulk material that are inextricably linked to the bulk material itself.

[0013] The proposed method can therefore better ensure that the correct bulk material is used in a process, i.e., processed and / or fed into it, and in particular that the correct bulk material is metered and / or fed into a dosing device. Especially with changing recipes (e.g., bulk material compositions), this can lead to an improved and more reliable process flow.

[0014] Incorrect processing of materials during the process can therefore be prevented by capturing the bulk material via a recording device and assessing it as described.

[0015] This method is particularly suitable for assessing the suitability of bulk material for dosing operations with a dosing device. Advantageously, the process under consideration is identical to the dosing operation in which the bulk material is dosed by the dosing device. This allows for the identification of material unsuitable for dosing. Furthermore, information on process steps outside the actual dosing operation can be advantageously included, enabling the suitability of the material to be determined, at least partially, based on this information.

[0016] The proposed method can easily be applied to existing processes. Essentially, it is sufficient to have the bulk material measurement available and to evaluate it appropriately. This allows the method to be used in a wide variety of processes and makes it extremely flexible.

[0017] Examples of bulk materials include rock, building materials (especially topsoil, sand, gravel and / or cement), raw materials (especially ore, coal, clay and / or road salt), foodstuffs (especially grain, sugar, salt, coffee and / or flour), and / or powdered goods (especially pigments, fillers, granules and / or pellets). Further examples of bulk materials include fibers (for example, consisting of or containing carbon and / or glass fibers), recycled materials (such as plastic scraps and / or shredded carpets).

[0018] The type of bulk material can be, for example, one of the following bulk material types: dust, powder, flour, grains, granules, grit, lumps, pellets and / or other.

[0019] It goes without saying that the bulk material, or rather a specific quantity thereof, is initially a bulk material to be dosed, and after it has undergone the dosing process, a dosed bulk material.

[0020] In the present application, a process may preferably comprise several sub-processes. A sub-process may, for example, be the dosing process in which the bulk material is dosed using the dosing device (for example, after the bulk material to be dosed has been fed to the dosing device in a preceding sub-process and / or before the dosed bulk material is subjected to further treatment and / or processing in a subsequent sub-process).

[0021] The process is advantageously implemented using a computer.

[0022] The process can be advantageously provided as a cloud service. This eliminates the need for extensive data processing at the location of the dosing device being configured.

[0023] Receiving a recording advantageously involves receiving data, particularly image data, from the recording. For example, the data represents pixel values ​​of the recording. This data can be received in raw format, in a pre-processed image format, and / or from a suitable light-sensitive sensor.

[0024] The assessment module can be implemented, for example, in software, in hardware, or a combination of both. Alternatively or additionally, the assessment module can include memory, a processor, a receiving device (e.g., to receive the recording), a transmitting device (e.g., to send a generated signal to another entity), or any combination thereof. Alternatively or additionally, the assessment module can provide and / or make available everything it has in common, including, in particular, all necessary resources, such as software and / or hardware resources.

[0025] When the assessment in the present application is determined "based on" certain data, this advantageously means that the assessment could not be determined without this certain data. This certain data (which can be referred to as source data) can advantageously be subjected to one or more data processing steps to obtain processed data. Within these data processing steps, the certain data can, for example, be evaluated, further processed, and / or combined with other data. Additional information, particularly from other sources such as databases, can also be obtained using the certain data and may be available, for example, as intermediate results.Within data processing steps, additional information can be subjected to further data processing steps alongside or instead of the certain data and / or processed data, including processing with other certain data. More generally, this means that several different certain data, "starting from" which the assessment is determined, may exist, each of which can be processed separately. At a specific processing step, two or more different such source data, possibly already in processed form, are combined and optionally used as input data for subsequent data processing.

[0026] In one embodiment, at least the recording data constitutes input data and / or at least the assessment constitutes output data of the assessment module. Further input and / or output data, in particular those described elsewhere in the application, are possible.

[0027] Preferably, the output data of a module is obtained at least partially by the respective module by processing at least the input data of the respective module, i.e., evaluating, analyzing and / or converting it into new data.

[0028] Alternatively or additionally, it may also be provided that, preferably by means of an evaluation module, at least one identifier, in particular a material designation, is determined based on the data of the recording and / or a classification of the bulk material is determined, and the identifier and / or a result of the classification is included in the determination of the assessment.

[0029] The identifier can, for example, be a unique identifier (such as an alphanumeric string) for a specific bulk material. Advantageously, further information about the bulk material represented by the identifier can be determined using this identifier, particularly when using a database. This information, such as material specifications of the bulk material, can then be retrieved from a database using the identifier.

[0030] This information can be taken into account when determining the assessment. For example, certain material properties may be among the relevant information. Based on material properties, the suitability of the bulk material for use in a dosing device and / or in the process can be advantageously assessed. Therefore, it is beneficial if, based on the data from the initial recording and using the identifier, one or more material properties are obtained and included in the assessment.

[0031] A classification can, for example, refer to the type of bulk material. Within the framework of classification, the bulk material can therefore be classified into at least one of the following categories: dust, powder, flour, grains, granules, grit, lumps, pellets, and / or other. Regardless of the specific classification, the suitability of the bulk material for use in a dosing device and / or in the process can be advantageously assessed based on the classification. For example, one or more material properties can be retrieved from a database for the respective classification and included in the assessment. Therefore, it is advantageous if, based on the data collected and with the aid of the classification, one or more material properties are obtained and included in the assessment.

[0032] Alternatively or additionally, a classification can also refer to a specific, particularly medium, particle size of the bulk material. This allows the classification to advantageously yield the bulk material type and / or a particle size as a single result.

[0033] In the aforementioned cases, the retrieved information can alternatively or additionally be provided together with the determined assessment, for example on a user interface such as a screen, and / or to a user. This allows, for example, the provision of a justification explaining the circumstances that lead to the assessment being against the use of the bulk material.

[0034] The evaluation module can be implemented, for example, in software, in hardware, or a combination of both. The evaluation module can alternatively or additionally include memory, a processor, a receiving device, a transmitting device, or any combination thereof. The evaluation module can alternatively or additionally provide and / or make available everything it is described as having, including, in particular, all necessary resources, for example, in the form of software and / or hardware resources.

[0035] In an advantageous embodiment, the assessment module includes the evaluation module. The evaluation module and the assessment module can preferably be identical and thus a single, combined module.

[0036] In one embodiment, the two modules are operated in separate locations. This is advantageous if the two modules have different hardware and / or software resource requirements, allowing the module with more computationally intensive operations to be operated in an environment with sufficient hardware and / or software resources. In this case, the modules can exchange data with each other, for example, via a data connection.

[0037] In one embodiment, at least the recording data constitutes input data and / or at least the identifier and / or the classification constitutes output data of the evaluation module. Further input and / or output data, in particular those described elsewhere in the application, are possible.

[0038] In one embodiment, alternatively or additionally, at least the output data of the evaluation module constitute at least partial input data of the assessment module. Further input and / or output data, in particular those described elsewhere in the application, are possible.

[0039] Alternatively or additionally, it may also be provided that the determination of the assessment includes determining, based on the identifier and / or the classification result, whether the bulk material is a bulk material permissible for the metering device and / or the process, wherein preferably at least partially the identifier and / or the classification result is checked against a database in which bulk material identifiers and / or bulk material classifications permissible for the metering device and / or the process are specified, wherein the determined assessment is an assessment of a first assessment type if the bulk material is determined to be a permissible bulk material and / or the determined assessment is an assessment of a second assessment type if the bulk material is not determined to be a permissible bulk material.

[0040] Advantageously, the method has the advantage that if the identifier and / or classification result is a predefined identifier and / or classification result that is permissible for the dosing device and / or the process, the bulk material is determined to be permissible and otherwise to be impermissible.

[0041] For example, a list containing all identifiers and / or bulk material classes (related to the bulk material type mentioned above) intended for use in the dosing device and / or process can be provided. These identifiers and / or classifications are deemed suitable for the respective dosing device and / or process. By checking whether the identifier and / or classification result is included in the list, it can be determined in a simple yet effective way whether the bulk material is acceptable. The list can advantageously be stored in a database. It can preferably be updated manually and / or automatically via a cloud service. This allows dosing devices already in production to be easily updated with new insights and experience regarding bulk materials.

[0042] In one embodiment, the first assessment type means that the bulk material can be used within the process, in particular with the metering device, and / or the second assessment type means that the bulk material cannot be used within the process, in particular with the metering device.

[0043] Alternatively or additionally, the procedure may also include the provision that information on a bulk material assigned to the identifier and / or information associated with the classification result is obtained, in particular retrieved from a database, and included in the determination of the assessment.

[0044] As described above, the additional information allows for an even more reliable and secure assessment. This enables the consideration of information about the bulk material that is not directly obtainable from the data recorded, but which can be retrieved from other sources (such as the database) by using the identifier and / or the classification result as a link (relation). While this information can be derived from the data recorded, it typically requires additional resources (such as databases, etc.) to obtain it.

[0045] In this process, the information is advantageously obtained based on the identifier and / or the classification result, i.e., retrieved from the database.

[0046] Preferably, the information relates at least partially to the material properties of the bulk material.

[0047] In one embodiment, the information obtained alternatively or additionally constitutes at least some input data for the assessment module. Further input and / or output data, particularly those described elsewhere in the application, are possible.

[0048] Alternatively or additionally, the procedure may also include the evaluation and / or analysis of the data from the first recording, at least partially using methods of digital image analysis, in particular at least partially in the field of machine learning, especially in order to determine the classification and / or the identifier.

[0049] Advantageously, digital image analysis is performed using machine learning methods. For this purpose, a machine learning model can be trained on training data that is of the type of the later expected input data, each with its corresponding expected output data. The trained model can then calculate output data based on the respective input data, representing the specific information or other information.

[0050] Therefore, for example, the assessment module can execute appropriate methods, especially on at least the recording data, to determine the assessment at least partially.

[0051] Therefore, for example, the evaluation module can execute appropriate methods, especially on at least the recording data, to determine the identifier and / or classification, at least partially.

[0052] Alternatively or additionally, it may also be provided that the determination of the assessment includes at least one piece of information relating to a sub-process, in particular a sub-process following and / or preceding the dosing process, in determining the assessment, wherein preferably the assessment determined is an assessment of a first type if the bulk material is determined to be suitable for the respective sub-process, in particular based on the identifier and / or the classification result, and / or the assessment determined is an assessment of a second type if the bulk material is determined to be unsuitable for the respective sub-process.

[0053] Advantageously, the method has the advantage that if the identifier and / or classification result could be determined in a given list of permissible identifiers and / or classification results, the bulk material is determined to be suitable for the respective sub-process and otherwise unsuitable for the respective sub-process.

[0054] For example, in a sub-process following the dosing process, the bulk material may be treated with heat. In this case, the maximum temperature during this sub-process could be relevant information. A bulk material unsuitable for such heat treatment could be classified as unsuitable.

[0055] For example, in the case of plastic compounding, each added raw material can serve a specific purpose. A subsequent process step, such as extrusion, then depends on receiving the correct mixture of raw materials. A bulk material that is incorrectly fed into the wrong dosing device could then be deemed unsuitable.

[0056] For example, in the production of plastic films, each raw material supplied can serve a specific purpose. A subsequent process step, such as extrusion, then depends on receiving the correct mixture of raw materials. A bulk material with deviating parameters, such as a particle size distribution, could then be deemed unsuitable. The same applies, in corresponding examples, to food production.

[0057] In one embodiment, alternatively or additionally, at least the information relating to the sub-process constitutes at least some input data for the assessment module. Further input and / or output data, particularly those described elsewhere in the application, are possible.

[0058] Alternatively or additionally, it may also be provided that the determination of the assessment includes the inclusion of at least one piece of information regarding the configuration of the metering device, such as a type designation of a, in particular interchangeable, mechanical component, such as a discharge element, of the metering device and / or a value of an operating parameter of the metering device, such as a conveying rate and / or a rotational speed of a motor of the metering device, in the determination of the assessment, wherein preferably the inclusion of the configuration information includes the evaluation of the configuration information in the background of the information obtained on a bulk material assigned to the identifier and / or that associated with the classification result, wherein preferably the determined assessment is an assessment of a first assessment type if the configuration of the metering device is determined to be suitable for the bulk material.in particular if the assessment is positive, and otherwise the assessment obtained is an assessment of a second type.

[0059] Advantageously, the method has the advantage that if the configuration information is consistent with predefined specifications of the bulk material (whereby the information obtained may be or contain such specifications), the configuration is determined to be suitable for the bulk material, and otherwise the configuration is determined to be unsuitable for the bulk material.

[0060] For example, a maximum rotational speed and / or minimum dimensions for the discharge element of the metering device may be specified for a bulk material. If the metering device intended for metering operates at a higher rotational speed and / or uses a discharge element that does not meet the minimum dimensions, the configuration may be determined to be unsuitable for the bulk material.

[0061] It is advantageous to determine, together with information about the bulk material (whether information obtained directly from the data of the recording, or indirectly, for example based on the identifier and / or the classification result from a database), to what extent the given configuration enables dosing of the bulk material and to include the result of the determination in the determination of the assessment.

[0062] In one embodiment, additional information about the bulk material (in particular based on the identifier and / or the classification result from a database) and additional information about the configuration of the dosing device can be determined and evaluated by comparing them, and the assessment can be determined at least partially based on a result of the evaluation.

[0063] Preferably, the configuration of the dosing device is known and / or the information about it can be made available in the method and / or retrieved from a memory.

[0064] In one embodiment, the configuration information alternatively or additionally constitutes at least some input data for the assessment module. Further input and / or output data, particularly those described elsewhere in the application, are possible.

[0065] Alternatively or additionally, it may also be provided that the assessment determined is an assessment of a first assessment type if the combination of the bulk material and the metering device is determined to be a permissible combination and / or the assessment determined is an assessment of a second assessment type if the combination of the bulk material and the metering device is not determined to be a permissible combination.

[0066] Advantageously, the method has the advantage that if the identifier and / or classification result is a predefined identifier and / or classification result that is permissible for the dosing device and / or the process, the combination is determined as a permissible combination and otherwise as an impermissible combination.

[0067] Alternatively or additionally, the method may also provide that the determined assessment is a characteristic value, preferably within defined limits, preferably a number from zero to one inclusive, wherein the characteristic value is preferably a measure of the suitability of the bulk material for use in the process and / or for being dosed with the dosing device.

[0068] For example, zero means the lowest suitability of the bulk material for use and one means the maximum suitability of the bulk material for use.

[0069] Alternatively or additionally, it may also be provided that the assessment is an assessment of the first type if the characteristic value corresponds to a defined quality measure, is greater or less than a defined first threshold value and / or is within a defined target value range, and / or the assessment is an assessment of the second type if the characteristic value does not correspond to the defined quality measure, is greater or less than a defined second threshold value and / or is outside the defined target value range.

[0070] Threshold values ​​make it easy to adjust the assessment sensitivity and thus flexibly take into account individual requirements regarding the safety and reliability of the assessment.

[0071] Alternatively or additionally, the procedure may also include the generation of a warning message, preferably displayed to a user on a user interface such as a screen, if the assessment is of the second assessment type and / or not of the first assessment type.

[0072] This allows operating and / or monitoring personnel to be informed about the assessment and asked to take action.

[0073] Alternatively or additionally, it may also be provided that a control signal, which is indicative of the determined assessment and / or the assessment type of the determined assessment, is generated and preferably, in particular as a control and / or regulation signal, is supplied to an entity and / or output to a user on a human-machine interface, such as a screen.

[0074] The entity can be the dosing device or parts thereof, such as a motor or its motor control. The entity can also be, for example, a device within the process that is different from the dosing device.

[0075] Alternatively or additionally, it may also be provided that the intake of the bulk material to be dosed is carried out before the dosing device is filled with the bulk material to be dosed.

[0076] For example, the bulk material captured by the recording may be contained in a material packaging, preferably sealed.

[0077] For example, the bulk material captured by the recording device may be located in the inlet of the metering device and / or in a storage container, from which the bulk material is advantageously taken and fed to the metering device.

[0078] Alternatively or additionally, it may also be provided that the bulk material captured by the intake is located in the metering device and / or on a conveying device upstream of the metering device, such as a conveyor belt.

[0079] For example, the bulk material captured by the recording device may be located in the inlet of the metering device and / or in a storage container, from which the bulk material is advantageously taken and fed to the metering device.

[0080] The bulk material can be fed to the metering device via the aforementioned conveyor belt. The conveyor belt can then be advantageously stopped if the bulk material being moved by the conveyor belt and picked up by the intake is deemed unsuitable for the metering device and / or the process. This prevents unsuitable bulk material from being metered and / or processed further.

[0081] Alternatively or additionally, it may also be provided that the bulk material captured by the recording device is located outside the dosing device.

[0082] Alternatively or additionally, it may also be provided that the intake is taken at the bulk material inlet, within the metering device and / or in front of and / or behind the discharge device.

[0083] For example, the bulk material captured by the recording device may be located in the discharge pipe and / or discharge head of the metering device.

[0084] The metering device advantageously includes a discharge element. The discharge element can be, for example, a screw, a spiral, a screw and / or a slide.

[0085] Alternatively or additionally, it may also be provided that the recording is an image recording, preferably in the visible, infrared or ultraviolet spectral range, retrieved from a memory, received by a sensor, in particular an optical sensor and / or received via a data connection.

[0086] The recording can advantageously be made with a camera. This camera can, for example, have a sensor that is sensitive in the visible, infrared, and / or ultraviolet spectral range. By choosing the sensor type—that is, which spectral components of the light are captured for the recording—different characteristics can be advantageously determined directly based on the recording data.

[0087] For example, an infrared camera can be used to determine the temperature of the bulk material and, based at least partially on this temperature, assess its suitability for dosing with the metering device and / or for use in the process. This allows for the detection of temperature fluctuations in the metered bulk material exceeding a certain threshold. An elevated temperature may indicate an incorrect choice of discharge element for the metering device. The metering process can then be stopped, for example, based on this finding.

[0088] Furthermore, the recording can also be made using a radar sensor and / or an X-ray device.

[0089] Alternatively or additionally, it may also be provided that the assessment module includes a machine learning model that has been pre-trained and / or that is included in the determination of the assessment.

[0090] Advantageously, the machine learning model (ML model) is trained with data from a large number of recordings of one or more known bulk materials. This allows the model to learn a relationship between a recording (of a bulk material) and a specific bulk material, information about it, and / or an assessment of the bulk material. Optionally, in addition to the recording data, further information, such as details about dosing devices (especially their configurations) and / or processes, can be provided as input data, and the training can incorporate this information accordingly. This allows the learned relationship to be expanded.

[0091] The machine learning model can also learn a relationship between identifiers and / or classification results on the one hand and assessments on the other. Optionally, further information, such as details about dosing devices (especially their configurations) and / or processes, can be provided as input data, and the training can take this information into account accordingly. This allows the learned relationship to be expanded.

[0092] To extract information from images, Convolutional Neural Networks (CNNs), especially those from the field of deep learning, have proven to be advantageously suited and are therefore preferably used as the basis for the ML model.

[0093] The machine learning model can also be retrained with newly acquired recordings. This allows the predictive power of the assessment to be continuously improved.

[0094] The machine learning (ML) model preferably uses at least some of the input and output data from the assessment module. The ML model advantageously calculates the output data based on the input data. Accordingly, the ML model is advantageously trained on input data that corresponds to the input data used later.

[0095] Alternatively or additionally, it may also be provided that the evaluation module has a machine learning model that has been pre-trained and / or that is included in the determination of the identifier and / or the classification.

[0096] Advantageously, the machine learning model (ML model) is trained with data from a large number of recordings of one or more known bulk materials. In this way, a relationship can be learned between, on the one hand, a recording (of a bulk material) and, on the other hand, a specific bulk material or information about it (such as an identifier and / or a classification of the bulk material).

[0097] Advantageously, a machine learning (ML) model can be used for both the assessment module and the evaluation module, with the two ML models operating independently. In this case, it is advantageous if the ML model of the assessment module is at least partially trained with data that results from the output of the ML model of the evaluation module and / or that is derived from at least some of the output data of the ML model of the evaluation module. In this way, the ML model of the assessment module can learn a relationship between, on the one hand, the respective output data of the evaluation module (and any additional information) and, on the other hand, an assessment of the bulk material.

[0098] If both ML models are successful, it is therefore advantageous to use the ML model of the assessment module to determine an assessment of the use of the bulk material based on the result data of the ML model of the evaluation module and / or the information determined from the result data of the ML model of the evaluation module.

[0099] To extract information from images, Convolutional Neural Networks (CNNs), especially those from the field of Deep Lean, have proven to be advantageously suited and are therefore preferably used as the basis for the ML model.

[0100] The machine learning model can also be retrained with newly acquired recordings. This allows the predictive power of the assessment to be continuously improved.

[0101] The machine learning (ML) model of the evaluation module preferably has, as input and output data, at least partially the input and output data of the evaluation module itself. The respective ML model advantageously calculates the output data based on the input data. Accordingly, the ML model is advantageously trained on input data that corresponds to the input data used later.

[0102] The object is solved by the invention according to a second aspect by proposing a method for monitoring a metering device provided within a process for metering a bulk material, comprising a method according to the first aspect of the invention to assess the use of the bulk material within the process and, depending on the assessment, in particular the type of assessment, to generate a control signal which is supplied, in particular as a control and / or regulation signal, to the metering device and / or an entity, in particular different from the metering device.

[0103] The invention is based on the surprising finding that the operation of a dosing device can be made more reliable and safer by using an assessment obtained according to a method according to the first aspect of the invention to monitor the dosing device and its dosing process.

[0104] All the advantages described in relation to the method according to the first aspect of the invention also apply accordingly to the method according to the second aspect of the invention. Therefore, reference can be made to the preceding explanations at this point.

[0105] The proposed method can advantageously be applied to existing metering devices. In principle, no structural modifications to the respective metering device are necessary. Ultimately, it is sufficient to have the bulk material intake available and to feed it into the method according to the first aspect of the invention. This allows the method to be used with a large number of metering devices and makes it extremely flexible.

[0106] The proposed monitoring of the bulk material being dosed can therefore prevent or detect incorrect filling of a dosing device at an early stage. Critical situations, including production downtime, can thus be avoided more reliably than before. Furthermore, unmanned and / or remotely controlled processes can be monitored more effectively and reliably, thereby preventing or at least limiting costly production errors.

[0107] Furthermore, the method can advantageously be used to continuously monitor bulk material fed into a dosing device and to suggest a new configuration for the dosing device and / or to terminate an ongoing dosing process if the properties of the bulk material have changed and the existing configuration of the dosing device no longer meets defined quality criteria. This allows the method to further improve the safety and reliability of the dosing process.

[0108] This method also makes it particularly advantageous to operate an existing dosing device safely and reliably with different bulk materials without significant effort. This increases the utilization of the dosing device and thus its economic efficiency, and can also improve operational safety.

[0109] Above all, the proposed method enables even a layperson to fill a dosing device. Furthermore, the monitoring of a dosing device can be fully or partially automated with this method, thereby further reducing or completely eliminating the potential for error introduced by a human operator.

[0110] The method according to the first aspect of the invention can advantageously be provided as a cloud service. Thus, no extensive data processing needs to take place at the location of the dosing device.

[0111] Preferably, the control signal is fed to a motor, in particular a motor controller of the metering device, wherein the motor can preferably be used to move a discharge element of the metering device. This allows the metering process to be advantageously influenced by the control signal, for example, to be started or stopped. In this way, for example, the bulk material can be assessed from the point of intake, and the discharge element of the metering device can be operated depending on this assessment.

[0112] Advantageously, the control signal can also be used to regulate and / or control an extruder and / or other dosing devices connected to the dosing device, in particular to stop and / or start their operation (for example, when several dosing devices mix a recipe and the metered materials end up in an extruder).

[0113] The control signal can also be fed into the control system of a refill valve. This allows for the control of the refill valve. For example, if a defective material has been fed into the dispenser, the control signal can be used as a control signal to close the refill valve. Alternatively or additionally, the control signal can also be used to trigger an alarm, preventing the dispenser and thus the entire system from starting.

[0114] The dosing of the bulk material can be the process in question or a sub-process of the process in question.

[0115] The entity can be used both within the dosing process and within a sub-process preceding or following the dosing process. Preferably, the entity is a device. For example, the entity can be a device that moves bulk material towards the dosing device and / or that further processes the dosed bulk material and / or conveys it away from the dosing device. It is conceivable that the entity is a selectively openable and / or closeable connecting section that links a storage container to a receiving container provided by the dosing device, and that by opening or closing the connecting section, bulk material can be transferred from the storage container to the receiving container. The control signal can then be supplied to this connecting section, thereby influencing its opening and closing.

[0116] Preferably, within the scope of this application, any handling of the bulk material that involves and / or is influenced by the metering device and / or its parts is considered part of the metering process. In one embodiment, once the bulk material has left the metering device, for example via an advantageously provided discharge chute, the bulk material is no longer considered part of the metering process.

[0117] The process is advantageously implemented using a computer.

[0118] Alternatively or additionally, it may also be provided that the dosing device is prompted by the control signal to start a dosing process with the bulk material and / or to continue an ongoing dosing process with the bulk material if the assessment is an assessment of the first assessment type and / or not of the second assessment type.

[0119] For example, the dosing device can be started or continued to operate accordingly.

[0120] Alternatively or additionally, it may also be provided that the dosing device is prompted by the control signal not to start a dosing process with the bulk material and / or to abort an ongoing dosing process with the bulk material if the assessment is an assessment of the second assessment type and / or not of the first assessment type.

[0121] For example, the dosing device cannot be started or stopped accordingly.

[0122] Alternatively or additionally, it may also be provided that the dosing device is prompted by the control signal, in particular to start a new dosing process and / or to continue a dosing process in progress, to request confirmation from a user if the assessment is an assessment of the second assessment type and / or not of the first assessment type.

[0123] This ensures that, for example, a negative assessment regarding the use of the bulk material is not overlooked. This allows the dosing process to become more reliable and safer.

[0124] For example, if confirmation is not received within a defined time period, a pending dosing process cannot be started and / or can be discarded and / or an ongoing dosing process can be aborted.

[0125] The problem is solved by the invention according to a third aspect by proposing a method for obtaining an assessment of the use of a bulk material within a process, which process at least comprises that the bulk material is dosed by means of a metering device, the method comprising that at least one image of at least one sample and / or parts of the bulk material is recorded, in particular with a camera, and is provided and received as an image in a method according to the first and / or second aspect of the invention; and obtaining an assessment of the use of the bulk material within the process and preferably outputting the assessment on a user interface, such as a handheld device.

[0126] This allows for the simple assessment and / or monitoring of bulk materials. All advantages described in relation to the method according to the first and / or second aspect of the invention also apply accordingly to the method according to the third aspect of the invention. Therefore, reference can be made to the preceding explanations at this point.

[0127] For example, the process is carried out using a smartphone. This enables mobile assessment of bulk materials by operating personnel.

[0128] The features described above relating to the bulk material, the position of the recording and the sensors used in the camera can also be provided accordingly in the method according to the third aspect of the invention.

[0129] The process is advantageously implemented using a computer.

[0130] Alternatively or additionally, it may also be provided that the assessment is displayed on a screen as an assessment of a first or second assessment type and / or, depending on the assessment type, is issued as a positive or negative confirmation tone, particularly on a handheld device.

[0131] The problem is solved by the invention according to a fourth aspect by proposing a device for data processing comprising means which are configured to carry out a method according to the first and / or second aspect of the invention.

[0132] All the advantages described in relation to the method according to the first and second aspects of the invention also apply accordingly to a data processing device according to the fourth aspect of the invention. Therefore, reference can be made to the preceding explanations at this point.

[0133] The data processing device may include the assessment module and / or the evaluation module and / or be operatively connected to them.

[0134] For example, the data processing device is a cloud computing system. The data processing device may be a distributed system.

[0135] The problem is solved by the invention according to a fifth aspect by proposing a dosing device comprising a device for data processing according to the fourth aspect of the invention.

[0136] All the advantages described with regard to the method according to the first and second aspects of the invention, and with regard to the device according to the fourth aspect of the invention, also apply accordingly to a metering device according to the fifth aspect of the invention. Therefore, reference can be made to the preceding explanations at this point.

[0137] The problem is solved by the invention according to a sixth aspect by proposing a device for data processing, in particular a smartphone, with a camera and / or a loudspeaker and further means which are configured to carry out a method according to the third aspect of the invention.

[0138] All the advantages described in relation to the method according to the third aspect of the invention also apply accordingly to a data processing device according to the sixth aspect of the invention. Therefore, reference can be made to the preceding statements at this point. Brief description of the drawings

[0139] Further features and advantages of the invention will become apparent from the following description, in which preferred embodiments of the invention are explained with reference to schematic drawings.

[0140] This shows: Fig. 1 a schematic representation of a dosing device according to the fifth aspect of the invention with further elements used in a process; Fig. 2 a flow chart of a process according to the second aspect of the invention in a first embodiment; Fig. 3 a flow chart of a process according to the second aspect of the invention in a second embodiment; Fig. 4 a schematic representation of a device for data processing according to the sixth aspect of the invention; and Fig. 5 a flowchart of a process according to the third aspect of the invention; Description of the embodiments

[0141] Fig. Figure 1 shows a schematic representation of a dosing device 1 according to the fifth aspect of the invention.

[0142] A bulk material 3 to be metered is fed to the metering device 1 from a storage container 5. From the storage container 5, the bulk material passes through a selectively openable and closeable connecting section 7 into a receiving container 9 of the metering device 1, where it exists as a bulk quantity with a surface area 11. By opening the connecting section 7, bulk material can be transferred from the storage container 5 into the receiving container 9. By means of a discharge element 13, such as a screw conveyor, the bulk material 3 is then discharged from the metering device 1, i.e., from the receiving container 9, in a manner known per se, and exits via a vertical discharge chute 15. The discharge element 13 is coupled to a motor 17 and can be rotated at an adjustable, variable speed, controlled by a motor controller of the motor 17.During material discharge, a change in weight of a system of the dosing device 1 weighed with a load cell 19 is used to control the speed of the discharge element 13.

[0143] The bulk material 3 can be processed in further process steps following the dosing process, with the necessary elements being located in Fig. 1 are not shown.

[0144] The bulk material 3 filled into the storage container 5 is detected by a camera 21 with a specific field of view 23. The camera 21 detects a portion of the bulk material 3 located on a surface 25 of the bulk material quantity received by the storage container 5. The camera 21 can then capture an image of the detected bulk material 3 in the visible spectral range.

[0145] The dosing device 1 includes a data processing device 27 according to the fourth aspect of the invention. The data processing device 27 is connected to the camera 21 via a data connection 29 (for example, in the form of a LAN cable or a radio connection). The device 27 can receive the images captured by the camera 21 via the data connection 29. Furthermore, the data processing device 27 is also coupled to the motor 17 via a data connection 31 and can thereby send instructions to the motor control of the motor 17.

[0146] The data processing device 27 includes means configured to carry out a method according to the second aspect of the invention. This allows monitoring of the metering device 1 to ensure that only bulk material suitable for the metering device 1 and / or the process under consideration is processed.

[0147] Fig. Figure 2 shows a flow chart 100 of a method according to the second aspect of the invention in a first embodiment for a corresponding monitoring of the dosing device 1, as advantageously carried out by the data processing device 27.

[0148] In 101, a recording of the bulk material 3, which was, for example, filled into the storage container 5 by operating personnel, is obtained. This can be, for example, the image section of the bulk material 3 in the storage container 5 captured by camera 21. Advantageously, the raw data (or alternatively, pre-processed image data) from the camera sensor can be received and thus obtained by camera 21.

[0149] In 103, a classification of the bulk material 3 is determined based on the image data. For this purpose, the image data is processed using an evaluation module. The evaluation module can be part of the data processing device 27. More precisely, the evaluation module is a machine learning (ML) model that, during training, has learned to classify bulk material image data based on numerous images of different bulk materials with their corresponding classifications.

[0150] The acquired image data is therefore fed into the evaluation module and thus into the machine learning model, which is then calculated based on this image data. The output of the machine learning model then yields data representing a classification result.

[0151] The classification result represents a type of the bulk material 3 received. Examples of advantageous bulk material types are dust, powder, granules, and the like. A database contains and / or allows for the identification of those bulk material types that can be dosed by the dosing device 1 in the process under consideration. The database can be part of the data processing device 27.

[0152] In section 105, an evaluation module determines whether the classification result corresponds to a bulk material type stored in the database. In other words, it determines whether the bulk material is suitable for the dosing device 1 and / or the process.

[0153] If the classification result is stored in the database as a bulk material type, an assessment of a first assessment type is determined in 107a. Subsequently, a control signal characteristic of the first assessment type is generated in 109a. This control signal is fed to the metering device, more precisely to the motor control. Based on the control signal representing the first assessment type, the motor control activates the motor in such a way that the metering process with the added bulk material is started or an ongoing metering process is continued. That is, the discharge mechanism is actuated accordingly.

[0154] If, however, the classification result is not stored in the database as a bulk material type, an assessment of a second assessment type is determined in 107b. Subsequently, the dosing process with the filled bulk material is either aborted in 109b or not started at all. The control signal generated in 109b and sent to the motor control represents this second assessment type.

[0155] Fig. Figure 3 shows a flow chart 200 of a method according to the second aspect of the invention in a second embodiment for a corresponding monitoring of the dosing device, as advantageously carried out alternatively by the data processing device 27.

[0156] In 201, an image of the bulk material 3 is obtained, which, for example, was filled into the storage container 5 by operating personnel. This could be, for example, the image section of the bulk material 3 in the storage container 5 captured by camera 21. Advantageously, the raw data (or alternatively, pre-processed image data) from the camera sensor can be received by camera 21 for this purpose.

[0157] In 203, an identifier in the form of a material designation for the bulk material is determined based on the image data. For this purpose, the image data is processed using an evaluation module. The evaluation module can be part of the data processing device 27. More precisely, the evaluation module is a machine learning model (ML model) that, during training, has learned the relationship between a bulk material and its designation based on numerous images of different bulk materials with their corresponding material designations.

[0158] The acquired image data is therefore fed into the evaluation module and thus into the machine learning model (ML model), which is then calculated based on this image data. The output of the ML model then yields output data representing the material designation.

[0159] The identifier can be, for example, a plain-text description of the material, or an internal identification number under which the respective bulk material is managed in an ERP system. In this case, the identified identifier is an internal identification number of the bulk material.

[0160] In a database, further data can be retrieved for each bulk material via its identifier, including information on the minimum dimensions of the discharge device to be used for discharging the bulk material. The database can be part of the data processing device 27.

[0161] In section 205, the information on the minimum dimensions is queried from the database using the determined internal identification number.

[0162] In 207, the dimensions of the discharge element used in the metering device 1, thus providing information on a configuration of the metering device 1, are determined.

[0163] In section 209, an assessment module is used to determine whether the required minimum dimensions of the discharge element are met by the metering device being used. For this purpose, the values ​​determined in sections 205 and 207 are compared. In other words, this determines whether the bulk material is suitable for the metering device and / or the process.

[0164] If the dimensions of the discharge element meet the minimum requirements, an assessment of a first assessment type is determined in 211a. Subsequently, a control signal characteristic of the first assessment type is generated in 213a. This control signal is fed to the metering device, more precisely to the motor control. Based on the control signal representing the first assessment type, the motor control activates the motor in such a way that the metering process with the added bulk material is started or an ongoing metering process is continued. That is, the discharge element is actuated accordingly.

[0165] If, however, the dimensions of the discharge device do not meet the minimum requirements, a second assessment type is determined in 211b. The metering process with the filled bulk material is then subsequently aborted in 113b or not even started in the first place. The control signal generated in 213b and sent to the motor control represents this second assessment type.

[0166] Consequently, the method according to the second aspect of the invention, in both the first and second embodiments, makes it possible to determine, based on the data from the image acquisition and with the integration of the evaluation module, an assessment of the use of the bulk material within the process by means of an assessment module and, depending on the assessment, to influence the dosing process differently and thereby monitor the dosing device.

[0167] In another embodiment, the control signal could alternatively or additionally be used to prevent the opening of the connecting section 7 if the assessment is of a second assessment type. This prevents impermissible bulk material from entering the receiving container 9.

[0168] In another embodiment, an image of the surface 11 could also be obtained and an assessment of the use of the bulk material could be carried out as described above. For this purpose, the camera 21 could be provided in the receiving container 9.

[0169] It should be noted that steps 109a / b and 213a / b could be omitted if only an assessment of the use of the bulk material within the process is required. That is, if no monitoring of the dosing device is to be carried out based on the assessment obtained. Steps 101 to 107a / b and 201 to 211a / b, respectively, then each correspond precisely to a method according to the first aspect of the invention.

[0170] Fig. Figure 4 shows a schematic representation of a device for data processing 33 according to the sixth aspect of the invention.

[0171] The data processing device 33 is a smartphone with a camera 35 and a speaker 37. The device 33 offers the operating personnel of the dosing device 1 a flexible way to check the suitability of a bulk material 3 to be dosed even before it is filled into the storage container 5.

[0172] The data processing device has 33 means which are set up to carry out a method according to the third aspect of the invention.

[0173] Fig. Figure 5 shows a flow chart 300 of a method according to the third aspect of the invention for a corresponding inspection of the bulk material, as advantageously carried out by the data processing device 33.

[0174] In section 301, a user takes a picture of the bulk material. It is advantageous to use the smartphone camera to take this picture. For example, the bulk material may still be in sealed packaging that is permeable to radiation to which the camera sensor is sensitive.

[0175] In 303, the image is provided in a process according to the first and / or second aspect of the invention. In this process, the image could be obtained in a manner very similar to the process described in 101 with respect to process flow 100 or the process described in 201 with respect to process flow 200. For example, the image data could be provided accordingly.

[0176] In 305, an assessment of the use of the bulk material is received. Depending on the assessment type, the smartphone 33 can, for example, emit a warning tone or a positive confirmation tone (i.e., a positive confirmation signal) via the speaker 37. Alternatively or additionally, a corresponding message could also be displayed on a screen of the smartphone, depending on the assessment type.

[0177] Consequently, the method according to the third aspect of the invention enables a user to conveniently and mobilize an assessment of the use of a bulk material.

[0178] The features disclosed in the preceding description, in the drawings and in the claims can be essential to the invention in its various embodiments, both individually and in any combination. Reference symbol list 1 dosing device 3 Bulk goods 5 storage containers 7 Connecting section 9 collection containers 11 Surface 13 Discharge organ 15 Vertical drop 17 Engine 19 load cell 21 camera 23 field of vision 25 surface 27 Device for data processing 29 Data connection 31 Data connection 33 Device for data processing 35 Camera 37 speakers 100 Schedule 101 Obtaining a recording of bulk material 103 Classifying bulk material based on the recording data using a machine learning model 105 Determine, based on a classification result, whether the bulk material is permissible 107a, 107b Determining an assessment of the use of the bulk material 109a, 109b Generating a control signal and controlling the dosing device 200 Schedule 201 Obtaining a recording of bulk material 203 Determining an identifier for the bulk material based on the recording data using a machine learning model 205 queries for information about the bulk material from a database using the identifier 207 Determining a configuration of the dosing device 209 Determine, based on the bulk material information and the configuration, whether the bulk material is permissible 211a, 211b Determining an assessment of the use of the bulk material 213a, 213b Generating a control signal and controlling the dosing device 300 Schedule 301 Taking a Recording 303 Providing the recording in a process according to the first and / or second aspect of the invention 305 Obtaining an assessment of the use of the bulk material

Claims

[1] Method for assessing the use of a bulk material (3) within a process, which process at least includes the bulk material (3) being dosed by means of a metering device (1), the method includes the acquisition of at least one sample and / or parts of the bulk material (3), and at least partially based on the data of the acquisition, an assessment of the use of the bulk material (3) within the process is determined by means of an assessment module, wherein, by means of an evaluation module based on the data of the recording, at least one identifier and / or a classification of the bulk material (3) is determined, and the identifier and / or a result of the classification is included in the determination of the assessment, wherein the assessment involves determining, based on the identifier and / or the classification result, whether the bulk material (3) is a bulk material suitable for the dosing device (1) and / or the process. [2] Method according to claim 1, wherein the identifier of the bulk material (3) is a material designation of the bulk material (3) and / or the intake is taken behind a discharge element (13) of the metering device (1). [3] Method according to one of the preceding claims, wherein determining the assessment comprises determining, based on the identifier and / or the classification result, whether the bulk material (3) is a bulk material permissible for the metering device (1) and / or the process, wherein, for this purpose, at least partially the identifier and / or the classification result is checked against a database in which bulk material identifiers and / or bulk material classifications permissible for the metering device (1) and / or the process are specified, and / or The assessment determined is a first-type assessment if the bulk material (3) is determined to be a permissible bulk material and / or the assessment determined is a second-type assessment if the bulk material (3) is not determined to be a permissible bulk material. [4] Method according to one of claims 2 to 3, wherein the method comprises obtaining information on a bulk material (3) assigned to the identifier and / or information associated with the classification result, in particular retrieved from a database, and including it in determining the assessment. [5] Method according to any of the preceding claims, wherein the method comprises evaluating and / or analyzing the data of the first recording at least partially using methods of digital image analysis, in particular at least partially in the field of machine learning, in particular in each case to determine the classification and / or the identifier. [6] Method according to any of the preceding claims, wherein the determination of the assessment includes the inclusion of at least one piece of information relating to a sub-process, in particular a sub-process following and / or preceding the dosing process, of the process in the determination of the assessment, wherein preferably the assessment obtained is an assessment of a first type if the bulk material (3) is determined to be suitable for the respective sub-process, in particular on the basis of the identifier and / or the classification result, and / or the assessment obtained is an assessment of a second type if the bulk material (3) is determined to be unsuitable for the respective sub-process. [7] Method according to one of the preceding claims, wherein the determination of the assessment comprises at least one piece of information about a configuration of the metering device (1), such as a type designation of a, in particular interchangeable, mechanical component, such as a discharge element, of the metering device (1) and / or a value of an operating parameter of the metering device (1), such as a delivery rate and / or a speed of a motor (17) of the metering device (1), being included in the determination of the assessment, preferably the inclusion of the configuration information shows that the configuration information is evaluated in the background of the information obtained on a bulk material (3) assigned to the identifier and / or that is associated with the classification result, wherein preferably the assessment obtained is an assessment of a first assessment type if the configuration of the metering device (1) is determined to be suitable for the bulk material (3), in particular if the assessment is positive, and otherwise the assessment obtained is an assessment of a second assessment type. [8] Method according to any of the preceding claims, wherein the assessment obtained is an assessment of a first assessment type if the combination of the bulk material (3) and the metering device (1) is determined to be a permissible combination and / or the assessment obtained is an assessment of a second assessment type if the combination of the bulk material (3) and the metering device (1) is not determined to be a permissible combination. [9] Method according to one of the preceding claims, wherein a control signal indicative of the determined assessment and / or the assessment type of the determined assessment is generated and preferably, in particular as a control and / or regulation signal, is supplied to an entity and / or output to a user on a human-machine interface, such as a screen. [10] Method for monitoring a metering device (1) provided within a process for metering a bulk material (3), comprising the method of assessing the use of the bulk material (3) within the process by means of a method according to one of claims 1 to 9 and generating a control signal depending on the assessment, in particular the type of assessment, which is supplied, in particular as a control and / or regulating signal, to the metering device (1) and / or to an entity, in particular different from the metering device (1).[11] Method according to claim 10, wherein (i) the metering device (1) is caused by the control signal to start a metering operation with the bulk material (3) and / or to continue a metering operation in progress with the bulk material (3) if the assessment is an assessment of the first assessment type and / or not of the second assessment type, (ii) the metering device (1) is caused by the control signal not to start a metering operation with the bulk material (3) and / or to terminate a metering operation in progress with the bulk material (3) if the assessment is an assessment of the second assessment type and / or not of the first assessment type, and / or (iii) the metering device (1) is caused by the control signal, in particular to start a new metering operation and / or to continue a metering operation in progress, to request confirmation from a user,if the assessment is of the second assessment type and / or not of the first assessment type. [12] Method for obtaining an assessment of the use of a bulk material (3) within a process, the process comprising at least that the bulk material (3) is dosed by means of a metering device (1), the method comprising that at least one image of at least one sample and / or parts of the bulk material (3), in particular with a camera (21), is taken and provided in a method according to one of claims 1 to 9 and is obtained there as an image; and obtaining an assessment of the use of the bulk material (3) within the process and preferably outputting the assessment on a user interface, such as a handheld device. [13] Device for data processing (27) comprising means configured to carry out a method according to any one of claims 1 to 9 and / or any one of claims 10 to 11. [14] Device for data processing (33), in particular a smartphone, with a camera (33) and / or a loudspeaker (37) and further means which are configured to carry out a method according to claim 12.

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