Digital non-induction intelligent storage management and control system

Abstract

The invention provides a digital non-induction intelligent storage management and control system, and relates to the technical field of storage management and control, and the system comprises a first collection module which is used for carrying out the weight collection of a first motor part; the material frame configuration module is used for configuring a first material frame; the second acquisition module is used for acquiring the weight of the first material frame; the third acquisition module is used for configuring a weighing sensor module to carry out weight acquisition to obtain a first real-time total weight; the metering module is used for inputting an intelligent storage material metering engine and outputting the number of first parts; and the prompt generation module is used for generating first material supplement prompt information according to the first model information when the number of the first parts reaches a first number threshold value. According to the invention, the technical problem that the efficiency and accuracy of warehousing operation are affected due to the fact that manual scanning omission or wrong scanning possibly exists because material identification and inventory updating are carried out by generally depending on manual code scanning or manual data input in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of warehouse management and control, and in particular to a digital non-sensing intelligent warehouse management and control system. Background Art

[0002] Currently, many warehousing systems rely on traditional barcode and RFID technologies and manual operations to identify, manage, and track materials. While these technologies have improved the automation level of warehousing operations to a certain extent, some issues remain that cannot be ignored. On the one hand, existing technologies often rely on manual scanning or data entry for material identification and inventory updates. Human errors, negligence, or omissions can lead to inaccurate inventory data, resulting in inventory imbalances or stock-outs. On the other hand, if barcodes or RFID tags cannot be effectively read, materials may not be accurately identified. This identification instability can be caused by reasons such as damaged or obscured item tags or equipment failures, resulting in the warehouse management system being unable to obtain material information in real time, which in turn affects the efficiency and accuracy of warehousing operations. Summary of the Invention

[0003] This application provides a digital, non-sensing intelligent warehouse management and control system, aiming to solve the technical problem that the existing technology usually relies on manual scanning or manual data input for material identification and inventory updates, which may result in omissions or erroneous scanning, thereby affecting the efficiency and accuracy of warehouse operations.

[0004] The present application discloses a digital, non-inductive, intelligent warehousing management and control system, the system comprising: a first acquisition module, for collecting the weight of a first motor component of a target motor product in a target storage area to obtain the weight of the first component, wherein the target motor product is composed of multiple motor components; a material box configuration module, for configuring the first material box and mapping the first material box according to the first model information of the first motor component; a second acquisition module, for collecting the weight of the first material box to obtain the weight of the first material box; a third acquisition module, for configuring a weighing sensor module below the first material box, collecting the weight through the weighing sensor module during the material flow process, and obtaining the first real-time total weight through real-time monitoring by a PLC signal feedback unit; a metering module, for inputting the weight of the first component, the weight of the first material box, and the first real-time total weight into an intelligent warehousing material metering engine to output the first component quantity; and a prompt generation module, for generating a first material replenishment prompt message according to the first model information when the first component quantity reaches a first quantity threshold.

[0005] One or more technical solutions provided in this application have at least the following beneficial effects:

[0006] Through the weight collection function of the first collection module and the second collection module, the parts and material boxes of the target motor products can be automatically and accurately measured. Warehouse managers do not need to manually operate the barcode scanner or manually record material information, which greatly improves work efficiency and enhances the automation level of warehouse management; the material box configuration module automatically maps the material box according to the model information of the motor parts, so that each material box is directly associated with the part model information, which avoids the tediousness and errors of manual identification. Each material box in the warehouse has a unique identification, and the identification can be directly associated with the target part model, which makes warehouse management more standardized, reduces errors or confusion in the material storage and retrieval process, and improves The system improves the operational efficiency of the warehouse; the weighing sensor module configured through the third acquisition module monitors the total weight of the material box in real time, and realizes real-time data transmission through the PLC signal feedback unit. This real-time feedback mechanism helps the warehouse management system to always understand the status of the materials and avoids the risk of delayed or lost inventory information; the metering module uses the intelligent warehouse material metering engine to accurately calculate the number of motor parts in the material box by inputting the weight of the parts, the weight of the material box, and the real-time total weight. When the inventory reaches the minimum threshold, it automatically generates replenishment information, triggering the replenishment operation in advance, avoiding the occurrence of inventory shortages. This intelligent replenishment mechanism reduces the risk of warehouse out-of-stock, improves the reliability of material supply and the utilization rate of warehouse resources. Overall, the entire system does not need to rely on manual scanning or manual data entry. It adopts a cargo identification method based on weight data. By accurately collecting the weight of motor parts, it can automatically identify and track each material box and the parts therein, thus forming a highly automated cargo identification system.

[0007] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 A schematic structural diagram of a digital, non-sensing intelligent warehouse management and control system provided in an embodiment of the present application.

[0009] Figure 2 This is a structural diagram of an associated supplement prompt module in a digital, non-sensing intelligent warehousing management and control system provided in an embodiment of the present application.

[0010] Explanation of the accompanying drawings: first acquisition module 10, material box configuration module 20, second acquisition module 30, third acquisition module 40, measurement module 50, prompt generation module 60, operation process acquisition channel 71, association analysis channel 72, impact analysis channel 73, prompt information generation channel 74. DETAILED DESCRIPTION

[0011] The embodiments of the present application provide a digital, non-sensing intelligent warehouse management and control system to solve the technical problem that the existing technology usually relies on manual scanning or manual data input for material identification and inventory updates, which may result in omissions or erroneous scanning, thereby affecting the efficiency and accuracy of warehouse operations.

[0012] After introducing the basic principles of this application, various non-limiting embodiments of this application will be specifically described below in conjunction with the accompanying drawings. It should be understood that the specific embodiments described here are only used to explain this application and are not used to limit this application.

[0013] like Figure 1 As shown, the embodiment of the present application provides a digital non-sensing intelligent warehouse management and control system, the system comprising:

[0014] The first collection module 10 is used to collect the weight of a first motor component of a target motor product in a target storage area to obtain the weight of the first component, wherein the target motor product is composed of a plurality of motor components.

[0015] The target motor product refers to the complete motor equipment that requires warehouse management. The target motor product is composed of multiple components, such as the motor rotor, stator, and bearings. Each motor component has different weights and models. The first motor component is any one of these components and serves as the target for subsequent analysis. Use appropriate weighing equipment, such as a high-precision load cell or electronic balance, to individually weigh the first motor component and record its weight to provide a basis for subsequent material management and calculations.

[0016] The material box configuration module 20 is used to configure a first material box and map the first material box according to the first model information of the first motor component.

[0017] A corresponding first material box is configured for the first motor component. The material box is a container for storing components, such as a pallet or a material box. Each material box can carry a certain amount of components, and the size and quantity of the material boxes match the volume and quantity of the components. Mapping identification refers to assigning a corresponding identification to the material box. This identification contains key information related to the material. The function of this identification is to help quickly identify the content in the material box. According to the first model information of the first motor component, such as the motor type, component specifications, model, etc., the first material box is mapped and identified. The mapping identification method can be through a barcode, RFID tag or other identification symbol, so that the material box corresponds to the model information of the motor component one-to-one. By identifying the first component model in the first material box, the first material box can be tracked and managed in the warehouse management system.

[0018] The second collection module 30 is used to collect the weight of the first material frame to obtain the weight of the first material frame.

[0019] Use appropriate weighing equipment, such as a high-precision weighing sensor or electronic balance, to weigh the empty first material box. The weight obtained at this time is the weight of the first material box. This weight does not include the weight of the components in the material box, but only the weight of the box itself. The purpose of this weight collection is to provide a benchmark for subsequent real-time weight monitoring to ensure that the weight of the material box itself and the weight of its internal components can be distinguished.

[0020] The third acquisition module 40 is used to configure a weighing sensor module below the first material frame, collect weight through the weighing sensor module during the material flow process, and obtain the first real-time total weight through real-time monitoring through the PLC signal feedback unit.

[0021] A weighing sensor module is located below the first material basket. This module consists of multiple weighing sensors, each mounted on a supporting position of the basket, typically at one of its four corners or other suitable locations. These sensors collect the total weight of the basket and its contents in real time. Feedback from multiple sensors reduces measurement errors and ensures accurate weight data. Material flow refers to the transfer of parts within a warehouse or workflow. During this process, the basket undergoes handling, loading, and unloading operations. As the basket progresses through these steps, the weighing sensor module collects real-time weight changes.

[0022] The PLC (Programmable Logic Controller) signal feedback unit is an automated control unit used to receive and process signals from weighing sensors. The PLC unit converts the weight data measured by the sensor into an actionable signal and transmits it to the warehouse management system in real time, displaying the first real-time total weight in real time. The real-time total weight refers to the current total weight of the material box, including the weight of the material box itself and the weight of the parts in the box. This total weight will change with the flow of materials.

[0023] The metering module 50 is used to input the weight of the first component, the weight of the first material box, and the first real-time total weight into the intelligent warehouse material metering engine, and output the quantity of the first component.

[0024] The Intelligent Warehouse Material Measurement Engine is an advanced calculation system that processes input weight data and calculates the number of parts based on a preset formula. This engine includes pre-set algorithms for performing complex mathematical operations and data processing tasks. Using the pre-set algorithms within the Intelligent Warehouse Material Measurement Engine, the current quantity of the first part stored in the first material bin is calculated and output as the first part quantity.

[0025] The prompt generating module 60 is configured to generate first material replenishment prompt information according to the first model information when the quantity of the first component reaches a first quantity threshold.

[0026] The first quantity threshold is a pre-set minimum number of parts. When the inventory quantity reaches or falls below this value, action is required. This threshold is set by the warehouse management system based on production demand, inventory strategy and other operational considerations.

[0027] The quantity of the first component is compared with a predetermined first quantity threshold. When the quantity of the first component reaches the first quantity threshold, a first material replenishment reminder is generated based on the first model information, including the component that needs to be replenished. This replenishment reminder can be communicated to warehouse personnel or an automated replenishment system in various ways, such as via email, SMS, system pop-up windows, or user interfaces directly integrated into warehouse management. This approach also helps reduce the risk of inventory shortages and improve the accuracy and responsiveness of warehouse operations.

[0028] Furthermore, the intelligent warehouse material measurement engine includes a material measurement formula, which is as follows:

[0029]

[0030] Among them, N i is the number of components of the i-th motor, W i,total is the real-time total weight of the i-th material box, which is the sum of the weight of the i-th material box and the weight of the parts in the material box. box is the weight of the i-th material box, W i,part is the weight of the i-th component.

[0031] Specifically, the intelligent warehouse material measurement engine includes a material measurement formula, which is as follows:

[0032]

[0033] The calculation process of the formula is: From the total weight W of the material box and its contents i,total Subtract the empty box weight W of the material box i,box The difference is the total weight of the parts in the material box, and then the total weight of the parts obtained above is divided by the weight of each part W i,part , thereby calculating the number N of parts in the material box iThis formula is used for warehouse management and inventory control, especially in situations where accurate calculation of inventory quantity is required. By accurately measuring the total weight of the material box, the weight of the empty box and the weight of each component, the number of components in the material box can be accurately obtained, thereby helping warehouse managers to effectively manage inventory and optimize logistics operations.

[0034] Furthermore, the third acquisition module includes:

[0035] The module configuration channel is used to configure the weighing sensor module, wherein the weighing sensor module includes multiple weighing sensors, each weighing sensor is respectively arranged at the bottom support position of the first material frame, and the multiple weighing sensors transmit the measured weight data in real time through the PLC signal feedback unit.

[0036] The weighing sensor module includes multiple weighing sensors, each of which should be highly accurate and adaptable to the warehouse environment. Common sensor types include resistive strain gauge sensors and capacitive sensors. Each sensor is mounted on the bottom support of the first material frame. Preferably, the sensors are fixed to the four corners or support points of the material frame to balance the weight and ensure measurement accuracy. All weighing sensors are connected to the PLC signal feedback unit via an appropriate interface, such as a cable or wireless connection. The PLC signal feedback unit is responsible for collecting the weight data measured by each sensor and processing this data in real time to ensure accurate and timely data transmission from the sensor to the system.

[0037] Furthermore, if Figure 2 As shown, the system further includes an associated supplement prompt module, including:

[0038] The operation process acquisition channel 71 is used to obtain the logistics operation process of the target storage area; the association analysis channel 72 is used to perform material flow association analysis based on the logistics operation process to obtain the first flow-related motor component of the first motor component; the impact analysis channel 73 is used to perform flow impact analysis on the first motor component and the first flow-related motor component to obtain a first association influence coefficient; the prompt information generation channel 74 is used to generate associated supplementary prompt information of the first flow-related motor component according to the first association influence coefficient when the quantity of the first component reaches a first quantity threshold.

[0039] The logistics operation process refers to the flow path and operation sequence of materials in the warehouse, usually including the entire process from receiving raw materials, storage, sorting, handling, transportation to final use or distribution. The operation process data is extracted from the logistics management system.

[0040] The purpose of material flow association analysis is to determine the flow relationship between a certain material (such as the first motor component) and other components in the target storage area. This analysis helps to understand the interdependence of materials in the warehouse and how they flow together. Flow association analysis establishes associations between materials by analyzing information such as material entry and exit, storage, and transportation. For example, the first motor component may have a common flow path with other materials such as auxiliary components. The first flow-associated motor component of the first motor component is obtained through association analysis, which means that the first flow-associated motor component will circulate or be used together with the first motor component.

[0041] Flow impact analysis is the process of evaluating the mutual influence between parts during the flow of materials in the warehouse. By analyzing the correlation between the flow paths of parts, the impact of the quantity change of one part on other parts can be evaluated. The first correlation impact coefficient is a quantitative coefficient obtained through flow impact analysis, which represents the extent to which the quantity change of the first motor part (for example, inventory decrease or increase) affects the demand change of the first flow-related motor part. For example, if the inventory of the first motor part decreases and it has a strong flow correlation with the second motor part, the inventory of the second motor part may also decrease.

[0042] The purpose of the associated supplementary prompt information is to provide supplementary suggestions for associated parts (first flow-associated motor parts) by calculating the circulation impact coefficient when the inventory of the first motor parts reaches the set threshold. The prompt information includes the current inventory of the first motor parts, the demand changes of the associated first flow-associated motor parts, the recommended supplementary quantity of the first flow-associated motor parts, etc. This information can be conveyed to relevant staff through the warehouse management system interface display, email notification, text message or automatically generated orders.

[0043] Furthermore, the impact analysis channel includes:

[0044] A quantity change record establishment node is used to establish a first quantity change record of the first motor component within a preset time period, and a first associated quantity change record of the first circulation-associated motor component; a correlation analysis node is used to perform a quantity change correlation analysis on the first associated quantity change record based on the first quantity change record, and generate the first associated influence coefficient based on the correlation analysis result.

[0045] Preset time periods, such as daily, weekly, or monthly, are used to record changes in component quantity. This time period should be determined based on the speed of business operations and the frequency of component usage. A first quantity change record for the first motor component is established within the preset time period, including records of the first motor component's inbound, outbound, and inventory changes during this period. This data can be automatically extracted from the warehouse management system. Furthermore, changes in the quantity of first-circulation-related motor components related to the first motor component's circulation are recorded within the preset time period.

[0046] The purpose of quantity change correlation analysis is to analyze how the quantity change of the first motor parts affects the quantity change of the parts associated with it (first flow-related motor parts). Specifically, statistical methods are used to analyze the quantity change relationship between the two types of parts. Correlation analysis, regression analysis, time series analysis and other methods can be applied. Taking the first quantity change record as a benchmark, the relationship between the first related quantity change record and the quantity change in the first quantity change record is analyzed. For example, when the quantity of the first motor parts increases, whether the demand for the first flow-related motor parts also increases, and the proportion or trend of this change.

[0047] Based on the results of the correlation analysis, the first correlation influence coefficient is determined. This is a quantitative indicator that represents the expected impact of the change in the quantity of the first motor parts on the quantity of the first flow-related motor parts. For example, if it is found that for every increase of 100 first motor parts, the demand for the first flow-related motor parts increases by 10, then the correlation influence coefficient can be set to 0.1.

[0048] Furthermore, the system further includes a feedback correction module, including:

[0049] The output data acquisition channel is used to obtain the output data of the intelligent warehouse material measurement engine and determine whether the output data is an integer; the output data splitting channel is used to split the output data to obtain the measurement base and measurement residual if the output data is not an integer; the first feedback correction channel is used to perform weight collection feedback correction based on the measurement residual.

[0050] The intelligent warehouse material measurement engine is responsible for processing the input weight data (such as the weight of the material box, the weight of the parts, etc.) and outputting the number of parts. It obtains the output data of the intelligent warehouse material measurement engine and checks whether the output data is an integer. This can be done by performing decimal point judgment on the output data.

[0051] If the output data is a non-integer, it can be split into an integer part and a decimal part. The integer part is the measurement base, which represents the main quantity of the parts, and the decimal part is the measurement residual, which represents the deviation of the part quantity. For example, in 10.75, 10 is the measurement base and 0.75 is the measurement residual.

[0052] We perform weight collection feedback correction based on measurement residuals to ensure that the number of parts accurately reflects the actual inventory. The correction method is designed according to the specific conditions of the warehouse system. For example, if the residual is large and repeated collection still has a large error, the weighing equipment needs to be adjusted, such as calibrating the sensor. Dynamic correction of the weighing sensor is performed, and the feedback is continuously monitored and adjusted to ensure that the data remains accurate.

[0053] Furthermore, the feedback correction module further includes:

[0054] A review instruction generation channel is used to generate a review instruction if the output data is an integer; a quantity review channel is used to review the quantity of parts according to the output data based on the review instruction to obtain a review result; a second feedback correction channel is used to perform weight collection feedback correction based on the output data if the review result fails.

[0055] If the output data of the intelligent warehouse material measurement engine is already an integer, for example, the output value is 10, it means that the material quantity already appears to be accurate and has no decimal part. At this time, a review instruction is automatically generated to instruct to check whether the quantity in the material box meets the output value.

[0056] The review process uses manual or automated equipment to verify whether the actual inventory quantity is consistent with the system output quantity. The review results may be one of two situations: the review passes, which means that the actual quantity is consistent with the system output quantity; the review fails, which means that the actual quantity is inconsistent with the system output quantity, and errors or omissions may occur.

[0057] If the verification results indicate an inconsistency—that is, the actual quantity differs from the output integer quantity—the feedback correction mechanism is activated. For example, if the weight of certain components is not as expected, such as if a component is heavier or lighter than the standard weight, the measurement method or weighing equipment deviation is adjusted. If the error is due to sensor failure or equipment inaccuracy, the equipment is prompted for calibration. After analyzing and correcting these discrepancies, the adjusted data is fed back to the warehouse management system to update inventory data and output information.

[0058] Furthermore, the first feedback correction channel includes:

[0059] A static tolerance threshold establishment node is used to establish a static tolerance threshold based on a weight collection device; an environmental data collection node is used to collect environmental data of a target storage area and obtain an environmental data set; a dynamic tolerance threshold establishment node is used to dynamically compensate the static tolerance threshold based on the environmental data set and establish a dynamic tolerance threshold; a feedback correction node is used to perform weight collection feedback correction when the measurement residual reaches the dynamic tolerance threshold, wherein the correction objects include the weight of the first component, the weight of the first material box, and the first real-time total weight.

[0060] The static tolerance threshold is determined based on the standard error of the weight collection device and the equipment specifications. This threshold defines the maximum measurement deviation that the system can accept under ideal conditions without external interference. It is usually set based on historical data and equipment accuracy test results.

[0061] Environmental data collection includes real-time monitoring of environmental factors such as temperature, humidity, and vibration in the target storage area. This data is crucial for adjusting the behavior of measurement equipment because these environmental variables may affect the accuracy of measurement results. Environmental data collection can be completed through a network of sensors installed in the warehouse. These sensors can continuously monitor and record environmental conditions to generate environmental data sets.

[0062] The dynamic compensation process is to adjust the static tolerance threshold based on the collected environmental data set. This adjustment is to reflect the actual impact of changing environmental conditions on weight measurement. The dynamic tolerance threshold is the result of adjusting the static threshold. It combines factors such as the impact of temperature changes on the accuracy of electronic weighing equipment and the potential impact of humidity changes on material weight. For example, if the temperature increase may cause the performance of certain electronic components to degrade, the dynamic tolerance threshold is adjusted from ±0.1kg to ±0.15kg to adapt to this environmental change.

[0063] When the measurement residual reaches the set dynamic tolerance threshold, the weight collection feedback correction process is triggered. For example, the weight of the first component, the weight of the first material box, and the first real-time total weight are recollected, and these weight data are corrected to ensure their accuracy. This includes readjusting or calibrating the weight collection device and recalculating the weight data based on the new environmental conditions. After correction, the number of components is recalculated and the system data is updated to reflect the latest measurement results. By establishing a dynamic tolerance threshold and making environmental adaptability adjustments, the intelligent warehousing system can effectively respond to the challenges brought about by environmental changes and improve the accuracy and reliability of weight measurement. This dynamic adjustment mechanism ensures that the system can maintain high efficiency and precision under various operating conditions, thereby improving overall warehouse management efficiency.

[0064] In summary, the digital, non-sensing, intelligent warehouse management and control system provided by the embodiments of the present application has the following technical effects:

[0065] Through the weight collection function of the first collection module and the second collection module, the parts and material boxes of the target motor products can be automatically and accurately measured. Warehouse managers do not need to manually operate the barcode scanner or manually record material information, which greatly improves work efficiency and enhances the automation level of warehouse management; the material box configuration module automatically maps the material box according to the model information of the motor parts, so that each material box is directly associated with the part model information, which avoids the tediousness and errors of manual identification. Each material box in the warehouse has a unique identification, and the identification can be directly associated with the target part model, which makes warehouse management more standardized, reduces errors or confusion in the material storage and retrieval process, and improves The system improves the operational efficiency of the warehouse; the weighing sensor module configured through the third acquisition module monitors the total weight of the material box in real time, and realizes real-time data transmission through the PLC signal feedback unit. This real-time feedback mechanism helps the warehouse management system to always understand the status of the materials and avoids the risk of delayed or lost inventory information; the metering module uses the intelligent warehouse material metering engine to accurately calculate the number of motor parts in the material box by inputting the weight of the parts, the weight of the material box, and the real-time total weight. When the inventory reaches the minimum threshold, it automatically generates replenishment information, triggering the replenishment operation in advance, avoiding the occurrence of inventory shortages. This intelligent replenishment mechanism reduces the risk of warehouse out-of-stock, improves the reliability of material supply and the utilization rate of warehouse resources. Overall, the entire system does not need to rely on manual scanning or manual data entry. It adopts a cargo identification method based on weight data. By accurately collecting the weight of motor parts, it can automatically identify and track each material box and the parts therein, thus forming a highly automated cargo identification system.

[0066] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A digital non-sensing intelligent warehouse management and control system, characterized by: The system comprises: A first collection module is configured to collect the weight of a first motor component of a target motor product in a target storage area to obtain the weight of the first component, wherein the target motor product is composed of a plurality of motor components; A material box configuration module, configured to configure a first material box and map and identify the first material box according to the first model information of the first motor component; A second collection module is used to collect the weight of the first material box to obtain the weight of the first material box; a third collection module, configured to configure a weighing sensor module below the first material frame, collect weight through the weighing sensor module during material flow, and obtain a first real-time total weight through real-time monitoring by a PLC signal feedback unit; A metering module, configured to input the weight of the first component, the weight of the first material frame, and the first real-time total weight into an intelligent warehouse material metering engine, and output the quantity of the first component; A prompt generation module is used to generate first material replenishment prompt information according to the first model information when the quantity of the first component reaches a first quantity threshold.

2. A digital non-inductive intelligent warehouse management and control system as claimed in claim 1, characterized in that: The intelligent warehouse material measurement engine includes a material measurement formula, which is as follows: Among them, N i is the number of components of the i-th motor, W i,total is the real-time total weight of the i-th material box, which is the sum of the weight of the i-th material box and the weight of the parts in the material box. box is the weight of the i-th material box, W i,part is the weight of the i-th component.

3. A digital non-inductive intelligent warehouse management and control system as claimed in claim 1, characterized in that: The third acquisition module includes: The module configuration channel is used to configure the weighing sensor module, wherein the weighing sensor module includes multiple weighing sensors, each weighing sensor is respectively arranged at the bottom support position of the first material frame, and the multiple weighing sensors transmit the measured weight data in real time through the PLC signal feedback unit.

4. A digital non-inductive intelligent warehouse management and control system as claimed in claim 1, characterized in that: The system further includes an associated supplement prompt module, including: An operation process acquisition channel, used to acquire the logistics operation process of the target storage area; a correlation analysis channel, configured to perform a material flow correlation analysis based on the logistics operation process to obtain first flow-related motor components of the first motor component; an impact analysis channel, configured to perform a flow impact analysis on the first motor component and the first flow-related motor component to obtain a first correlation impact coefficient; A prompt information generation channel is used to generate associated supplementary prompt information of the first circulation-related motor component according to the first associated influence coefficient when the quantity of the first component reaches a first quantity threshold.

5. A digital non-inductive intelligent warehouse management and control system as claimed in claim 4, characterized in that: The impact analysis channel includes: A quantity change record establishment node, configured to establish a first quantity change record of the first motor component and a first associated quantity change record of the first flow-associated motor component within a preset time period; The correlation analysis node is configured to perform a quantity change correlation analysis on the first associated quantity change record based on the first quantity change record, and generate the first associated influence coefficient according to the correlation analysis result.

6. A digital non-inductive intelligent warehouse management and control system as claimed in claim 1, characterized in that: The system further includes a feedback correction module, comprising: An output data acquisition channel, used to acquire the output data of the intelligent warehouse material metering engine and determine whether the output data is an integer; An output data splitting channel, used for splitting the output data to obtain a measurement base and a measurement residual if the output data is not an integer; The first feedback correction channel is used to perform weight collection feedback correction based on the measurement residual.

7. A digital non-inductive intelligent warehouse management and control system as claimed in claim 6, characterized in that: The feedback correction module also includes: a review instruction generating channel, for generating a review instruction if the output data is an integer; A quantity review channel, for reviewing the quantity of parts according to the review instruction and the output data to obtain a review result; The second feedback correction channel is used to perform weight collection feedback correction based on the output data if the review result fails.

8. The digital non-inductive intelligent warehouse management and control system according to claim 6, characterized in that: The first feedback correction channel includes: A static tolerance threshold establishment node, used to establish a static tolerance threshold according to a weight collection device; Environmental data collection node, used to collect environmental data of the target storage area and obtain environmental data sets; A dynamic tolerance threshold establishment node, configured to dynamically compensate the static tolerance threshold according to the environmental data set to establish a dynamic tolerance threshold; The feedback correction node is used to perform weight collection feedback correction when the measurement residual reaches the dynamic tolerance threshold, wherein the correction objects include the weight of the first component, the weight of the first material frame, and the first real-time total weight.

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