Remote 3D printer sharing method and system based on 5G communication

Abstract

The invention discloses a remote 3D printer sharing method and system based on 5G communication, and relates to the technical field of sharing 3D printing, the method establishes communication with a 3D printer through an API interface through a sharing platform, and a user can upload a printing task model through the sharing platform; the method comprises the following steps: acquiring a state data set and an operation data set of a 3D printer in real time, calculating a matching availability scoring coefficient kyx, and carrying out preliminary evaluation on the matching availability scoring coefficient kyx and an equipment availability scoring threshold A; and when the 3D printer meets the distribution condition, analyzing equipment material data and task requirements, performing task matching by using a multi-objective optimization algorithm, outputting a comprehensive task matching index ZHP, performing deep evaluation on the comprehensive task matching index ZHP and a preset task printing matching threshold B, and distributing a proper printing task for the 3D printer. According to the method, the utilization rate of 3D printer resources is effectively increased, the task allocation process is optimized, and high efficiency of task execution and printing quality are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of shared 3D printing, and in particular to a remote shared 3D printer method and system based on 5G communication. Background Art

[0002] With the rapid development of modern manufacturing technology, 3D printing has gradually expanded from industrial manufacturing to multiple fields such as medical care, education and consumer goods, becoming an important force in promoting social innovation. At the same time, the concept of resource sharing economy has become increasingly popular, giving rise to various emerging service models with sharing as the core. However, traditional 3D printing equipment is generally expensive, which limits its popularity among small and medium-sized enterprises and individual users. By introducing 5G communication technology, remote shared 3D printing has become an important means to solve these problems. The high bandwidth and low latency characteristics of 5G networks provide technical support for real-time data transmission and equipment monitoring, enabling the sharing platform to quickly respond to user needs, perform efficient task allocation and equipment management, thereby promoting the popularization of shared manufacturing models, improving production efficiency and resource utilization, and promoting the development of manufacturing in a more intelligent and intensive direction.

[0003] Currently, in the 3D printing sharing platform, the detailed matching tasks of 3D printers still face some challenges and limitations. Existing technologies usually rely on basic status data and rough load analysis when matching printing tasks with equipment, and are not easy to dynamically and accurately adjust task allocation. This simple matching method leads to waste of resources, unbalanced equipment load, delays and even equipment damage under high load. Traditional methods find it difficult to fully utilize real-time data for efficient task allocation, which affects the utilization rate and output quality of 3D printers. In addition, the lack of data integration on the status and stability of equipment materials also limits the accurate assessment of equipment availability. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a remote shared 3D printer method and system based on 5G communication, which solves the problems in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: A remote sharing 3D printer method based on 5G communication, comprising the following steps:

[0006] S1. Establish a communication connection between the 3D printer and the sharing platform through the API communication interface and register relevant information. The user registers a personal account through the sharing platform and uploads the 3D model file to be printed through the 5G communication network;

[0007] S2. The sharing platform collects the equipment status data group and the operation data group in real time through the printer task monitoring system and the sensor group installed on the 3D printer, obtains the operation stability data group after pre-processing, and transmits it to the relational database for storage through the 5G communication network;

[0008] S3, performing summary calculation based on the stable operation data group to obtain the printer load factor dfz and the printer health factor sjk;

[0009] S4. Based on the printer load coefficient dfz and the printer health coefficient sjk, combined with the network delay yc, a summary calculation is performed to obtain the matching availability score coefficient kyx, and then the availability is evaluated with the preset device availability score threshold A;

[0010] S5. When the preliminary assessment shows that the 3D printer can be assigned a task, the printing data group is collected in real time, and preprocessing is performed to obtain the equipment material data group. Summary calculations are performed based on the equipment material data group to obtain the material availability index cky and the printer task requirement matching degree rwp. Combined with the matching availability score coefficient kyx, a comprehensive calculation is performed to obtain the comprehensive task matching index ZHP, which is then deeply evaluated with the preset task printing matching threshold B.

[0011] Preferably, said S1 includes S11 and S12;

[0012] S11. Establish a communication connection between the 3D printer and the sharing platform through the API communication interface and register detailed information, including device model, supported material types, current status and geographic location. The sharing platform reviews and verifies all connected devices;

[0013] S12. The user registers through the sharing platform, creates a personal account, and sets personal information and preferences. After registration, the user uploads the 3D model file to be printed to the sharing platform through the 5G communication network through the user-side APP, and provides a detailed description of the project, including the required materials, printing size and expected completion time.

[0014] Preferably, S2 includes S21, S22 and S23;

[0015] S21, collecting the device status data group of the 3D printer in real time through the 3D printer task monitoring system, and transmitting it to the sharing platform through the 5G communication network;

[0016] S22, collecting an operation data group of the 3D printer in real time through a sensor group installed in the 3D printer, wherein the sensor group includes a temperature sensor and a current sensor;

[0017] The sensor group communicates with the sharing platform through the 5G communication network and transmits the operation data group to the sharing platform in real time;

[0018] S23, the sharing platform receives the operation data group in real time, and then performs denoising, missing value filling, duplication removal and dimensionless processing on the operation data group and the equipment status data group to obtain the operation stability data group;

[0019] The sharing platform organizes the stable operation data group according to the factors affecting the 3D printer load and equipment health, and divides the stable operation data group into a load data group and a health data group;

[0020] The load data group includes task occupancy ratio zy, queue waiting task quantity dl, operating temperature yw and material replacement frequency pl;

[0021] The state data group includes the operation time ys, the printing speed sd, the temperature fluctuation amplitude wd and the current fluctuation amplitude db;

[0022] The sharing platform transmits stable operating data sets to a relational database through the 5G communication network for storage, and annotates each data with timestamp, data identifier, data type and data source.

[0023] Preferably, said S3 includes S31, S32 and S33;

[0024] S31, the sharing platform analyzes the device health status of the 3D printer and the load status of the processed files based on the acquired stable operation data group of the 3D printer;

[0025] S32, analyzing the load state of the 3D printer according to the acquired load data group, summarizing and calculating, and obtaining the printer load coefficient dfz;

[0026] The printer load factor dfz is calculated using the following formula:

[0027]

[0028] Where, dfz i represents the load factor of the i-th 3D printer, zy i represents the current task occupancy ratio of the i-th 3D printer, dl i represents the number of tasks waiting in the queue of the i-th 3D printer, yx i represents the printing task priority of the i-th 3D printer, yw i represents the average operating temperature of the i-th 3D printer, pl i represents the material replacement frequency of the i-th 3D printer, k1 and k2 represent the adjustment coefficients of the queue waiting task volume dl and the material replacement frequency pl, respectively, and ∈ represents the minimum value to prevent the denominator from being zero;

[0029] S33, analyzing the operating status and health of the 3D printer according to the acquired status data group, summarizing and calculating, and obtaining the printer health coefficient sjk;

[0030] The printer health factor sjk is calculated using the following formula:

[0031]

[0032] In the formula, ln represents the logarithmic function, sjk i represents the 3D printer health factor of the i-th 3D printer, ys i represents the running time of the i-th 3D printer, sd i represents the printing speed of the i-th 3D printer, wd i Indicates the temperature fluctuation amplitude of the i-th 3D printer, db i represents the current fluctuation amplitude of the i-th 3D printer, and k3 represents the weight coefficient of temperature fluctuation wd and current fluctuation db.

[0033] Preferably, said S4 includes S41 and S42;

[0034] S41. The sharing platform preliminarily analyzes the status and task load of the 3D printer, combines the impact of the network delay of 5G communication on the status analysis of the 3D printer, and builds a task execution availability model through an intelligent matching algorithm. The obtained printer load coefficient dfz and printer health coefficient sjk are input into the task execution availability model to calculate and obtain the matching availability score coefficient kyx.

[0035] The matching availability score coefficient kyx is calculated by the following formula:

[0036]

[0037] In the formula, kyx i represents the matching availability score coefficient of the i-th 3D printer, yc i represents the network delay of the i-th 3D printer, and ln represents the logarithmic function.

[0038] Preferably, the S42 includes S421 and S422;

[0039] S421, extracting the 3D printer historical operation stability data group from the relational database, and inputting it into the task execution availability model, and using the statistical analysis method to calculate the mean of the historical matching availability score coefficient, and setting the obtained mean as the equipment availability score threshold A;

[0040] S422, compare the obtained matching availability score coefficient kyx with the device availability score threshold A, and preliminarily evaluate the task allocatability of the 3D printer. The specific evaluation scheme is as follows;

[0041] When the matching availability score coefficient kyx ≥ the device availability score threshold A, the device can be assigned tasks and deeply evaluated;

[0042] When the matching availability score coefficient kyx is less than the device availability score threshold A, the device cannot perform the assigned task, and the 3D printer has overload, obsolescence and fault problems. The sharing platform marks the registration ID of the 3D printer and generates early warning information, which is transmitted to relevant personnel for detection through the 5G communication network.

[0043] Preferably, the S5 includes S51, S52 and S53;

[0044] S51, when it is preliminarily assessed that the 3D printer can be assigned a task, the printing material data and the 3D printer performance data of the 3D printer are analyzed according to the printing task uploaded to the sharing platform by the user-side APP, and the printing data group is collected in real time through the installed encoder and the 3D printer task monitoring system;

[0045] The encoder communicates with the sharing platform through the 5G communication network and transmits the printing data group to the sharing platform in real time;

[0046] The sharing platform receives the printing data set in real time, and then performs denoising, missing value filling, duplication removal and dimensionless processing on the printing data set to obtain the equipment material data set;

[0047] The sharing platform organizes the equipment material data group according to the factors affecting the remaining materials and task matching of the 3D printer, and divides it into a material availability data group and a task matching data group;

[0048] The material availability data set includes the remaining material inventory kc, the material consumption rate xh and the replenishment time gy;

[0049] The task matching degree data group includes a stable printing speed peak value ms and a supported resolution sf;

[0050] The sharing platform transmits the equipment material data group to the relational database through the 5G communication network for storage, and annotates each data with a timestamp, data identifier, data type and data source;

[0051] S52, performing summary calculation based on the acquired material availability data group to obtain the material availability index cky;

[0052] The material availability index cky is calculated by the following formula:

[0053]

[0054] In the formula, cky i represents the material availability index of the i-th 3D printer, kc i represents the remaining material inventory of the i-th 3D printer, xh i represents the material consumption rate of the i-th 3D printer, gy i represents the time required to replenish the i-th 3D printer, log represents the logarithmic function, and ∈ represents the minimum value that prevents the denominator from being zero;

[0055] Based on the obtained task matching degree data group and in combination with the printing requirements of the user's printing task, a summary calculation is performed to obtain the printer task requirement matching degree rwp;

[0056] The printer task requirement matching degree rwp is calculated by the following formula:

[0057]

[0058] In the formula, z represents the compatibility coefficient of the 3D printer's support for basic materials, ms i represents the peak stable printing speed of the i-th 3D printer, sf i represents the supported resolution of the i-th 3D printer, cg represents the resolution requirement of the task, ts represents the printing speed required by the task, sl represents the number of prints required by the task, and tt represents the printing time required by the task.

[0059] Preferably, the S53 includes S531 and S532;

[0060] S531. By analyzing the performance indicators and available materials of 3D printers, conducting a comprehensive analysis of the real-time data and historical data of 3D printers, and using a multi-objective optimization algorithm to deeply evaluate the adaptability of each 3D printer, a task matching model is constructed, and then the obtained matching availability score coefficient kyx, material availability index cky and printer task demand matching degree rwp are input into the task matching model, and the task matching model is used to summarize and calculate, and the comprehensive task matching index ZHP is output to assign appropriate printing tasks to each 3D printer;

[0061] The comprehensive task matching index ZHP is calculated by the following formula:

[0062]

[0063] Wherein, ln represents the logarithmic function.

[0064] Preferably, S532, by collecting a large number of equipment and material data groups of existing 3D printers, including 3D printers that can be assigned tasks and 3D printers that cannot be assigned tasks, combining the matching availability score coefficient kyx of each 3D printer and the printing requirements of the sharing platform users, inputting the task matching model for comprehensive analysis, calculating the comprehensive task matching index ZHP of each 3D printer, and calculating the average value through statistical analysis method to preset the task printing matching threshold B;

[0065] The obtained task printing matching threshold B and the comprehensive task matching index ZHP are used for task matching evaluation, and the task matching degree of the 3D printer is deeply evaluated. The specific evaluation scheme is as follows;

[0066] When the comprehensive task matching index ZHP ≥ the task printing matching threshold B, it means that the 3D printer meets the printing requirements and the printing task is assigned;

[0067] When the comprehensive task matching index ZHP is less than the task printing matching threshold B, it means that the 3D printer does not meet the printing requirements. At this time, an overload signal is generated and transmitted to S4 through the 5G communication network to reallocate the printing task.

[0068] A remote shared 3D printer system based on 5G communication, comprising a device access module, a device status acquisition module, an intelligent analysis module, a usability evaluation module and a task matching module;

[0069] The device access module establishes a communication connection between the 3D printer and the sharing platform through the API communication interface and registers relevant information. The user registers a personal account through the sharing platform and uploads the 3D model file to be printed through the 5G communication network;

[0070] The device status acquisition module uses a shared platform to collect device status data groups and operation data groups in real time through a printer task monitoring system and a sensor group installed on a 3D printer, obtains an operation stability data group after preprocessing, and transmits it to a relational database for storage through a 5G communication network;

[0071] The intelligent analysis module is used to perform summary calculation based on the stable operation data group and the network delay yc to obtain the printer load factor dfz and the printer health factor sjk;

[0072] The availability evaluation module is used to perform summary calculation based on the printer load coefficient dfz and the printer health coefficient sjk, obtain the matching availability score coefficient kyx, and then perform availability evaluation with the preset device availability score threshold A;

[0073] The task matching module is used to collect the printing data group in real time when it is preliminarily assessed that the 3D printer can be assigned a task, perform preprocessing to obtain the equipment material data group, perform summary calculation based on the equipment material data group, obtain the material availability index cky and the printer task requirement matching degree rwp, perform comprehensive calculation in combination with the matching availability scoring coefficient kyx, obtain the comprehensive task matching index ZHP, and then perform in-depth evaluation with the preset task printing matching threshold B.

[0074] The present invention provides a remote shared 3D printer method and system based on 5G communication. It has the following beneficial effects:

[0075] (1) This method uses the high-speed transmission of the 5G communication network to achieve real-time communication between the sharing platform and the 3D printer. It supports users to register an account on the sharing platform and upload the 3D model files to be printed. At the same time, the sharing platform registers detailed device information for each connected 3D printer, including model, material type, and geographic location. After the device is connected, the sharing platform uses the API communication interface and sensor group to monitor the 3D printer, collect device status data and operation data in real time, and store the data in a relational database after preprocessing, providing basic data support for subsequent device health assessment and load analysis.

[0076] (2) This method uses a sharing platform to evaluate the real-time load status and health status of the device by calculating the printer load coefficient dfz and the printer health coefficient sjk. The sharing platform combines the 5G network delay factor to design a task execution availability model, and evaluates the availability of the device by calculating the matching availability score coefficient kyx to ensure that the task can be assigned to a device with suitable performance and healthy status. After preliminarily screening the available devices, the sharing platform analyzes the material data and task matching requirements, and determines the degree of matching between the device and the task by calculating the material availability index cky and the printer task requirement matching degree rwp, laying the foundation for achieving refined task allocation.

[0077] (3) In terms of task matching and resource allocation, the sharing platform uses a multi-objective optimization algorithm to combine the matching availability score coefficient kyx, the material availability index cky, and the printer task demand matching degree rwp to construct a comprehensive task matching index ZHP to achieve intelligent allocation. In this model, the material surplus, consumption speed, and supported resolution of the equipment are all included in the calculation as influencing factors to ensure that the assigned tasks meet the equipment performance and reduce printing failures caused by insufficient materials and substandard performance. When the comprehensive task matching index ZHP of the 3D printer reaches the preset task printing matching threshold B, the sharing platform will automatically assign the printing task, otherwise it will be marked as an unavailable device and an overload warning message will be generated. Ultimately, this method effectively improves equipment utilization, optimizes resource allocation, and avoids problems such as equipment overload, insufficient materials, and improper allocation. Through precise data collection and intelligent matching, this method achieves efficient allocation of 3D printing tasks, improves the operating efficiency and user experience of the sharing platform, and promotes the intelligent and automated development of 3D printing sharing services. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 A schematic diagram of the steps of a remote shared 3D printer method based on 5G communication of the present invention;

[0079] Figure 2 This is a schematic diagram of the flow of a remote shared 3D printer system based on 5G communication in the present invention. DETAILED DESCRIPTION

[0080] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0081] Example 1

[0082] See also Figure 1 The present invention provides a remote sharing 3D printer method based on 5G communication. To achieve the above purpose, the present invention is implemented by the following technical scheme: comprising the following steps:

[0083] S1. Establish a communication connection between the 3D printer and the sharing platform through the API communication interface and register relevant information. The user registers a personal account through the sharing platform and uploads the 3D model file to be printed through the 5G communication network;

[0084] S2. The sharing platform collects the equipment status data group and the operation data group in real time through the printer task monitoring system and the sensor group installed on the 3D printer, obtains the operation stability data group after pre-processing, and transmits it to the relational database for storage through the 5G communication network;

[0085] S3, performing summary calculation based on the stable operation data group to obtain the printer load factor dfz and the printer health factor sjk;

[0086] S4. Based on the printer load coefficient dfz and the printer health coefficient sjk, combined with the network delay yc, a summary calculation is performed to obtain the matching availability score coefficient kyx, and then the availability is evaluated with the preset device availability score threshold A;

[0087] S5. When the preliminary assessment shows that the 3D printer can be assigned a task, the printing data group is collected in real time, and preprocessing is performed to obtain the equipment material data group. Summary calculations are performed based on the equipment material data group to obtain the material availability index cky and the printer task requirement matching degree rwp. Combined with the matching availability score coefficient kyx, a comprehensive calculation is performed to obtain the comprehensive task matching index ZHP, which is then deeply evaluated with the preset task printing matching threshold B.

[0088] In this embodiment, the remote sharing 3D printer method based on 5G communication realizes the complete process from task submission to intelligent allocation through five steps, significantly optimizing the use and management of shared printing resources. In the S1 module, the 3D printer accesses the sharing platform through the API interface, and the user registers and uploads the 3D model file on the sharing platform, forming a fast and efficient device and user docking process. The S2 module uses the sensor group and the 5G network to collect and transmit the device status and operation data in real time, and stores the pre-processed data in the relational database, providing complete basic data for subsequent intelligent analysis, and improving the accuracy and real-time performance of data processing. In the S3 and S4 modules, the sharing platform uses data analysis to calculate the printer load coefficient dfz and the printer health coefficient sjk, and combines the network delay yc to calculate the matching availability score coefficient kyx, thereby providing a basis for the preliminary availability evaluation of the 3D printer task. This process ensures that the load and health status of the equipment are considered before the task is assigned. Compared with traditional technologies, it avoids the misjudgment problem caused by over-reliance on manual inspection and simple scheduling algorithms. By comparing the matching availability score coefficient kyx with the preset equipment availability score threshold A, the automatic screening and preliminary task allocation of equipment are realized, and the efficiency of resource scheduling and equipment use is optimized. The S5 module deepens the task evaluation. By collecting printing data in real time and calculating the material availability index cky and the printer task requirement matching degree rwp, combined with the matching availability score coefficient kyx, the comprehensive task matching index ZHP is calculated, and then an in-depth evaluation is performed with the preset task printing matching threshold B to ensure that the equipment materials and performance meet the printing task requirements. Compared with traditional 3D printing sharing technology, this method combines multidimensional data and multi-parameter evaluation models to significantly improve the accuracy of task allocation and equipment utilization, and reduce the problems of printing failure and resource waste. On the whole, this method achieves the purpose of optimizing resource allocation, improving the completion rate of printing tasks, and enhancing system stability, and promotes the technological progress of intelligent printing scheduling.

[0089] Example 2

[0090] This embodiment is explained in Example 1, please refer to Figure 1 , specifically: the S1 includes S11 and S12;

[0091] S11. Establish a communication connection between the 3D printer and the sharing platform through the API communication interface and register detailed information, including device model, supported material types, current status and geographic location. The sharing platform reviews and verifies all connected devices to ensure that the devices can be used for sharing and meet quality and safety standards;

[0092] S12. The user registers through the sharing platform, creates a personal account, and sets personal information and preferences. After registration, the user uploads the 3D model file to be printed to the sharing platform through the 5G communication network through the user-side APP, and provides a detailed description of the project, including the required materials, printing size and expected completion time.

[0093] In this embodiment, through the detailed steps of the S1 module, the method ensures smooth access between the 3D printer and the sharing platform and convenient registration of users. In step S11, detailed registration and information review of the 3D printer are implemented through the API interface, which not only ensures that the access device meets the quality and safety standards, but also improves the reliability of device sharing and the overall credibility of the sharing platform. In step S12, the user uploads the 3D model file through a simple registration process and the user-side APP, and provides detailed project requirements, thereby achieving seamless connection between the user and the sharing platform. This design greatly improves the user experience, reduces the complexity of registration and project submission, and enables users to quickly start printing tasks while ensuring the availability of the equipment and the degree of matching the task. This efficient device review and user upload process, combined with the high-speed transmission of the 5G network, optimizes resource allocation and improves the service quality and intelligent management level of the sharing platform.

[0094] Example 3

[0095] This embodiment is explained in Example 2. Please refer to Figure 1 Specifically: S2 includes S21, S22 and S23;

[0096] S21. The device status data group of the 3D printer is collected in real time through the 3D printer task monitoring system, and transmitted to the sharing platform through the 5G communication network. The specific device status data collection steps are as follows;

[0097] The sharing platform uses the API communication interface to extract the current task status recorded by the 3D printer task monitoring system and the queue length of pending tasks in real time, record the start and end time of the task, and calculate the task occupancy ratio zy, the queue waiting task volume dl, the running time ys and the printing speed sd in the current time;

[0098] Obtain the material replacement frequency pl through the historical material replacement records recorded by the 3D printer task monitoring system;

[0099] S22, collecting an operation data group of the 3D printer in real time through a sensor group installed in the 3D printer, wherein the sensor group includes a temperature sensor and a current sensor;

[0100] The sensor group communicates with the sharing platform through the 5G communication network and transmits the operation data group to the sharing platform in real time;

[0101] The operating temperature yw of the 3D printer is collected in real time through the temperature sensor. The sharing platform analyzes the temperature data fluctuations of each component, calculates the maximum and minimum temperature difference, and obtains the temperature fluctuation amplitude wd;

[0102] Monitor current changes through current sensors and calculate the current fluctuation amplitude in db;

[0103] S23, the sharing platform receives the operation data group in real time, and then performs denoising, missing value filling, duplication removal and dimensionless processing on the operation data group and the equipment status data group to obtain the operation stability data group;

[0104] The sharing platform organizes the stable operation data group according to the factors affecting the 3D printer load and equipment health, and divides the stable operation data group into a load data group and a health data group;

[0105] The load data group includes task occupancy ratio zy, queue waiting task quantity dl, operating temperature yw and material replacement frequency pl;

[0106] The state data group includes the operation time ys, the printing speed sd, the temperature fluctuation amplitude wd and the current fluctuation amplitude db;

[0107] The sharing platform transmits stable operating data sets to a relational database through the 5G communication network for storage, and annotates each data with timestamp, data identifier, data type and data source.

[0108] In this embodiment, in the S2 module, by collecting the device status data group and operation data group of the 3D printer in real time, the sharing platform realizes accurate monitoring and data analysis of the printing task. The sharing platform uses the 5G communication network and API interface to establish a stable data transmission link with the 3D printer task monitoring system and sensor group, and transmits the real-time collected device operation data to the sharing platform. After denoising, filling missing values, deduplication and dimensionless processing of the operation data group and the device status data group, a high-quality stable operation data group is provided, which is divided into a load data group and a health data group and stored in a relational database to ensure data integrity, timeliness and structure. This process greatly improves the ability to accurately evaluate the health and load status of the equipment, enabling the sharing platform to respond to changes in the equipment status in a timely manner, optimize task allocation and resource utilization. Through this real-time and automated data processing and management method, manual monitoring and human errors are reduced, the working stability of the equipment and the success rate of printing tasks are improved, and the effective integration and application of 5G communication and data processing technologies are fully reflected.

[0109] Example 4

[0110] This embodiment is explained in Example 3, please refer to Figure 1 , specifically: S3 includes S31, S32 and S33;

[0111] S31, the sharing platform analyzes the device health status of the 3D printer and the load status of the processed files based on the acquired stable operation data group of the 3D printer;

[0112] S32, analyzing the load state of the 3D printer according to the acquired load data group, summarizing and calculating, and obtaining the printer load coefficient dfz;

[0113] The printer load factor dfz is calculated using the following formula:

[0114]

[0115] Where, dfz i represents the load factor of the i-th 3D printer, zy i represents the current task occupancy ratio of the i-th 3D printer, dl i represents the number of tasks waiting in the queue of the i-th 3D printer, yx i Indicates the printing task priority of the i-th 3D printer, represents the average operating temperature of the i-th 3D printer, pl i represents the material replacement frequency of the i-th 3D printer, k1 and k2 represent the adjustment coefficients of the queue waiting task volume dl and the material replacement frequency pl, respectively, and ∈ represents the minimum value to prevent the denominator from being zero;

[0116] S33, analyzing the operating status and health of the 3D printer according to the acquired status data group, summarizing and calculating, and obtaining the printer health coefficient sjk;

[0117] The printer health factor sjk is calculated using the following formula:

[0118]

[0119] In the formula, ln represents the logarithmic function, sjk i represents the 3D printer health factor of the i-th 3D printer, ys i represents the running time of the i-th 3D printer, sd i represents the printing speed of the i-th 3D printer, wd i Indicates the temperature fluctuation amplitude of the i-th 3D printer, db i represents the current fluctuation amplitude of the i-th 3D printer, and k3 represents the weight coefficient of temperature fluctuation wd and current fluctuation db.

[0120] In this embodiment, S31 provides the ability to monitor and diagnose the health of the device in real time by analyzing the running stable data group, which ensures the stability and reliability of the device during long-term use. The calculation method of the printer load factor dfz and the printer health factor sjk of S32 and S33 comprehensively considers multiple parameters such as task occupancy rate, queue length, running time, temperature and current fluctuations, and forms a refined assessment of the device's operating status. Compared with the traditional method that relies only on simple indicators, this multi-dimensional and data-driven analysis method can more accurately identify the load pressure and health status of the device, prevent potential overload and failure problems, thereby extending the life of the equipment and improving the accuracy of task allocation and the overall efficiency of the system.

[0121] Example 5

[0122] This embodiment is explained in Example 4. Please refer to Figure 1 , specifically: the S4 includes S41 and S42;

[0123] S41. The sharing platform preliminarily analyzes the status and task load of the 3D printer, combines the impact of the network delay of 5G communication on the status analysis of the 3D printer, and builds a task execution availability model through an intelligent matching algorithm. The obtained printer load coefficient dfz and printer health coefficient sjk are input into the task execution availability model to calculate and obtain the matching availability score coefficient kyx.

[0124] The matching availability score coefficient kyx is calculated by the following formula:

[0125]

[0126] In the formula, kyx i represents the matching availability score coefficient of the i-th 3D printer, yc i represents the network delay of the i-th 3D printer, and ln represents the logarithmic function.

[0127] The S42 includes S421 and S422;

[0128] S421, extracting the 3D printer historical operation stability data group from the relational database, and inputting it into the task execution availability model, and using the statistical analysis method to calculate the mean of the historical matching availability score coefficient, and setting the obtained mean as the equipment availability score threshold A;

[0129] S422, compare the obtained matching availability score coefficient kyx with the device availability score threshold A, and preliminarily evaluate the task allocatability of the 3D printer. The specific evaluation scheme is as follows;

[0130] When the matching availability score coefficient kyx ≥ the device availability score threshold A, the device can be assigned tasks and deeply evaluated;

[0131] When the matching availability score coefficient kyx is less than the device availability score threshold A, the device cannot perform the assigned task, and the 3D printer has overload, obsolescence and fault problems. The sharing platform marks the registration ID of the 3D printer and generates early warning information, which is transmitted to relevant personnel for detection through the 5G communication network.

[0132] In this embodiment, the sharing platform implements a preliminary intelligent analysis of the status and task load of the 3D printer, and combines the network delay factor of 5G communication to build a task execution availability model. The calculation of the matching availability score coefficient kyx and the statistical analysis of historical data enable the sharing platform to set the device availability score threshold A, thereby more accurately evaluating the task allocation capability of the 3D printer. This method ensures that task allocation not only depends on the current device status, but also comprehensively considers network delays and historical operation data of the device, making the evaluation more comprehensive and dynamic. By combining real-time data and historical data for evaluation, the sharing platform can identify potential equipment overload, obsolescence and failure problems before task allocation, generate early warning information in advance and notify relevant personnel for maintenance. This refined and intelligent evaluation mechanism improves the stability of the system and the reliability of task execution, avoids task failures or equipment overloads caused by insufficient status judgment in traditional means, and significantly improves the accuracy of overall resource management and equipment maintenance.

[0133] Example 6

[0134] This embodiment is explained in Example 5. Please refer to Figure 1 Specifically: S5 includes S51, S52 and S53;

[0135] S51. When the 3D printer is preliminarily assessed to be capable of being assigned a task, the printing material data and the performance data of the 3D printer are analyzed based on the printing task uploaded to the sharing platform by the user-side APP, and the printing data group is collected in real time through the installed encoder and the 3D printer task monitoring system. The specific steps for collecting the printing data group are as follows;

[0136] By installing encoders on the print head and transmission mechanism of the 3D printer, the print quantity and material consumption of the 3D printer are monitored in real time, and the remaining material inventory kc is obtained. Then, the material consumption speed xh and the printing speed are obtained by combining the print quantity and material consumption per unit time recorded by the 3D printer task monitoring system during the printing process. After extracting the peak value of the printing speed during stable operation, the stable printing speed peak value ms is obtained.

[0137] Obtain the time required for replenishment through the historical replenishment records recorded by the 3D printer task monitoring system;

[0138] Get the supported resolution sf of the 3D printer through the model and factory settings of the 3D printer;

[0139] The encoder communicates with the sharing platform through the 5G communication network and transmits the printing data group to the sharing platform in real time;

[0140] The sharing platform receives the printing data set in real time, and then performs denoising, missing value filling, duplication removal and dimensionless processing on the printing data set to obtain the equipment material data set;

[0141] The sharing platform organizes the equipment material data group according to the factors affecting the remaining materials and task matching of the 3D printer, and divides it into a material availability data group and a task matching data group;

[0142] The material availability data set includes the remaining material inventory kc, the material consumption rate xh and the replenishment time gy;

[0143] The task matching degree data group includes a stable printing speed peak value ms and a supported resolution sf;

[0144] The sharing platform transmits the equipment material data group to the relational database through the 5G communication network for storage, and annotates each data with a timestamp, data identifier, data type and data source;

[0145] S52, performing summary calculation based on the acquired material availability data group to obtain the material availability index cky;

[0146] The material availability index cky is calculated by the following formula:

[0147]

[0148] In the formula, cky i represents the material availability index of the i-th 3D printer, kc i represents the remaining material inventory of the i-th 3D printer, xh i represents the material consumption rate of the i-th 3D printer, gy i represents the time required to replenish the i-th 3D printer, log represents the logarithmic function, and ∈ represents the minimum value that prevents the denominator from being zero;

[0149] Based on the obtained task matching degree data group and in combination with the printing requirements of the user's printing task, a summary calculation is performed to obtain the printer task requirement matching degree rwp;

[0150] The printer task requirement matching degree rwp is calculated by the following formula:

[0151]

[0152] Where z represents the compatibility coefficient of the 3D printer's support for basic materials, and the supported material information is provided in the 3D printer's technical manual and specification sheet, ms i represents the peak stable printing speed of the i-th 3D printer, sf i represents the supported resolution of the i-th 3D printer, cg represents the resolution requirement of the task, ts represents the printing speed required by the task, sl represents the number of prints required by the task, and tt represents the printing time required by the task.

[0153] The S53 includes S531 and S532;

[0154] S531. By analyzing the performance indicators and available materials of 3D printers, conducting a comprehensive analysis of the real-time data and historical data of 3D printers, and using a multi-objective optimization algorithm to deeply evaluate the adaptability of each 3D printer, a task matching model is constructed, and then the obtained matching availability score coefficient kyx, material availability index cky and printer task demand matching degree rwp are input into the task matching model. The task matching model is used to summarize and calculate, and the comprehensive task matching index ZHP is output to assign appropriate printing tasks to each 3D printer to avoid problems such as 3D printer overload and unqualified printing;

[0155] The comprehensive task matching index ZHP is calculated by the following formula:

[0156]

[0157] Wherein, ln represents the logarithmic function.

[0158] S532, by collecting a large number of equipment and material data groups of existing 3D printers, including 3D printers that can be assigned tasks and 3D printers that cannot be assigned tasks, combined with the matching availability score coefficient kyx of each 3D printer and the printing requirements of the sharing platform users, input the task matching model for comprehensive analysis, calculate the comprehensive task matching index ZHP of each 3D printer, and calculate the average value through statistical analysis method to preset the task printing matching threshold B;

[0159] The obtained task printing matching threshold B and the comprehensive task matching index ZHP are used for task matching evaluation, and the task matching degree of the 3D printer is deeply evaluated. The specific evaluation scheme is as follows;

[0160] When the comprehensive task matching index ZHP ≥ the task printing matching threshold B, it means that the 3D printer meets the printing requirements and the printing task is assigned;

[0161] When the comprehensive task matching index ZHP is less than the task printing matching threshold B, it means that the 3D printer does not meet the printing requirements. At this time, an overload signal is generated and transmitted to S4 through the 5G communication network to reallocate the printing task.

[0162] In this embodiment, the real-time collection of printing data by encoder and task monitoring system is used, and the method realizes accurate monitoring of the material balance, consumption speed and printing performance data of the equipment, ensuring the matching of tasks and equipment. By calculating the material availability index cky and the printer task demand matching degree rwp, the sharing platform can accurately identify whether the equipment is suitable for a specific task, thereby reducing material waste and the risk of task failure. The comprehensive task matching model constructed using the multi-objective optimization algorithm effectively integrates the equipment status, material availability and task requirements, and maximizes the equipment utilization rate while ensuring the printing quality. Through in-depth evaluation through the comprehensive task matching index ZHP, the sharing platform can identify and prioritize the most suitable equipment, and timely warn and adjust inappropriate equipment to avoid overload and performance degradation, thereby improving the intelligence and sustainable operation capabilities of the sharing platform. This method significantly improves the accuracy of task allocation, the success rate of task completion and the long-term stability of the equipment, so that it can achieve a double improvement in performance and efficiency based on the current technology.

[0163] Example 7

[0164] Please refer to Figure 1 and Figure 2 , a remote shared 3D printer system based on 5G communication, including a device access module, a device status acquisition module, an intelligent analysis module, a usability evaluation module and a task matching module;

[0165] The device access module establishes a communication connection between the 3D printer and the sharing platform through the API communication interface and registers relevant information. The user registers a personal account through the sharing platform and uploads the 3D model file to be printed through the 5G communication network;

[0166] The device status acquisition module uses a shared platform to collect device status data groups and operation data groups in real time through a printer task monitoring system and a sensor group installed on a 3D printer, obtains an operation stability data group after preprocessing, and transmits it to a relational database for storage through a 5G communication network;

[0167] The intelligent analysis module is used to perform summary calculation based on the stable operation data group and the network delay yc to obtain the printer load factor dfz and the printer health factor sjk;

[0168] The availability evaluation module is used to perform summary calculation based on the printer load coefficient dfz and the printer health coefficient sjk, obtain the matching availability score coefficient kyx, and then perform availability evaluation with the preset device availability score threshold A;

[0169] The task matching module is used to collect the printing data group in real time when it is preliminarily assessed that the 3D printer can be assigned a task, perform preprocessing to obtain the equipment material data group, perform summary calculation based on the equipment material data group, obtain the material availability index cky and the printer task requirement matching degree rwp, perform comprehensive calculation in combination with the matching availability scoring coefficient kyx, obtain the comprehensive task matching index ZHP, and then perform in-depth evaluation with the preset task printing matching threshold B.

[0170] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A remote sharing 3D printer method based on 5G communication, characterized in that: The following steps are involved: S1. Establish a communication connection between the 3D printer and the sharing platform through the API communication interface and register relevant information. The user registers a personal account through the sharing platform and uploads the 3D model file to be printed through the 5G communication network; S2. The sharing platform collects the equipment status data group and the operation data group in real time through the printer task monitoring system and the sensor group installed on the 3D printer, obtains the operation stability data group after pre-processing, and transmits it to the relational database for storage through the 5G communication network; S3, performing summary calculation based on the stable operation data group to obtain the printer load factor dfz and the printer health factor sjk; S4. Based on the printer load coefficient dfz and the printer health coefficient sjk, combined with the network delay yc, a summary calculation is performed to obtain the matching availability score coefficient kyx, and then the availability is evaluated with the preset device availability score threshold A; S5. When the preliminary assessment shows that the 3D printer can be assigned a task, the printing data group is collected in real time, and preprocessing is performed to obtain the equipment material data group. Summary calculations are performed based on the equipment material data group to obtain the material availability index cky and the printer task requirement matching degree rwp. Combined with the matching availability score coefficient kyx, a comprehensive calculation is performed to obtain the comprehensive task matching index ZHP, which is then deeply evaluated with the preset task printing matching threshold B.

2. A remote shared 3D printer method based on 5G communication according to claim 1, characterized in that: Said S1 includes S11 and S12; S11. Establish a communication connection between the 3D printer and the sharing platform through the API communication interface, and register detailed information, including the device model, supported material types, current status and geographic location. The sharing platform reviews and verifies all connected devices; S12. The user registers through the sharing platform, creates a personal account, and sets personal information and preferences. After registration, the user uploads the 3D model file to be printed to the sharing platform through the 5G communication network through the user-side APP, and provides a detailed description of the project, including the required materials, printing size and expected completion time.

3. A remote sharing 3D printer method based on 5G communication according to claim 2, characterized in that: The S2 includes S21, S22 and S23; S21, collecting the device status data group of the 3D printer in real time through the 3D printer task monitoring system, and transmitting it to the sharing platform through the 5G communication network; S22, collecting an operation data group of the 3D printer in real time through a sensor group installed in the 3D printer, wherein the sensor group includes a temperature sensor and a current sensor; The sensor group communicates with the sharing platform through the 5G communication network and transmits the operation data group to the sharing platform in real time; S23, the sharing platform receives the operation data group in real time, and then performs denoising, missing value filling, duplication removal and dimensionless processing on the operation data group and the equipment status data group to obtain the operation stability data group; The sharing platform organizes the stable operation data group according to the factors affecting the 3D printer load and equipment health, and divides the stable operation data group into a load data group and a health data group; The load data group includes task occupancy ratio zy, queue waiting task quantity dl, operating temperature yw and material replacement frequency pl; The state data group includes the operation time ys, the printing speed sd, the temperature fluctuation amplitude wd and the current fluctuation amplitude db; The sharing platform transmits stable operating data sets to a relational database through the 5G communication network for storage, and annotates each data with timestamp, data identifier, data type and data source.

4. A remote sharing 3D printer method based on 5G communication according to claim 3, characterized in that: The S3 includes S31, S32 and S33; S31, the sharing platform analyzes the device health status of the 3D printer and the load status of the processed files based on the acquired stable operation data group of the 3D printer; S32, analyzing the load state of the 3D printer according to the acquired load data group, summarizing and calculating, and obtaining the printer load coefficient dfz; The printer load factor dfz is calculated using the following formula: Where, dfz i represents the load factor of the i-th 3D printer, zy i represents the current task occupancy ratio of the i-th 3D printer, dl i represents the number of tasks waiting in the queue of the i-th 3D printer, yx i Indicates the printing task priority of the i-th 3D printer, represents the average operating temperature of the i-th 3D printer, pl i represents the material replacement frequency of the i-th 3D printer, k1 and k2 represent the adjustment coefficients of the queue waiting task volume dl and the material replacement frequency pl, respectively, and ∈ represents the minimum value to prevent the denominator from being zero; S33, analyzing the operating status and health of the 3D printer according to the acquired status data group, summarizing and calculating, and obtaining the printer health coefficient sjk; The printer health factor sjk is calculated using the following formula: In the formula, ln represents the logarithmic function, sjk i represents the 3D printer health factor of the i-th 3D printer, ys i represents the running time of the i-th 3D printer, sd i represents the printing speed of the i-th 3D printer, wd i Indicates the temperature fluctuation amplitude of the i-th 3D printer, db i represents the current fluctuation amplitude of the i-th 3D printer, and k3 represents the weight coefficient of temperature fluctuation wd and current fluctuation db.

5. A remote shared 3D printer method based on 5G communication according to claim 4, characterized in that: The S4 includes S41 and S42; S41. The sharing platform preliminarily analyzes the status and task load of the 3D printer, combines the impact of the network delay of 5G communication on the status analysis of the 3D printer, and builds a task execution availability model through an intelligent matching algorithm. The obtained printer load coefficient dfz and printer health coefficient sjk are input into the task execution availability model to calculate and obtain the matching availability score coefficient kyx. The matching availability score coefficient kyx is calculated by the following formula: In the formula, kyx i represents the matching availability score coefficient of the i-th 3D printer, yc i represents the network delay of the i-th 3D printer, and ln represents the logarithmic function.

6. A remote sharing 3D printer method based on 5G communication according to claim 5, characterized in that: The S42 includes S421 and S422; S421, extracting the 3D printer historical operation stability data group from the relational database, and inputting it into the task execution availability model, and using the statistical analysis method to calculate the mean of the historical matching availability score coefficient, and setting the obtained mean as the equipment availability score threshold A; S422, compare the obtained matching availability score coefficient kyx with the device availability score threshold A, and preliminarily evaluate the task allocatability of the 3D printer. The specific evaluation scheme is as follows; When the matching availability score coefficient kyx ≥ the device availability score threshold A, the device can be assigned tasks and deeply evaluated; When the matching availability score coefficient kyx is less than the device availability score threshold A, the device cannot perform the assigned task, and the 3D printer has overload, obsolescence and fault problems. The sharing platform marks the registration ID of the 3D printer and generates early warning information, which is transmitted to relevant personnel for detection through the 5G communication network.

7. A remote shared 3D printer method based on 5G communication according to claim 6, characterized in that: The S5 includes S51, S52 and S53; S51, when it is preliminarily assessed that the 3D printer can be assigned a task, the printing material data and the 3D printer performance data of the 3D printer are analyzed according to the printing task uploaded to the sharing platform by the user-side APP, and the printing data group is collected in real time through the installed encoder and the 3D printer task monitoring system; The encoder communicates with the sharing platform through the 5G communication network and transmits the printing data group to the sharing platform in real time; The sharing platform receives the printing data set in real time, and then performs denoising, missing value filling, duplication removal and dimensionless processing on the printing data set to obtain the equipment material data set; The sharing platform organizes the equipment material data group according to the factors affecting the remaining materials and task matching of the 3D printer, and divides it into a material availability data group and a task matching data group; The material availability data set includes the remaining material inventory kc, the material consumption rate xh and the replenishment time gy; The task matching degree data group includes a stable printing speed peak value ms and a supported resolution sf; The sharing platform transmits the equipment material data group to the relational database through the 5G communication network for storage, and annotates each data with a timestamp, data identifier, data type and data source; S52, performing summary calculation based on the acquired material availability data group to obtain the material availability index cky; The material availability index cky is calculated by the following formula: In the formula, cky i represents the material availability index of the i-th 3D printer, kc i represents the remaining material inventory of the i-th 3D printer, xh i represents the material consumption rate of the i-th 3D printer, gy i represents the time required to replenish the i-th 3D printer, log represents the logarithmic function, and ∈ represents the minimum value that prevents the denominator from being zero; Based on the obtained task matching degree data group and in combination with the printing requirements of the user's printing task, a summary calculation is performed to obtain the printer task requirement matching degree rwp; The printer task requirement matching degree rwp is calculated by the following formula: In the formula, z represents the compatibility coefficient of the 3D printer's support for basic materials, ms i represents the peak stable printing speed of the i-th 3D printer, sf i represents the supported resolution of the i-th 3D printer, cg represents the resolution requirement of the task, ts represents the printing speed required by the task, sl represents the number of prints required by the task, and tt represents the printing time required by the task.

8. A remote sharing 3D printer method based on 5G communication according to claim 7, characterized in that: The S53 includes S531 and S532; S531. By analyzing the performance indicators and available materials of 3D printers, conducting a comprehensive analysis of the real-time data and historical data of 3D printers, and using a multi-objective optimization algorithm to deeply evaluate the adaptability of each 3D printer, a task matching model is constructed, and then the obtained matching availability score coefficient kyx, material availability index cky and printer task demand matching degree rwp are input into the task matching model, and the task matching model is used to summarize and calculate, and the comprehensive task matching index ZHP is output to assign appropriate printing tasks to each 3D printer; The comprehensive task matching index ZHP is calculated by the following formula: Wherein, ln represents the logarithmic function.

9. A remote sharing 3D printer method based on 5G communication according to claim 8, characterized in that: S532, by collecting a large number of equipment and material data groups of existing 3D printers, including 3D printers that can be assigned tasks and 3D printers that cannot be assigned tasks, combined with the matching availability score coefficient kyx of each 3D printer and the printing requirements of the sharing platform users, input the task matching model for comprehensive analysis, calculate the comprehensive task matching index ZHP of each 3D printer, and calculate the average value through statistical analysis method to preset the task printing matching threshold B; The obtained task printing matching threshold B and the comprehensive task matching index ZHP are used for task matching evaluation, and the task matching degree of the 3D printer is deeply evaluated. The specific evaluation scheme is as follows; When the comprehensive task matching index ZHP ≥ the task printing matching threshold B, it means that the 3D printer meets the printing requirements and the printing task is assigned; When the comprehensive task matching index ZHP is less than the task printing matching threshold B, it means that the 3D printer does not meet the printing requirements. At this time, an overload signal is generated and transmitted to S4 through the 5G communication network to reallocate the printing task.

10. A remote shared 3D printer system based on 5G communication, comprising a remote shared 3D printer method based on 5G communication according to any one of claims 1 to 9, characterized in that: It includes equipment access module, equipment status collection module, intelligent analysis module, availability evaluation module and task matching module; The device access module establishes a communication connection between the 3D printer and the sharing platform through the API communication interface and registers relevant information. The user registers a personal account through the sharing platform and uploads the 3D model file to be printed through the 5G communication network; The device status acquisition module uses a shared platform to collect device status data groups and operation data groups in real time through a printer task monitoring system and a sensor group installed on a 3D printer, obtains an operation stability data group after preprocessing, and transmits it to a relational database for storage through a 5G communication network; The intelligent analysis module is used to perform summary calculation based on the stable operation data group and the network delay yc to obtain the printer load factor dfz and the printer health factor sjk; The availability evaluation module is used to perform summary calculation based on the printer load coefficient dfz and the printer health coefficient sjk, obtain the matching availability score coefficient kyx, and then perform availability evaluation with the preset device availability score threshold A; The task matching module is used to collect the printing data group in real time when it is preliminarily assessed that the 3D printer can be assigned a task, perform preprocessing to obtain the equipment material data group, perform summary calculation based on the equipment material data group, obtain the material availability index cky and the printer task requirement matching degree rwp, perform comprehensive calculation in combination with the matching availability scoring coefficient kyx, obtain the comprehensive task matching index ZHP, and then perform in-depth evaluation with the preset task printing matching threshold B.

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