Multi-source verification handheld industrial intelligent terminal integrating on-line measurement technology and MES function

Abstract

The invention relates to a multi-source verification handheld industrial intelligent terminal integrating an online measurement technology and an MES function, and belongs to the field of industrial big data. According to the scheme, the measuring part of the handheld industrial intelligent terminal is used for collecting and uploading the quality and inspection time data of the parts in real time, the method steps of production progress tracking and productivity analysis are achieved through the processor, and the specific procedure positions of the specific batch of parts in the production process are determined according to the quality inspection data. In addition, the proportion of the number of the parts subjected to quality inspection in the working procedure to the total machining number can be calculated, and therefore the progress completion percentage of the working procedure is obtained. And the whole production progress can be effectively tracked. According to the scheme, the workpiece quality data uploaded in real time by the measuring part of the handheld industrial intelligent terminal is analyzed, so that accurate and efficient productivity statistics and plan execution condition feedback are realized, the equipment productivity and the shift completion operation condition can be accurately known, and the requirements of higher data management and analysis of the portable terminal can be met.

Description

Technical Field

[0001] The present invention relates to a multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES functions, belonging to the fields of intelligent manufacturing and industrial big data, and is used for real-time production progress tracking, production capacity optimization and quality control in discrete manufacturing industries (such as auto parts, precision machinery). Background Art

[0002] With the continuous development of industrial production, the requirements for quality monitoring and control in the production process are also getting higher and higher. Traditional production quality control requires measuring tools (such as measuring rulers or measuring and control instruments) and then cooperates with a Statistical Process Control (SPC) workstation to monitor the quality process.

[0003] Generally, SPC workstations are large and bulky, and are fixed to the process machine tools together with the measuring tools, making it difficult to carry and move. Therefore, a handheld SPC process controller came into being. The handheld SPC process controller supports the online detection function of parts to be processed and can convert the collected quality inspection data into specific charts that are convenient for operators to observe.

[0004] For industrial production, the production progress tracking and production capacity analysis in the production process are crucial for the formulation and adjustment of the factory production plan. Traditional manufacturing enterprises generally focus on the enterprise resource planning (ERP) management system and the field automation system in terms of informatization construction. However, relying solely on ERP and field automation often cannot cope with the contradiction between production and management. ERP mainly focuses on upper-level resource planning management, can handle things that have happened before, and can also predict and handle events that will happen in the future, but it is powerless for events that are happening now. Traditional production site management only regards it as a black box operation.

[0005] The Manufacturing Execution System (MES) emphasizes the execution of manufacturing plans. It builds a bridge between the planning management layer and the process control layer, just filling the gap between the two. Generally, it is used to track the production progress and / or analyze the production capacity.

[0006] As the link between the enterprise decision-making layer and the basic control layer, MES rationalizes the information flow within the enterprise. MES can accurately schedule, send, track, monitor the production information and process in the workshop, and at the same time can measure and report its real-time performance. It is the basic technical means to achieve workshop production agility.

[0007] However, existing handheld SPC cannot achieve closed-loop management of production progress tracking and production capacity analysis. With the continuous improvement of the requirements for industrial production intelligence and digitization, there is an urgent need for a portable intelligent terminal that integrates high-precision measurement, real-time data analysis, and multi-source verification to meet the higher data management and analysis needs. Summary of the Invention

[0008] The object of the present invention is to provide a multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function to meet the higher data management and analysis needs of portable terminals.

[0009] To achieve the above object, the solution of the present invention includes: A handheld industrial intelligent terminal integrating online measurement technology and MES function of the present invention includes an edge computing module for tracking production progress and a measurement unit for inspecting the parts to be processed in the corresponding processing procedure and obtaining inspection data. The edge computing module executes a computer program to implement a production progress tracking method including the following steps: Collect the inspection data uploaded during the inspection process corresponding to the processing procedure. For a batch of parts to be processed, when determining the current production progress, the condition for a certain procedure to be the current production progress of the batch of parts to be processed is that only some parts of the procedure have corresponding inspection data.

[0010] Further, the inspection data includes the time corresponding to the inspection of each part; For each completed procedure of a batch of parts to be processed, take the last inspection time as the actual completion time of the procedure, and display the planned completion time and actual completion time of each completed procedure on the man-machine interface.

[0011] Further, the condition for the current production progress further includes: all parts of the necessary procedures before this procedure have inspection data.

[0012] Further, the condition for the current production progress further includes: there is no inspection data for the procedures after this procedure.

[0013] Further, the inspection data includes the final inspection data uploaded during the final inspection process; The parts with final inspection data in the current processing procedure are regarded as processed parts. Obtain the processed proportion of the processed parts in the total parts in the current processing procedure according to the number of processed parts, and obtain the processing progress of the corresponding procedure of this batch of parts according to the processed proportion.

[0014] Further, the inspection data further includes the first inspection data uploaded during the first inspection process; Parts with first inspection quality inspection data but no final inspection quality inspection data in the current processing operation are regarded as in - process parts. The processed proportion combined with the number of in - process parts is used to obtain the processing progress of the corresponding process of this batch of parts.

[0015] Further, the number of in - process parts is multiplied by a weight coefficient less than 1, and then the proportion in the total number of parts of the corresponding batch is calculated. Adding this to the processed proportion gives the processing progress of the corresponding process of this batch of parts.

[0016] Further, the final inspection quality inspection data includes the time for quality inspection corresponding to each part; The latest quality inspection time in the final inspection quality inspection data of the current process is used as the time to reach the corresponding production progress and / or the processing progress of the corresponding process.

[0017] Further, both the first inspection quality inspection data and the final inspection quality inspection data include the time for quality inspection corresponding to each part; The start time of the first program and / or the end time of the last program of the corresponding process obtained from the machine tool numerical control system of the corresponding process are also used. The start time of the first program is compared with the time of the first inspection quality inspection. If the gap exceeds the set value, the corresponding first inspection quality inspection data will no longer count the in - process parts. The end time of the last program is compared with the time of the final inspection quality inspection. If the gap exceeds the set value, the corresponding final inspection quality inspection data will no longer count the processed parts.

[0018] Further, the edge computing module is also used to generate an SPC chart of the key quality parameters that can reflect the quality inspection data of the corresponding process of a certain batch of products; Among them, the SPC chart is divided into a first inspection SPC chart that can reflect the key quality parameters of the first inspection quality inspection data of the corresponding process of a certain batch of products and a final inspection SPC chart that can reflect the key quality parameters of the final inspection quality inspection data of the corresponding process; If the latest SPC chart is a first inspection SPC chart, the previous process corresponding to this first inspection SPC chart is used as the production progress of a certain batch of products; If the latest SPC chart is a final inspection SPC chart, the process corresponding to this final inspection SPC chart is used as the production progress of a certain batch of products.

[0019] Further, the handheld industrial intelligent terminal also includes a camera for face recognition of the operator and then performing work reporting operations.

[0020] Further, the handheld industrial intelligent terminal also includes an RFID device for identifying the information code of the product; Among them, the information code is bound with the ID of the product and the quality inspection data of the product; the form of the information code is a bar code and / or a two - dimensional code.

[0021] The beneficial effects of the present invention are: As a pioneering invention, the present invention proposes a handheld industrial intelligent terminal integrating online measurement technology and multi-source verification of MES functions, which is used to automatically track the production progress. The measurement unit in the handheld industrial intelligent terminal can perform quality inspection on the parts to be processed in the corresponding processing procedure and obtain quality inspection data. The edge computing module in the handheld industrial intelligent terminal can implement the production progress tracking method. This method can automatically monitor the actual production progress and timely adjust and schedule the production plan according to the actual production progress. According to the workpiece quality data and measurement time data uploaded in real time according to the quality management requirements, the specific process position of the specific batch of parts in the production process can be determined by the final inspection quality inspection data in the process. In addition, the ratio of the number of parts that have completed quality inspection to the total number of processed parts in this process can be calculated, so as to obtain the progress completion percentage of this process. It can effectively track the entire production progress. Since it can integrate quality inspection data, CNC machine tool signals and operator identity information, multi-modal data fusion can be achieved. It realizes accurate and efficient acquisition of the production plan execution situation and can meet the higher data management and analysis requirements for portable terminals. This innovative solution not only improves the efficiency of manufacturing enterprises in the quality inspection link and overall operation, but also has high flexibility and can be widely applied to different industry scenarios, providing a strong boost for promoting the transformation and upgrading of intelligent manufacturing.

[0022] A multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES functions of the present invention includes an edge computing module for analyzing production capacity and a measurement unit for performing quality inspection on the parts to be processed in the corresponding processing procedure and obtaining quality inspection data. The quality inspection data includes the first inspection quality inspection data uploaded during the first inspection quality inspection process and the final inspection quality inspection data uploaded during the final inspection quality inspection process. The edge computing module executes a computer program to implement a production capacity analysis method including the following: Collect the first inspection quality inspection data and the final inspection quality inspection data corresponding to the processing procedure; Both the first inspection quality inspection data and the final inspection quality inspection data include the time corresponding to the quality inspection of each part; When determining the production capacity, according to the time period for which the production capacity needs to be calculated, obtain the number of processed completed parts whose first inspection time and final inspection time of all processes are within this time period; The number of processed completed parts is used as the production capacity based on the corresponding time period.

[0023] Furthermore, it also includes a preset time interval; The number of parts whose first inspection completion time and final inspection completion time of a certain process are within the preset time interval is used as the production capacity of this process based on the corresponding time interval.

[0024] Further, the edge computing module also uses the start time of the first program and the end time of the last program of the corresponding process obtained from the numerical control system of the machine tool for the corresponding process, and compares them with the first inspection completion time and the last inspection completion time respectively, and eliminates the first inspection completion time and the last inspection completion time whose differences exceed the set threshold.

[0025] Further, the edge computing module is also used to generate a first inspection SPC chart of the key quality parameters that can reflect the first inspection quality inspection data of the corresponding process of a batch of products and a last inspection SPC chart of the key quality parameters of the last inspection quality inspection data of the corresponding process; When the number of data points of the key quality parameters on the first inspection SPC chart and the last inspection SPC chart is the same, the production capacity of the time period between the time corresponding to the data point of the earliest key quality parameter on the first inspection SPC chart and the time corresponding to the data point of the latest key quality parameter on the last inspection SPC chart is the number of data points of the key quality parameters on the first inspection SPC chart or the last inspection SPC chart.

[0026] Further, the handheld industrial intelligent terminal further includes a camera for performing work reporting operations after face recognition of the operator.

[0027] Further, the handheld industrial intelligent terminal further includes an RFID device for identifying the information code of the product; Wherein, the information code is bound with the ID of the product and the quality inspection data of the product; the form of the information code is a bar code and / or a two-dimensional code.

[0028] The beneficial effects of the present invention are as follows: As a pioneering invention, the present invention proposes a multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES functions for automatically calculating production capacity. The measurement unit in the handheld industrial intelligent terminal can perform quality inspection on the parts to be processed in the corresponding processing process and obtain quality inspection data, and the quality inspection data includes the first inspection quality inspection data uploaded during the first inspection quality inspection process and the last inspection quality inspection data uploaded during the last inspection quality inspection process. The edge computing module in the handheld industrial intelligent terminal can implement a method for automatically calculating production capacity (also known as a production capacity analysis method). This method uses the number of workpieces whose first inspection time before the process and last inspection time after the process are both within a preset time period based on the real-time uploaded workpiece quality data to obtain production capacity data based on this time period, realizing accurate and efficient production capacity statistics, and meeting the higher data management and analysis requirements for portable terminals. This innovative solution not only improves the efficiency of manufacturing enterprises in the quality inspection link and overall operation, but also has high flexibility, can be widely applied to different industry scenarios, and provides strong assistance for promoting the transformation and upgrading of intelligent manufacturing. Description of the Drawings

[0029] Figure 1It is a schematic structural diagram of a multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES functions provided by an embodiment of the present invention; Figure 2 It is a schematic flowchart of a production progress tracking method and a production capacity analysis method provided by an embodiment of the present invention; Figure 3 It is an example diagram of the dimensional parameters of parts to be inspected and tested provided by an embodiment of the present invention; Figure 4 It is a schematic diagram of a human-computer interaction interface for production progress tracking of bearing parts provided by an embodiment of the present invention; Figure 5 It is a schematic diagram of an SPC chart of key quality parameters that can reflect the quality inspection data of corresponding processes of a certain batch of products. Detailed implementation manners

[0030] To make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0031] The concept of the present invention lies in: using the quality inspection link after each processing step, collecting the quality inspection data of each processed part and the corresponding data upload time uploaded by the quality inspection equipment connected to the industrial Internet in the quality inspection link, and at the same time using the collected quality inspection big data to realize the statistics of the processing quantity and corresponding time of parts in each process during the quality inspection. It is possible to obtain production progress-related data through the essential quality inspection link without adding extra links or occupying extra manpower, and then analyze the data to achieve production progress tracking and production capacity analysis.

[0032] Moreover, the quality inspection measurement data is rigorous, accurate, and automatically uploaded, without relying on manual additional registration, and it is not easy to have errors or omissions. The production progress obtained based on such data statistics and analysis is more accurate.

[0033] In a certain link during the part processing process, for example, after processes such as cutting, milling slots, drilling, and grinding are completed, it is necessary to perform quality inspection on whether the processing of the corresponding part in this process is up to standard after the processing process or after completion. Workers need to use relevant measuring instruments to measure the key quality parameters (such as dimensions, geometric tolerances, and quality, etc.) of the processed part corresponding to this process, and compare them with the standard parameters or requirements of the processing target to see if there are parts whose processing accuracy and processing target are not achieved and the key quality parameters are unqualified during the processing of this process. For unqualified parts, they cannot enter the next processing step and need to be reworked or scrapped in this process.

[0034] In the prior art, there have emerged digital quality inspection devices for measuring key measurement parameters in quality inspection, namely digital measuring instruments, simply referred to as digital gauges. Digital gauges are used to measure and statistically analyze the key quality parameters (such as dimensions, geometric tolerances, etc., and can also include weighing) of each workpiece, directly display them on the instrument for on-site quality inspectors to judge whether the machining of parts in the current process is qualified, and can convert these data into a communicable format according to the protocol in combination with the corresponding measurement time, and transmit them to a computer or server cloud platform through a network interface for remote quality inspection and data archiving and analysis.

[0035] Specifically, in the mass production of a batch of products, multiple processes are required for processing. According to production and quality requirements, generally, first inspections are required before each process and final inspections are required after each process to ensure processing quality. Through different digital measuring instruments, the quality parameters, measurement quantities, and measurement times of the first inspections and final inspections of each process are uploaded in real time, and quality inspections, data statistical calculations, and analyses are completed on-site, at the edge, or in the cloud, and the quality inspection results are returned.

[0036] An embodiment of a multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function: Embodiment 1: Figure 1 It is a schematic structural diagram of a multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function provided by an embodiment of the present invention, as Figure 1 shown. The multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function mainly includes a measurement module and an edge computing module communicatively connected to the measurement module.

[0037] Among them, the measurement module is used to perform quality inspection on the parts to be processed in the corresponding processing process and obtain quality inspection data (that is, to realize online measurement technology); the edge computing module is used to track the production progress and / or analyze the production capacity (that is, to realize the MES function).

[0038] Among them, the measurement module is also called the measurement unit, which can be a digital measuring instrument, or a high-precision sensor array, etc. Of course, it can also be a precision electronic weighing instrument, and the present invention does not make special limitations on this.

[0039] The digital gauge is a measuring instrument with communication function for measuring parameters and indicators such as dimensions and tolerances, including but not limited to calipers, micrometers, ten-thousandth meters, comparators, pneumatic gauges, coordinate measuring machines, etc. with communication interfaces (including software interfaces and hardware interfaces). The present invention does not limit the digital gauge, and any measuring instrument with communication function can be used.

[0040] For example, the authorized announcement text of the Chinese utility model patent with the authorization announcement number CN201387383Y discloses a digital display inspection template for locomotives and vehicles. This inspection template uses digital measuring instruments, providing a fast, accurate, and reliable inspection method for improving the inspection reliability, stability, and traceability of locomotive and vehicle parts. As described in the specific implementation manner and Figure 1 , 2 the disclosed solution in this patent, this inspection template can transmit data to the host computer through relevant protocols and analyze and process the data using database management software.

[0041] In addition, the authorized announcement text of the Chinese utility model patent with the authorization announcement number CN207730234U discloses a digital measuring instrument, which includes a data processor, a data communicator, and an output trigger device. The data processor is respectively connected to the data communicator and the output trigger device, and can output the measurement result obtained through the data communicator to an external device when the output trigger device receives an external trigger. In the technical solution disclosed in this patent application, after the digital measuring instrument measures the corresponding result, the data processor can output the measurement result obtained through the data communicator to an external device when the external trigger activates the output trigger device, thereby automatically outputting the measurement result obtained by the digital measuring instrument to an external device, that is, a third-party device or system, facilitating the acquisition of the measurement result obtained by the digital measuring instrument by the third-party device or system.

[0042] When it is a high-precision sensor array, the high-precision sensor array includes at least a communication interface and one of a laser ranging module, a machine vision module, and a displacement sensor. When the high-precision sensor array is a laser ranging module, the accuracy requirement for the laser ranging module is ±0.5μm; when the high-precision sensor array is a machine vision module, the resolution of the machine vision module is 1280×1024; when the high-precision sensor array is a displacement sensor, the resolution of the displacement sensor ≤0.001 millimeters (mm).

[0043] As a specific implementation manner, as Figure 1 shown, the handheld industrial intelligent terminal in this embodiment also has a multi-channel expansion function for on-line measurement, supporting external connection of other types of measurement devices through communication interfaces such as RS232 or RS485 and obtaining the measurement data of other measurement devices (including the workpiece quality data detected by the externally connected sensors), such as the measurement data collected by a measuring ruler, a measuring table, a measuring instrument, or other sensors, etc., to realize the expansion of the quality inspection measurement function.

[0044] The measurement data of the built-in measurement module of the handheld industrial intelligent terminal and other external measurement devices are transmitted to the edge computing module for further calculation of MES functions. As an alternative implementation, other external measurement devices can transmit the quality parameters and measurement time of each workpiece to the edge computing module through wireless communication methods such as WIFI or Bluetooth.

[0045] Online measurement has a data archiving function, which is convenient for users to view historical data; the data archiving can store up to 100,000 records at most.

[0046] For the edge computing module, the edge computing module can only implement the function of production progress tracking, or can only implement the function of production capacity analysis, or can implement both functions, etc. The present invention does not make special limitations on this. Subsequently, taking the edge computing module implementing both functions as an example, an exemplary description will be given.

[0047] Furthermore, the edge computing module may further include a multi-source data verification module and a human-computer interaction module that facilitates the statistics and analysis of products.

[0048] It should be noted that when the edge computing module can only implement the function of production progress tracking, the edge computing module can also be called a production progress tracking module; when the edge computing module can only implement the function of production capacity analysis, the edge computing module can also be called a production capacity analysis module.

[0049] In order to improve the machining accuracy, as an alternative implementation, the multi-source verification handheld industrial intelligent terminal provided by the embodiments of the present invention integrating online measurement technology and MES functions further includes an alarm module. The alarm module is used to alarm when the difference between the size of the part to be machined and the set size is greater than the preset error, so as to remind the operator to pay attention to the machining effect. The operator can manually adjust the parameters of the machining equipment to make the machining equipment process the part to be machined at a lower speed, so that the size of the part to be machined gradually becomes consistent with the set size, so as to reduce the occurrence of over-machining.

[0050] Among them, the parameters of the machining equipment include the spindle speed of the machining equipment and the tool feed speed of the machining equipment, etc. The present invention does not make special limitations on this.

[0051] It can be understood that due to the accuracy problem of the machining equipment, there may be an error between the size of the part to be machined and the set size, resulting in the inequality between the size of the part to be machined and the set size. Therefore, it is necessary to stipulate the error. In the embodiments of the present application, taking the error as 0.0001 millimeters (mm) as an example, an exemplary description will be given.

[0052] To save labor and improve intelligence, as an alternative implementation, when the difference between the size of the part to be processed and the set size is greater than the preset error, the edge computing module can automatically adjust the parameters of the processing equipment.

[0053] To make the obtained quality inspection data more accurate, as an alternative implementation, the multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function provided by the embodiments of the present invention further includes a temperature sensor. The temperature sensor is communicatively connected to the measurement module, and the temperature sensor uploads the collected temperature quality data to the measurement module through the sensor interface of the measurement module. The temperature sensor is used to respond to environmental changes and automatically compensate for the temperature difference between the standard part and the part to be processed.

[0054] Among them, the temperature sensor can be selected according to the actual production requirements for temperature detection. The present invention does not make special limitations on the temperature detection requirements during production. In this embodiment, the temperature range to be detected is [-20°C, 50°C] as an example for illustrative purposes.

[0055] To obtain operator information, as an alternative implementation, the multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function provided by the embodiments of the present invention further includes a camera (not shown). The camera is used to perform a work reporting operation after face recognition of the operator.

[0056] As another alternative implementation, the multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function provided by the embodiments of the present invention further includes a Radio Frequency Identification (RFID) device (not shown); the RFID device is used to identify the information code of the product.

[0057] The part to be processed that has completed all processing procedures is called a product. By using the RFID device to identify the information code of the product, the function of tracing the quality of the product can be realized.

[0058] Among them, the information code is bound with the ID of the product and the quality inspection data of the product; the form of the information code can be a barcode, a two-dimensional code, or a combination of a barcode and a two-dimensional code, etc. The present invention does not make special limitations on this.

[0059] To ensure the validity of the quality inspection data, as an alternative implementation, the multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function provided by the embodiments of the present invention further includes a Figure 1 communication module as shown; the communication module is used to interact with the numerical control machine tool to obtain the machine tool operation data.

[0060] Among them, the communication module adopts a multi-source heterogeneous communication mode and integrates communication interfaces such as serial ports, network ports, Bluetooth, Zigbee, and WiFi.

[0061] To prevent data loss, as an optional implementation, the multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES functions provided by the embodiments of the present invention can upload relevant production capacity data and progress tracking data to the cloud MES system through the communication link layer, and the cloud MES system stores and displays them.

[0062] Among them, the communication link layer can be 5G or a network, etc., and the present invention does not make special limitations on this.

[0063] Among them, the multi-source verification module in the edge computing module is used to verify the consistency between the first and last inspection times and the start and stop times of the processing program, and eliminate the data with a difference exceeding the set threshold, so as to improve the reliability of the data.

[0064] Among them, the set threshold can be ±5% or other values, etc., and the present invention does not make special limitations on this. In the following embodiments, the set threshold is taken as ±5% as an example for illustrative description.

[0065] Exemplarily, in a bearing processing workshop, an operator uses the terminal to scan the part QR code to start the inspection. The measurement module collects parameters such as the outer diameter and aperture, and records the last inspection time as 14:30. The multi-source verification module verifies that the deviation between this time and the end time (14:28) of the tool withdrawal program of the numerical control machine tool is within 2%, and determines that the data is valid.

[0066] Exemplarily, in a bearing processing workshop, an operator uses the terminal to scan the part QR code to start the inspection. The measurement module collects parameters such as the outer diameter and aperture, and records the first inspection time as 09:00. The multi-source verification module verifies that the deviation between this time and the start time (08:50) of the preheating program of the numerical control machine tool exceeds 5%, automatically marks it as abnormal data, eliminates the data, or conducts manual review again.

[0067] Among them, the human-computer interaction module in the edge computing module is used to generate a statistical process control (SPC) chart of key quality parameters that can reflect the quality inspection data of the corresponding process of a certain batch of products, and display it on the screen in real time to facilitate the statistics and analysis of products.

[0068] As an optional implementation, the generated SPC chart can also be uploaded to the cloud MES through the communication link layer for storage.

[0069] Among them, SPC collects the data in the production process and presents it in the form of a chart. In this embodiment, by collecting the quality inspection data uploaded by the measurement module and calculating statistical indicators such as the mean and standard deviation of the quality inspection data, a line chart and so on can be generated. Subsequently, taking the line chart as an example, an exemplary description will be given.

[0070] Among them, the SPC chart includes four key elements: data points, the mean line CL, the upper control limit UCL, and the lower control limit LCL. Through these four key elements, the health status of the production process can be reflected.

[0071] Among them, the data points (i.e., the measured values) can represent the actual measurement results in the production process, such as the size, weight, or other key characteristics of the product. They are obtained through real-time data collection and displayed on the control chart.

[0072] Among them, the mean line represents the target value or average level of the production process. It is calculated through historical data and reflects the average performance of the production process.

[0073] Among them, these control limits, the upper control limit UCL and the lower control limit LCL, represent the allowable fluctuation range in the production process and are calculated based on the mean μ and the standard deviation σ. Usually, the upper control limit is μ + 3σ, and the lower control limit is μ - 3σ.

[0074] When the data point exceeds the upper control limit, it indicates that there may be abnormal fluctuations in the process, and immediate action needs to be taken for correction. When the data point exceeds the lower control limit, it also indicates that there are problems in the process, which may affect the product quality.

[0075] Among them, among the data points, there may be out-of-limit points. An out-of-limit point refers to a data point that exceeds the upper control limit or the lower control limit. When an out-of-limit point appears, it indicates that there are abnormal fluctuations in the production process, and these fluctuations may be caused by factors such as process changes, equipment failures, and material problems.

[0076] Furthermore, the SPC chart can be used for production progress tracking and / or production capacity analysis.

[0077] When using the SPC chart for production progress tracking, only one SPC chart is needed. This SPC chart can be the first-inspection SPC chart that reflects the key quality parameters of the first-inspection quality inspection data of the corresponding process of a certain batch of products, or the last-inspection SPC chart that reflects the key quality parameters of the last-inspection quality inspection data of the corresponding process of a certain batch of products.

[0078] Exemplarily, if the latest SPC chart is the first-inspection SPC chart, the previous process of the process corresponding to the first-inspection SPC chart is taken as the production progress of a certain batch of products; if the latest SPC chart is the final-inspection SPC chart, the process corresponding to the final-inspection SPC chart is taken as the production progress of a certain batch of products.

[0079] When conducting capacity analysis using SPC tables, two SPC charts are required. One SPC chart is the first-inspection SPC chart that reflects the key quality parameters of the first-inspection quality inspection data of the process corresponding to a certain batch of products, and the other SPC chart is the final-inspection SPC chart that reflects the key quality parameters of the final-inspection quality inspection data of the process corresponding to a certain batch of products.

[0080] Exemplarily, when the number of data points of the key quality parameters on the first-inspection SPC chart and the final-inspection SPC chart is the same, the production capacity during the time period between the time corresponding to the earliest data point of the key quality parameters on the first-inspection SPC chart and the time corresponding to the latest data point of the key quality parameters on the final-inspection SPC chart is the number of data points of the key quality parameters on the first-inspection SPC chart or the final-inspection SPC chart.

[0081] Furthermore, on the SPC chart during the time period when capacity analysis is required, if out-of-control points appear, when the number of data points of the key quality parameters on the first-inspection SPC chart and the final-inspection SPC chart is the same, the production capacity during the time period between the time corresponding to the earliest data point of the key quality parameters on the first-inspection SPC chart and the time corresponding to the latest data point of the key quality parameters on the final-inspection SPC chart is the difference obtained by subtracting the number of out-of-control points from the number of data points of the key quality parameters on the first-inspection SPC chart or the final-inspection SPC chart. The production capacity calculated using this method will be more accurate and more in line with actual production.

[0082] When conducting capacity analysis, the SPC chart can help production managers deeply understand the stability and efficiency of the production process and take appropriate measures to improve production capacity.

[0083] The specific help is as follows: Help 1. Monitor process stability.

[0084] The SPC chart can monitor the stability of the production process in real time. If most of the data points in the production process are between the upper control limit UCL and the lower control limit LCL and do not exceed the control limits, this indicates that the production process is stable and the process variation is small.

[0085] Help 2. Identify abnormal fluctuations.

[0086] When there are out-of-control points, the SPC chart can promptly indicate these abnormal fluctuations. These abnormal fluctuations may indicate problems in certain links of the production process, such as equipment failures, operation errors, raw material problems, etc. Identifying and handling these abnormalities in a timely manner can avoid production capacity waste and quality issues.

[0087] Help Three: Improve production efficiency.

[0088] By analyzing the trend lines and out-of-control points on the SPC chart, production managers can identify the reasons for process changes or improper operations, and adjust process parameters to reduce fluctuations, thereby improving production efficiency.

[0089] Among them, the trend line is a line formed by connecting data points.

[0090] Exemplarily, in the SPC chart, when there are 5 consecutive out-of-control points, it may mean that process optimization is required for a certain link (such as spindle load, feed rate, etc.), thereby improving production efficiency and reducing the scrap rate.

[0091] Help Four: Precise production capacity prediction and optimization.

[0092] If the SPC chart shows continuous fluctuations (such as frequent out-of-control points), production managers can reduce fluctuations by adjusting the process or optimizing the equipment, making the production process more precise, and thus enhancing production capacity.

[0093] Exemplarily, after process optimization, the production line may be able to operate more stably and reach the expected production capacity level (such as 1200 pieces / shift).

[0094] Help Five: Data-driven decision support.

[0095] The SPC chart provides quantified production capacity analysis data to help production decision-makers make more scientific decisions. Through these data, production line managers can accurately judge whether adjustments are needed to the production process, optimize production equipment, or improve process control, avoiding unnecessary downtime or resource waste.

[0096] Help Six: Early warning and prevention.

[0097] The SPC chart can not only detect existing problems but also warn of potential quality problems or production bottlenecks. If the trend line starts to deviate from the normal fluctuation range, or the SPC chart shows a repeated fluctuation pattern, then managers can take preventive measures in advance to prevent the occurrence of production capacity bottlenecks.

[0098] The main role of the SPC chart in production capacity analysis is to ensure the stability of the production process and quality control. By monitoring production data in real time, it helps to detect and eliminate fluctuations, avoiding unnecessary downtime, equipment failures, or quality issues. By promptly identifying anomalies and optimizing processes and equipment, the SPC chart can directly improve production efficiency and capacity, reduce costs, and enhance product quality. By setting process parameter optimization suggestions in the SPC chart (such as triggering optimization when 5 consecutive points exceed the limit), it can make a rapid response based on real-time data, ensure the high efficiency and stability of the production process, and maximize production capacity.

[0099] Regarding the size and type of the screen, the present invention does not make any special limitations. In this embodiment, a 4-inch TFT color touch screen is taken as an example for illustrative purposes.

[0100] For the convenience of carrying, the multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function provided by the embodiments of the present invention is built-in with a rechargeable lithium battery and supports long-term continuous use.

[0101] To meet the different needs of users, as an optional implementation manner, the multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function provided by the embodiments of the present invention supports an external power supply working mode.

[0102] Among them, the external power supply can provide a voltage of 5 volts DC for the multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function.

[0103] To improve user satisfaction, as an optional implementation manner, the multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function provided by the embodiments of the present invention supports operators to set different parameters according to needs during quality inspection.

[0104] For example, it can be the upper and lower limits of standard parts. Exemplarily, if the height of the standard part is 52 millimeters (mm), and the upper limit of the height of the standard part is set to 0 mm and the lower limit is 0.1 mm, it means that the height of the part to be processed after completing the relevant process is considered qualified within the range of [51.9 mm, 52 mm] and the next process can be carried out. If this process is the last process, it means that the part has completed all processing processes.

[0105] Another example can be the alarm threshold of the alarm module (i.e., the preset error).

[0106] The protection level of the multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function provided by the embodiments of the present invention is IP67. In actual applications, the protection level can be higher or lower, and the present invention does not make any special limitations.

[0107] Among them, the protection level of IP67 represents a specific protection safety level. IP is the abbreviation of Ingress Protection Rating (or International Protection code), which defines the protection ability of an interface against liquid and solid particles. Specifically, the two digits in IP67 represent the solid protection level and the liquid protection level respectively. The first digit "6" represents the solid protection level, indicating complete prevention of foreign objects and dust intrusion. This means that the relevant equipment can effectively block the entry of tiny solid particles such as dust when it is completely sealed, thus protecting the internal precision components from damage; the second digit "7" represents the liquid protection level, indicating that the equipment can prevent the intrusion of water and cause harmful effects when immersed in water at a depth of 1 meter for a short time (usually 30 minutes). This enables the equipment to operate normally in daily life scenarios such as handwashing and rain, without being damaged due to short-term immersion in water.

[0108] In summary, the IP67 protection level provides high-level dust and water protection for the equipment, enabling it to maintain stable performance and reliability in various complex environments.

[0109] Specifically, in combination with Figures 2 to 4 the process of the edge computing module tracking the production progress and analyzing the production capacity will be described in detail.

[0110] Figure 2 is a schematic flowchart of a production progress tracking method and a production capacity analysis method provided by an embodiment of the present invention. As Figure 2 shown, it includes the following steps: In the first inspection and the last inspection of each process in the production of a batch of parts, use a measurement module (i.e., a digital measuring instrument or a high-precision sensor array) or other external measuring devices to obtain the quality inspection data of each part. That is, the quality inspection data includes the first inspection quality inspection data uploaded during the first inspection process and the last inspection quality inspection data uploaded during the last inspection process; transmit the quality inspection data to the edge computing module, complete the quality inspection through the edge computing module and return the quality inspection result, and then associate the quality inspection data, the quality inspection time (which can be obtained by the measurement module during quality inspection and transmitted together with the quality inspection data, or the time when the edge computing module receives the corresponding quality inspection data can be used as the quality inspection time for storage) with the part number to form the processing data of the corresponding process and store it locally, and further can be stored in the cloud as industrial big data for obtaining subsequent production data, such as production progress tracking and production capacity analysis. By using edge computing, the processing speed and accuracy can be optimized and improved.

[0111] As a specific implementation manner, the processing data of a certain process can be stored in the cloud database in the form shown in the following table: The above table can analyze data such as the processing progress of parts in a process.

[0112] Among them, the quality inspection data 1, 2... can be different key quality parameters after the corresponding process of a part is processed. The quality inspection time can be the time when the last item of quality inspection data for the part is completed. It can also be several key quality parameters for the first inspection and the corresponding several key quality parameters for the last inspection respectively. If it is divided into the first inspection and the last inspection, at least the quality inspection time (first inspection time) for the first inspection and the quality inspection time (last inspection time) for the last inspection should be stored separately.

[0113] Of course, as a more refined statistical result, when conditions permit, the detection time or upload time of each item of quality inspection data can be separately counted.

[0114] The corresponding quality inspection data and quality inspection time for the unfinished processes of the corresponding parts can be empty.

[0115] The following combines Figure 3 Taking a specific example, the process of using the measurement module to collect processing data in this embodiment is described.

[0116] Figure 3 It is an example diagram of the size parameters of a part to be quality inspected provided by an embodiment of the present invention. As Figure 3 shown, the figure shows a cross-sectional view of the part to be quality inspected. A certain processing process is to turn its first outer diameter B to Ф12mm, the second outer diameter C to Ф10mm, and the height A to 52mm. After the processing of this process is completed, the quality inspector uses a digital micrometer to conduct a final inspection on the parts processed in this process, and measures the sizes of the first outer diameter B, the second outer diameter C, and the height A in sequence. After stable data is obtained for each size measurement, the corresponding size data is uploaded by operating the digital micrometer, and the following table is obtained. The measurement time can be the time recorded by the digital micrometer and uploaded together with the measurement data, or the receiving time when the receiving party receives the corresponding size data uploaded by the digital micrometer.

[0117] Among them, the 3 measurement times for each part, because they are all obtained when the part is taken offline for quality inspection after the processing of the corresponding process is completed, can all be used as the quality inspection time (last inspection time) for the final inspection after the part completes the processing of the corresponding process. During the processing of a batch of parts, when the processing data of this batch of parts in the current process is obtained by a digital measuring instrument and stored in the cloud, these data can be used for production progress tracking and production capacity analysis.

[0118] From the processing data, the quality inspection time data concerned by the method of this embodiment can be further extracted. The statistical results of the quality inspection time for the entire process flow of parts processing and all parts are shown in the following table: For each part in each process of the entire production process flow, the quality inspection time can be filled with null if there is no corresponding data. Among them, the quality inspection time includes the final inspection time; further, the quality inspection time can also include the first inspection time, that is, the quality inspection time includes both the final inspection time and the first inspection time.

[0119] For production progress tracking, specifically, the measurement module first conducts quality inspection on the parts to be processed after the processing operation is completed, and transmits the recorded quality inspection data to the edge computing module. Then, the edge computing module collects the quality inspection data uploaded during the quality inspection process corresponding to the processing operation; for a batch of parts to be processed, if only some parts in a certain operation have quality inspection data, then this operation represents the current production progress of this batch of parts to be processed. The last (i.e., the latest) quality inspection time in the quality inspection data is the time when this production progress is achieved.

[0120] Among them, the quality inspection data can be the first inspection quality inspection data uploaded during the first inspection process, or the final inspection quality inspection data uploaded during the final inspection process.

[0121] At the same time, for each completed operation of the parts to be processed in the corresponding batch, the last (the latest) quality inspection time (if there is final inspection quality inspection data, it is the final inspection quality inspection time) is the actual completion time of this operation. Listing the planned completion time and the actual completion time of each completed operation can be used for the adjustment and management of the production plan.

[0122] Figure 4 is a schematic diagram of a human-computer interaction interface for production progress tracking of a bearing part provided by an embodiment of the present invention, as Figure 4 shown. In the figure, "rough turning, finish turning, drilling, rough grinding", etc. listed in the process route tracking row are different processing operations. The planned completion time of each operation in the production plan is listed above, and the actual completion time of the corresponding operation obtained by tracking through the method of this embodiment is listed below. During the production process, according to the deviation between the planned completion time and the actual completion time, the production plan can be adjusted adaptively in real time, and the production plan management can be carried out scientifically, reasonably and based on evidence in a timely manner.

[0123] To ensure the accuracy of progress tracking, as another implementation method, for a batch of parts to be processed, if only some parts in a certain operation have quality inspection data and there is no quality inspection data for the operations after this operation, then this operation represents the current production progress of this batch of parts to be processed.

[0124] Alternatively, for a batch of parts to be processed, if only some parts of a certain process have quality inspection data, and all parts of the necessary processes before this process have quality inspection data, then this process is the current production progress of the batch of parts to be processed.

[0125] Or, for a batch of parts to be processed, if only some parts of a certain process have quality inspection data, and all parts of the necessary processes before this process have quality inspection data, and there is no quality inspection data for the processes after this process, then this process is the current production progress of the batch of parts to be processed.

[0126] As another implementation manner, it is also possible to further obtain the number of parts that have completed the processing of the corresponding process among the parts of this batch according to how many parts have final inspection quality inspection data for the corresponding process. By comparing the number of completed parts with the total number of parts to be processed in this batch, the proportion of the parts that have completed the processing of the current process among the total parts of this batch is obtained. This proportion is the processing completion progress of the current process of this batch. The last (latest) quality inspection time in the final inspection quality inspection data is the actual completion time when reaching this completion progress.

[0127] Specifically, a completion progress table for each batch can be formed for a certain process as shown in the following table: In the table, the planned quantity is the quantity of parts to be processed in the corresponding batch, the completed quantity is the quantity of parts that have completed the processing of the corresponding batch in this process statistically obtained by using the method of the present invention according to how many parts have final inspection quality inspection data. The completion ratio is obtained by comparing the completed quantity with the planned quantity, and the last (latest) quality inspection time of the corresponding batch for this process is used as the completion time when reaching the corresponding completion ratio.

[0128] Furthermore, it is also possible to combine the position of the current process of the parts in this batch among all the processes from the parts processing to the finished product to obtain the completion progress of the parts in this batch during the entire processing process. That is, by combining the necessary processes (completed processes) before the current process and the uncompleted processes after the current process, the current production progress of the parts in this batch before becoming finished products is calculated.

[0129] Furthermore, among the parts in this batch in the processing data of the current process, parts that have first inspection data but no final inspection data can be considered as parts being processed in the current process. By combining the number of parts that have been processed in the current process and the number of parts being processed, the completion progress of the current process for this batch can be obtained, making the progress statistics more detailed and accurate. Specifically, multiplying the number of parts being processed by a weight coefficient less than 1 and then calculating the proportion in the total number of parts in this batch, and adding the proportion of the parts that have completed the processing in the current process in the total number of parts in this batch, the completion progress of the current process for the parts in this batch considering the parts being processed can be obtained. For the production capacity analysis of the processing of a batch of parts, according to the time period for which the production capacity needs to be calculated (such as one day, one week, or one month), obtaining the number of parts whose first inspection time and final inspection time for all processes are within this time period can be regarded as the production capacity of this batch of parts based on this time period.

[0130] As another alternative implementation, multiplying the number of parts being processed by a weight coefficient less than 1 and then adding the number of parts that have been processed to obtain the production volume of the current process; dividing the production volume of the current process by the total planned number of parts to be produced and then multiplying by 100% to obtain the completion progress of the current process.

[0131] For example, if the number of parts being processed is 80, the number of parts that have been processed is 1100, the weight coefficient is 0.4, and the total planned number of parts to be produced is 1200, then the completion progress of the current process = (0.4 * 80 + 1100) ÷ 1200 * 100% = 94.3%.

[0132] Among them, the setting of the weight coefficient is related to the preparation time of the CNC machine tool, and the general value range is [0.3, 0.5].

[0133] Since the preparation time of the CNC machine tool is taken into account, therefore, the production capacity analysis with the addition of the weight coefficient can solve the problem of missing statistics of work-in-progress in the traditional method.

[0134] As an alternative implementation, after obtaining the completion progress of the current process, it can be compared with the planned progress. When it is less than the planned progress, the alarm system can be triggered to give an alarm, and the management personnel can add equipment for inspection to improve the completion progress.

[0135] For the production capacity analysis of the processing of parts in a process, the production capacity of the processing of parts in this process can be based on the average processing time of a single part in this process itself, or the average processing time of a single part multiplied by the corresponding time interval.

[0136] For the average processing time of a single part in a certain process, it can be obtained by taking the average of the time intervals between the first inspection time and the final inspection time of each part in this process.

[0137] As other embodiments, the processing time of a part for a corresponding process can also be obtained by means of big data statistics. For a time interval, the number of parts whose first inspection time and last inspection time of the process are within this time interval is divided by the duration of this time interval to obtain the average processing time of a single part.

[0138] After obtaining the part processing capacities of each process, considering whether each process can be parallel, the requirement that a certain process needs to be a prior process of another process, and the average processing time of a single part of each process, a reasonable parallelism is configured within a certain time interval, so as to obtain the production capacity of a batch of parts processing for the corresponding time interval.

[0139] Cloud processing and report generation: According to the above method, with the help of the cloud system production capacity analysis data processing engine, the data stream of the processing data including production capacity data and progress tracking data uploaded by the intelligent terminal of the present invention is dynamically analyzed, and the production team output capacity index is continuously updated within the current cycle and an efficiency report is output. At the same time, according to the progress tracking data, the actual completion total is compared and verified with the preset production plan. Once a deviation is found, the deviation is immediately identified, the trend is predicted and the strategy is adjusted to improve the overall production efficiency.

[0140] In order to facilitate the statistics and analysis of the product processing quality, the edge computing module can use the quality inspection data uploaded by the measurement module to generate an SPC chart of the key quality parameters reflecting the quality inspection data of the corresponding process of a certain batch of products.

[0141] The following combines Figure 5 , and introduces a method for analyzing the corresponding production capacity situation based on the SPC chart of the key quality parameters of the quality inspection data of the corresponding process of a certain batch of products.

[0142] Figure 5 is a schematic diagram of an SPC chart of the key quality parameters reflecting the quality inspection data of the corresponding process of a certain batch of products provided by an embodiment of the present invention. As Figure 5 shown, the horizontal axis represents the detection time, the vertical axis is the dimension, and the unit of the vertical axis is millimeter (mm).

[0143] In Figure 5 : There are two red lines. One is the upper limit line UCL, which is between 50.10 mm and 50.15 mm, and the other is the lower limit line LCL, which is between 49.90 mm and 49.95 mm. There is one black line, which represents the average line CL and is used to represent the trend of the key quality parameter detection values. A dot represents the data point of the key quality parameter of a part. The blue data points represent qualified data points, and the red data points represent out-of-limit points. The blue lines are used to connect the data points to obtain a blue broken line, and the blue broken line represents the change trend of the data points.

[0144] Take this SPC chart as an example of the final inspection SPC table of the fine milling process to calculate the production capacity under the fine milling process. In this SPC chart, each data point reflects the key quality parameters of the part.

[0145] When calculating the fine milling process, in the final inspection SPC chart, the latest data point of the key quality parameter corresponds to 15:50, and in the first inspection SPC chart ( Figure 5 Similarly, (not shown), the earliest data point of the key quality parameter in the first inspection SPC chart corresponds to an earlier time than the earliest data point of the key quality parameter in the final inspection SPC chart). The earliest data point of the key quality parameter corresponds to 7:00 (not shown). Since the number of data points of the key quality parameters in the final inspection SPC chart is equal to the number of data points of the key quality parameters in the first inspection SPC chart, both are 48, the initial estimated capacity is 48 within the 8 hours and 50 minutes from 7:00 to 15:50. That is, a total of 48 parts are inspected during the first inspection before the process. When the number of data points of the key quality parameters in the SPC chart corresponding to the final inspection is also updated to 48, it means that the 48 parts that have passed the first inspection have completed the processing of the corresponding process, and have been removed from the machine tool clamp and completed the final inspection.

[0146] Since there are 3 out-of-limit points (i.e. 3 red points) in the final inspection SPC chart, indicating that 3 parts are not qualified and cannot be included in the production capacity, the more accurate production capacity within 8 hours and 50 minutes from 7:00 to 15:50 is 45. As an optional implementation, SPC can automatically update the data every hour. If a preset number of consecutive data are not qualified data, the process parameter optimization suggestion is triggered.

[0147] The preset number is an integer greater than zero, and this embodiment is exemplified by taking the preset number of 5 as an example.

[0148] Embodiment 2: Based on method embodiment 1, this embodiment further utilizes the control data of the parts processing equipment in each process, such as the CNC system data of the CNC machine tool that can reflect the machine tool processing action, and verifies it with the quality inspection data to further improve the accuracy of the production data acquisition method.

[0149] Specifically, an edge acquisition gateway is configured for the CNC machine tool to enable the access of the data of the machine tool numerical control system to the industrial Internet. An edge acquisition gateway connected to the machine tool numerical control system is deployed, which is responsible for collecting the start and end signals of multiple programs in this processing operation, thereby determining each processing cycle. Similarly, the start processing time and processing completion time of a part in this operation can be obtained, and the actual completed quantity of parts processed within a period of time can also be counted. According to the product processing technology, it is known that the machine tool in this operation needs to execute programs for several specific actions. The edge acquisition gateway monitors the running status of each program throughout the process, collects its start and end signals as well as relevant time data, and uploads this information to the intelligent terminal of the present invention through the industrial Internet. The edge computing module of the intelligent terminal calculates and judges the actual completed quantity of parts. At the same time, it can also compare with the preset standard to detect whether the operation has been changed or identify the phenomenon of idling, so as to accurately evaluate the real production situation.

[0150] The intelligent terminal of the present invention can also be equipped with a mainstream industrial protocol data acquisition module to directly collect the data of the machine tool numerical control system, or the processing data collected by the machine tool edge gateway and the quality data information collected by the handheld terminal can be uploaded to the cloud system, and the analysis results will be fed back to the handheld terminal for display after being verified and compared by cloud computing data.

[0151] Exemplarily, among all the data uploaded on the same day, when the first abnormal data is found, it is determined to be in the idling state, and at this time, the system will eliminate it.

[0152] Among them, the first abnormal data refers to the data in which the actual load of the main shaft of the CNC machine tool is less than the preset load and lasts for a period of time.

[0153] Among them, for the preset load, the present invention does not make any special limitations. In the following embodiments, the preset load is taken as 30% of the rated value of the main shaft load for exemplary illustration; for the duration, the present invention does not make any special limitations. In the following embodiments, the duration is taken as 10 seconds for exemplary illustration, that is, when the actual load of the main shaft < 30% of the rated value of the main shaft load and lasts for 10 seconds, this data is the first abnormal data.

[0154] Exemplarily, among the data uploaded on the same day, there are 3 pieces of data in which the actual load of the main shaft < 30% of the rated value of the main shaft load and lasts for 10 seconds, then it is determined to be in the idling state.

[0155] When the first abnormal data appears, it indicates that the production capacity is underestimated. Further, as an optional implementation manner, the production capacity can be increased according to the number of the first abnormal data.

[0156] Furthermore, the number of the increased production capacity is consistent with the number of the first abnormal data, so as to make the calculation of the production capacity more accurate.

[0157] Exemplarily, among the data uploaded on the same day, 3 are the first abnormal data and 15 are the last inspection time data. According to the 15 last inspection time data, it can be known that the production capacity on the same day is 15. Also, because there are 3 pieces of the first abnormal data, it indicates that the actual production capacity on the same day is more than 15. The 3 pieces of the first abnormal data indicate that the CNC machine tool has run idle 3 times. Therefore, the production capacity should be increased by 3 more. Then, the actual production capacity on the same day should be 18.

[0158] Specifically, the start signal can be the program of the first specific action of the machine tool. For example, when the workpiece chuck hydraulic system of the machine tool acts to clamp the workpiece, the execution of the program of the action of the chuck hydraulic system can be used as the start signal. Or when the oil pressure of the chuck hydraulic system is greater than the set value, it can also be used as the start signal for the machine tool to start processing the corresponding part; the execution of the program of the machine tool retracting the tool and the chuck hydraulic system releasing the workpiece can be considered as the end signal for the corresponding part to end the current process machining.

[0159] It should be noted here that only using the CNC data of the machine tool for the corresponding process to obtain the processing start time and end time of a part for production progress tracking or production capacity analysis, the accuracy of the result is difficult to guarantee. This is because there are situations such as self-checking and trial running during the operation and processing of the machine tool, or during the processing interval, the operator manually operates the machine tool to execute a specific program to move the relevant components of the machine tool in order to clean the machine tool; these situations will all lead to the acquisition of the program of the specific action of the machine tool, and thus may misjudge the start or end of part processing.

[0160] If there is no corresponding CNC data for the machine tool, it can be determined that the processing of the parts related to the corresponding process has not been carried out, providing a basis for using the machine tool data to clean invalid quality inspection data.

[0161] Therefore, as other implementation manners, the quality inspection data of the parts in each process can also be adopted, and further use the CNC data of the machine tool as verification, so as to identify the quality inspection data without corresponding CNC data of the machine tool, filter out these false data and pseudo data generated for various reasons, and further improve the accuracy of progress tracking and production capacity analysis.

[0162] The methods related to the networking of CNC machine tools, the methods for collecting CNC system data, and the corresponding edge collection gateways (industrial gateways) and data collection systems for the networking of machine tool CNC systems belong to the prior art. For details, reference can be made to the published text of the Chinese invention patent application with the application publication number CN114598572A and the published text of the Chinese invention patent application with the publication number CN114650471A.

[0163] Data integration and analysis: The quality inspection data from the measurement module is comprehensively compared with the information obtained by the edge acquisition gateway. By comparing the consistency between the time points recorded in the first and last inspections of each process (the first inspection time and the last inspection time) and the start time of the first program and the end time of the last program of the corresponding process in the numerical control system, the corresponding first inspection time and last inspection time can be verified and data cleaned, and abnormal data with a deviation greater than the set threshold is deleted. The production progress is tracked and production capacity is analyzed using the cleaned processing data, further improving the accuracy of the results. For specific examples, refer to the processing method of the multi-source verification module in Embodiment 1.

[0164] In summary, the multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES functions provided by the embodiments of the present invention uses digital advanced measurement technology and intelligent data processing technology means to achieve the leap from single-quality assurance to production plan management optimization, can meet the higher data management and analysis requirements for portable terminals, significantly improves the efficiency of manufacturing enterprises in the quality inspection link and production operation, not only ensures that the final delivery quality meets the standards, but also lays a solid foundation for subsequent expansion. It can be widely applied to different industry scenarios and provides a powerful boost for promoting the transformation and upgrading of intelligent manufacturing.

Claims

1. A multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES functions, characterized in that: The method comprises an edge computing module for tracking the production progress and a measuring unit for performing quality inspection on the parts to be processed corresponding to the processing procedure and obtaining quality inspection data. The edge computing module executes a computer program to implement a production progress tracking method comprising the following steps: Collect the quality inspection data uploaded during the quality inspection process corresponding to the processing procedure; For a batch of parts to be processed, when determining the current production progress, the condition that a certain process is the current production progress of the batch of parts to be processed includes that only some parts of the process have corresponding quality inspection data.

2. The multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function according to claim 1 is characterized in that: The quality inspection data includes the time of quality inspection corresponding to each part; For each completed process of a batch of parts to be processed, the last quality inspection time is used as the actual completion time of the process, and the planned completion time and actual completion time of each completed process are displayed on the human-computer interaction interface.

3. The multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function according to claim 1 is characterized in that: The condition of the current production progress also includes: the necessary process before the process has quality inspection data of all parts.

4. The multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function according to claim 1 or 3, characterized in that: The condition of the current production progress also includes: there is no quality inspection data for the process after the process.

5. The multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function according to claim 1 is characterized in that: The quality inspection data includes the final inspection quality inspection data uploaded during the final inspection process; The parts with final quality inspection data in the current processing step are regarded as processed parts. The processed proportion of the processed parts in the total parts in the current processing step is obtained according to the number of processed parts. The processing progress of the corresponding step of the batch of parts is obtained according to the processed proportion.

6. The multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function according to claim 5 is characterized in that: The quality inspection data also includes the first inspection quality inspection data uploaded during the first inspection quality inspection process; Parts that do not have final inspection quality inspection data but have initial inspection quality inspection data in the current processing step are regarded as in-process parts. The processed proportion is combined with the number of in-process parts to obtain the processing progress of the corresponding step of the batch of parts.

7. The multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function according to claim 6 is characterized in that: The number of parts being processed is multiplied by a weight coefficient less than 1 to calculate the proportion of the total number of parts in the corresponding batch, and then the processed proportion is added to obtain the processing progress of the corresponding process of the batch of parts.

8. The multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function according to claim 5 is characterized in that: The final quality inspection data includes the time of quality inspection corresponding to each part; The latest quality inspection time in the final quality inspection data of the current process is used as the time to reach the corresponding production progress and / or the corresponding process processing progress.

9. The multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function according to claim 6, characterized in that: The first inspection quality inspection data and the final inspection quality inspection data both include the time of the corresponding quality inspection of each part; The first program start time and / or the last program termination time of the corresponding process obtained from the CNC system of the machine tool of the corresponding process are also used; the first program start time is compared with the time of the first inspection and quality inspection. If the difference exceeds the set value, the corresponding first inspection and quality inspection data will no longer be counted in the processing of parts; the last program termination time is compared with the time of the final inspection and quality inspection. If the difference exceeds the set value, the corresponding final inspection and quality inspection data will no longer be counted in the processing of parts.

10. The multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function according to claim 6, characterized in that: The edge computing module is also used to generate an SPC chart of key quality parameters that can reflect the quality inspection data of a batch of products corresponding to a process; The SPC chart is divided into a first inspection SPC chart that can reflect the key quality parameters of the first inspection quality inspection data of a certain batch of products corresponding to the process and a final inspection SPC chart that reflects the key quality parameters of the final inspection quality inspection data of the corresponding process; If the latest SPC chart is the first inspection SPC chart, the previous process of the process corresponding to the first inspection SPC chart is used as the production progress of a batch of products; If the latest SPC chart is a final inspection SPC chart, the process corresponding to the final inspection SPC chart is used as the production progress of a batch of products.

11. The multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function according to claim 1, characterized in that: The handheld industrial intelligent terminal also includes a camera for reporting work operations after performing facial recognition on the operator.

12. The multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function according to claim 1, characterized in that: The handheld industrial intelligent terminal also includes an RFID device for identifying the information code of the product; The information code is bound to the product ID and the quality inspection data of the product; the information code is in the form of a barcode and / or a QR code.

13. A multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function, characterized in that: The system comprises an edge computing module for analyzing production capacity and a measuring unit for performing quality inspection on the parts to be processed in the corresponding processing steps and obtaining quality inspection data, wherein the quality inspection data comprises the first inspection quality inspection data uploaded in the first inspection quality inspection process and the final inspection quality inspection data uploaded in the final inspection quality inspection process, and the edge computing module executes a computer program to implement the following production capacity analysis method: Collecting the first inspection quality inspection data and the final inspection quality inspection data corresponding to the processing steps; The first inspection quality inspection data and the final inspection quality inspection data both include the time of the corresponding quality inspection of each part; When determining production capacity, the time period for calculating production capacity is used to obtain the number of parts that have been processed within this time period, including the first inspection time and the final inspection time of all processes. The number of processed parts is used as the production capacity based on the corresponding time period.

14. The multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function according to claim 13, characterized in that: It also includes preset time intervals; The number of parts whose first inspection completion time and final inspection completion time of a process are both within the preset time interval is used as the production capacity of the process based on the corresponding time interval.

15. The multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function according to claim 14, characterized in that: The edge computing module also uses the first program start time and the last program end time of the corresponding process obtained from the CNC system of the corresponding process machine tool, and compares them with the first inspection completion time and the last inspection completion time respectively, and eliminates the first inspection completion time and the last inspection completion time whose difference exceeds the set threshold.

16. The multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function according to claim 13, characterized in that: The edge computing module is also used to generate a first inspection SPC chart that can reflect the key quality parameters of the first inspection quality inspection data of a certain batch of products corresponding to the process and a final inspection SPC chart of the key quality parameters of the final inspection quality inspection data of the corresponding process; When the number of data points of the key quality parameters on the first inspection SPC chart and the final inspection SPC chart is the same, the production capacity of the time period between the time corresponding to the earliest data point of the key quality parameter on the first inspection SPC chart and the time corresponding to the latest data point of the key quality parameter on the final inspection SPC chart is the number of data points of the key quality parameter on the first inspection SPC chart or the final inspection SPC chart.

17. The multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function according to claim 13, characterized in that: The handheld industrial intelligent terminal also includes a camera for reporting work operations after performing facial recognition on the operator.

18. The multi-source verification handheld industrial intelligent terminal integrating online measurement technology and MES function according to claim 13, characterized in that: The handheld industrial intelligent terminal also includes an RFID device for identifying the information code of the product; The information code is bound to the product ID and the quality inspection data of the product; the information code is in the form of a barcode and / or a QR code.

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