Automatic measurement system and method

Abstract

The invention provides an automatic measurement system and method which are used for improving the efficiency and accuracy of quality detection in the manufacturing industry. The system comprises an information extraction module which obtains product information through scanning an SN code or image recognition; the QMS interaction module communicates with a background system and automatically identifies test items; the program selection module is used for automatically matching and starting a measurement program according to items; the data uploading module is used for filling the result into a template and uploading the result to a database; and the utilization rate monitoring module is used for recording time nodes and analyzing the equipment utilization rate. The method comprises the steps of scanning a product, automatically matching a program, executing measurement, generating a report and monitoring the utilization rate. The method is developed on the basis of. NET Framework 4.8, is suitable for the precision manufacturing fields of electronics, automobiles and the like, and can reduce manual intervention and improve the detection speed and the data reliability.

Description

Technical Field

[0001] The present invention relates to the field of measurement systems, and in particular to an automated measurement system and method. Background Art

[0002] In the manufacturing industry's quality control process, accurate measurement of product parameters such as dimensions and appearance is crucial for ensuring product quality. Traditional measurement methods rely primarily on manual operations. For example, the measurement process is manually executed: Operators must manually enter product information, select measurement procedures, perform measurements, and record data. This approach is inefficient and prone to data errors due to human factors (such as fatigue and operator error). Procedure selection relies on experience: Different products may require different measurement procedures, and operators must be familiar with a large number of procedure paths, resulting in long training cycles for new employees and prone to errors. Data recording is cumbersome: After measurement, reports must be manually filled out or data copied into templates, which is not only time-consuming but can also affect data management due to formatting errors. Utilization rate monitoring is difficult: Traditional methods cannot automatically record measurement time points, resulting in inaccurate equipment utilization analysis and hindering production optimization. Some companies have attempted to adopt semi-automated solutions, such as barcode scanners or simple data collection software, but these still present the following issues: System isolation: Measurement equipment, QMS (Quality Management System), and MES (Manufacturing Execution System) lack data interoperability, requiring manual intervention. Lack of intelligence: Measurement programs cannot be automatically matched, requiring manual selection by the operator, failing to achieve true "unmanned operation." Lack of real-time monitoring: Equipment utilization rates cannot be automatically calculated, making it difficult to optimize production cycles. Therefore, a fully automated measurement system is urgently needed. Summary of the Invention

[0003] In response to the above-mentioned technical deficiencies, the purpose of the present invention is to provide an automated measurement system and method that intelligently identifies product information, automatically matches programs, seamlessly uploads data, and monitors equipment operating status in real time to improve efficiency, reduce human errors, and achieve closed-loop data management for intelligent manufacturing.

[0004] To achieve the above object, the present invention adopts the following technical solutions:

[0005] An automated measurement system, comprising:

[0006] The information extraction module is used to extract product information by scanning the SN code or order number on the product;

[0007] QMS interaction module, which communicates with the backend QMS system and automatically identifies the project name, workstation and test item;

[0008] Program selection module, automatically finds and opens the corresponding measurement program according to the test item;

[0009] The data upload module automatically opens the report template after the measurement is completed and uploads the measurement data to the background system;

[0010] The utilization rate monitoring module records time nodes and organizes them into JSON documents, which are uploaded to a specified path to monitor equipment utilization rates.

[0011] Preferably, the information extraction module obtains the product SN code or order number through a scanner or image recognition technology, and matches it with the database to extract product information.

[0012] Preferably, the QMS interaction module interacts with the backend QMS system through an API interface, automatically parses the project name, workstation and test item, and generates measurement task instructions.

[0013] Preferably, the program selection module automatically locates the measurement program through a path matching algorithm and calls the program interface to start the measurement process.

[0014] Preferably, the data upload module fills the measurement data into a preset report template through a template engine, and automatically saves the data into a file in a specified format and uploads it to the backend.

[0015] Preferably, the utilization rate monitoring module records the measurement start time, end time and abnormal interruption time, generates a log file in JSON format and uploads it to the monitoring server.

[0016] An automated measurement method comprises the following steps:

[0017] Scan the product SN code or order number to extract product information;

[0018] Interact with the backend QMS system to automatically identify project names, workstations, and test items;

[0019] Automatically search and open the corresponding measurement program according to the test item;

[0020] Execute the measurement program and automatically generate measurement data after completing the measurement;

[0021] Fill the measurement data into the report template and upload it to the backend system;

[0022] Record the time nodes of the measurement process, generate utilization rate monitoring data and upload it.

[0023] Preferably, the measurement program is started by calling a program interface, and the steps that require manual point selection during the measurement process are automatically completed through image recognition technology.

[0024] Preferably, the report template data upload is achieved through the background API interface.

[0025] Preferably, the utilization rate monitoring data includes measurement time, equipment status and abnormal records, which are used to analyze equipment operating efficiency.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] Automated program matching and data uploading reduce manual operations and increase measurement speed by more than 50%. New employees can get started without complex training, reducing labor costs. Avoid manual input errors and ensure that measurement data is 100% compliant with specifications. Standardized report templates eliminate format confusion issues. Seamlessly connect with QMS / MES systems, provide real-time feedback on quality data, and support rapid process adjustments. Utilization rate monitoring helps optimize production scheduling and improve equipment utilization. Supports multiple information input methods such as scanners and visual recognition. Can be expanded to meet the measurement needs of different industries (such as electronics, automobiles, and medical devices). Reduce the need for full-time measurement personnel and save manpower investment in the long term. Reduce equipment failure rate through preventive maintenance (based on utilization rate data). BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a flowchart of the present invention. DETAILED DESCRIPTION

[0029] The present invention will be further described below with reference to the accompanying drawings.

[0030] like Figure 1 As shown, an automated measurement system includes:

[0031] The information extraction module is used to extract product information by scanning the SN code or order number on the product;

[0032] QMS interaction module, which communicates with the backend QMS system and automatically identifies the project name, workstation and test item;

[0033] Program selection module, automatically finds and opens the corresponding measurement program according to the test item;

[0034] The data upload module automatically opens the report template after the measurement is completed and uploads the measurement data to the background system;

[0035] The utilization rate monitoring module records time nodes and organizes them into JSON documents, which are uploaded to a specified path to monitor equipment utilization rates.

[0036] In this embodiment, the information extraction module obtains the product SN code or order number through a scanner or image recognition technology, and matches it with the database to extract product information.

[0037] In this embodiment, the QMS interaction module interacts with the backend QMS system through an API interface, automatically parses the project name, workstation and test item, and generates measurement task instructions.

[0038] In this embodiment, the program selection module automatically locates the measurement program through a path matching algorithm and calls the program interface to start the measurement process.

[0039] In this embodiment, the data upload module fills the measurement data into a preset report template through a template engine, and automatically saves the data into a file in a specified format and uploads it to the backend.

[0040] In this embodiment, the utilization rate monitoring module records the measurement start time, end time, and abnormal interruption time, generates a log file in JSON format, and uploads it to the monitoring server.

[0041] An automated measurement method comprises the following steps:

[0042] Scan the product SN code or order number to extract product information;

[0043] Interact with the backend QMS system to automatically identify project names, workstations, and test items;

[0044] Automatically search and open the corresponding measurement program according to the test item;

[0045] Execute the measurement program and automatically generate measurement data after completing the measurement;

[0046] Fill the measurement data into the report template and upload it to the backend system;

[0047] Record the time nodes of the measurement process, generate utilization rate monitoring data and upload it.

[0048] In this embodiment, the measurement program is started by calling a program interface, and the steps that require manual point selection during the measurement process are automatically completed through image recognition technology.

[0049] In this embodiment, the report template data upload is implemented through the background API interface.

[0050] In this embodiment, the utilization rate monitoring data includes measurement time, equipment status, and abnormality records, which are used to analyze equipment operating efficiency.

[0051] Specific embodiment 1: Automated measurement system based on a scanner

[0052] Application scenarios:

[0053] In electronics manufacturing plants, operators need to inspect products for size and appearance. Traditional methods rely on manual labor, which is inefficient and prone to errors. This embodiment uses an automated measurement system to improve inspection efficiency and accuracy.

[0054] System composition and workflow:

[0055] Information extraction module: The operator uses a scanner to scan the SN code on the product, and the system automatically extracts product model, batch number and other information.

[0056] QMS interaction module: The system connects with QMS (Quality Management System) to automatically identify the current workstation (such as "appearance inspection workstation") and test items (such as "dimensional deviation detection").

[0057] Program selection module: The system automatically matches the corresponding measurement program (such as "Dimension Measurement.exe") according to the test item and starts the program.

[0058] Data upload module: After the measurement is completed, the system automatically fills the data into the preset Excel report template and uploads it to the QMS database.

[0059] Utilization rate monitoring module: The system records the measurement start and end times, generates JSON logs, and uploads them to the server for production management to analyze equipment utilization.

[0060] Technical effects:

[0061] Reduce manual operations and shorten measurement time by 50%.

[0062] Human recording errors are avoided and data accuracy is increased to 99.9%.

[0063] Monitor equipment utilization in real time and optimize production scheduling.

[0064] Specific embodiment 2: Automated measurement method based on image recognition

[0065] Application scenarios:

[0066] In automotive parts inspection, multiple characteristic points on precision parts need to be measured. Traditional methods rely on manual point selection, which is inefficient and prone to fatigue. This embodiment uses automated measurement methods combined with image recognition technology to achieve high-precision inspection.

[0067] Method steps:

[0068] Information extraction: The camera captures the QR code on the part, and the system decodes it to obtain the part number and inspection standard.

[0069] QMS interaction: The system obtains the inspection requirements of the part (such as "aperture tolerance ±0.01mm") from the QMS.

[0070] Program selection: The system automatically calls the corresponding visual measurement program (such as "aperture detection.py").

[0071] Automatic measurement:

[0072] The program locates part feature points (such as hole edges) through image recognition.

[0073] Automatically calculate the pore size and compare it with the standard value.

[0074] Data upload: The system generates a test report (TXT format), marks it as qualified / unqualified, and uploads it to the MES (Manufacturing Execution System).

[0075] Utilization rate monitoring: record the time spent on testing, calculate equipment utilization, and optimize the testing process.

[0076] Technical effects:

[0077] The detection speed is increased by 60%, making it suitable for mass production.

[0078] The image recognition accuracy reaches ±0.005mm, which is higher than manual measurement.

[0079] Data is uploaded in real time to ensure traceability of the entire process.

Claims

1. An automated measurement system, characterized in that: include: The information extraction module is used to extract product information by scanning the SN code or order number on the product; QMS interaction module, which communicates with the backend QMS system and automatically identifies the project name, workstation and test item; Program selection module, automatically finds and opens the corresponding measurement program according to the test item; The data upload module automatically opens the report template after the measurement is completed and uploads the measurement data to the background system; The utilization rate monitoring module records time nodes and organizes them into JSON documents, which are uploaded to a specified path to monitor equipment utilization rates.

2. An automated measurement system according to claim 1, characterized in that: The information extraction module obtains the product SN code or order number through a scanner or image recognition technology, and matches it with the database to extract product information.

3. The automated measurement system according to claim 1, wherein: The QMS interaction module interacts with the backend QMS system through the API interface, automatically parses the project name, work station and test item, and generates measurement task instructions.

4. The automated measurement system according to claim 1, wherein: The program selection module automatically locates the measurement program through the path matching algorithm and calls the program interface to start the measurement process.

5. The automated measurement system according to claim 1, wherein: The data upload module fills the measurement data into the preset report template through the template engine, and automatically saves it as a file in the specified format and uploads it to the background.

6. The automated measurement system according to claim 1, wherein: The utilization rate monitoring module records the measurement start time, end time, and abnormal interruption time, generates a log file in JSON format, and uploads it to the monitoring server.

7. An automated measurement method, characterized in that: The following steps are involved: Scan the product SN code or order number to extract product information; Interact with the backend QMS system to automatically identify project names, workstations, and test items; Automatically search and open the corresponding measurement program according to the test item; Execute the measurement program and automatically generate measurement data after completing the measurement; Fill the measurement data into the report template and upload it to the backend system; Record the time nodes of the measurement process, generate utilization rate monitoring data and upload it.

8. An automated measurement method according to claim 7, characterized in that: The measurement program is started by calling the program interface, and the steps that require manual point selection during the measurement process are automatically completed through image recognition technology.

9. The automated measurement method according to claim 7, wherein: Report template data upload is achieved through the background API interface.

10. The automated measurement method according to claim 7, wherein: Utilization rate monitoring data includes measurement time, equipment status, and abnormal records, which are used to analyze equipment operating efficiency.

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