Network transformation of enterprise measurement management in the network economy
The advent of the Internet era has completely reconstructed the information transmission logic of enterprise management. For enterprises that rely on measurement data to support quality control and cost accounting, the traditional manual operation mode (such as ledger registration and multi - level reporting) can no longer meet the digital requirements. Measurement management must shift from "off - line and decentralized" to "on - line and unified", and from "post - event summarization" to "real - time processing". This transformation not only provides measurement workers with a broader space for development but also poses the core issue of "how to build a networked management system".
I. The core connotation of the networking of measurement management
The networking of measurement management essentially involves leveraging computer network technology to build a unified measurement management information platform within the enterprise, breaking down the information barriers among the decision - making level, management level, and operation level, and achieving three core goals:
Data sharing: The measurement data obtained at all levels are completely consistent (avoiding "data conflicts among departments").
Real-time processing: Analyze data immediately instead of aggregating it afterwards (for example, decision-makers can see the calibration records just entered right away).
Process optimization: Transform traditional manual operations into intelligent and automated processes (for example, automatically generate verification plans instead of manual calculations).
Simply put, it means enabling the decision - making level to "see real - time data", the management level to "analyze data thoroughly", and the operation level to "record data accurately", and ultimately achieving "quality improvement, cost reduction, and efficiency enhancement" in measurement management.
II. The Practical Necessity of Networked Enterprise Measurement Management
(I) Solve the pain points of traditional management and improve management precision
The core contradictions of traditional measurement management are "information lag" and "high error rate":
- The decision-making level only sees the "inspection data from last week" and is unable to respond to the current production changes.
- Management needs to manually summarize the data of each department, which is prone to analysis deviations due to clerical errors and omissions in reporting.
- The operating layer needs to repeatedly enter ledger information and transfer paper documents, and their energy is consumed in "valueless labor".
Network management can completely solve these problems through intelligent process transformation:
- The decision-making level can view the full-link status of the metering process in real time (for example, whether all the measuring instruments on a certain production line have passed the verification).
- Management can conduct multi - dimensional queries through the system (e.g., by department, by appliance type, by time) to quickly identify the reasons for the decline in the pass rate of a certain type of appliance.
- The operating layer has reduced 80% of the manual statistical workload and can focus on core tasks such as "analyzing data anomalies" and "optimizing the verification process".
(II) Reduce management costs and improve the efficiency of information transmission
The information transmission in traditional measurement management has to pass through the successive levels of "operation level → management level → decision - making level", and each step is accompanied by time cost and information loss.
- It may take 3 - 5 days for a verification record to be transmitted from the workshop to the decision - making level.
- The "manual transcription" in the intermediate link is prone to causing data deviations (for example, writing "qualified" as "to be repaired").
Networked management changes the information transmission mode from "offline multi - level transfer" to "online direct communication".
- The statistical data at the decision - making level comes directly from the real - time data on the internal network, without the need to wait for reports from departments.
- Decision instructions are directly transmitted to the operation layer via the network (for example, "A certain instrument needs to be urgently calibrated", and the operation layer will immediately receive a reminder);
- The communication cost and labor cost of intermediate links are reduced by more than 50%, and the authenticity and effectiveness of information are fundamentally guaranteed.
(III) Release the vitality of personnel and increase management flexibility
In traditional metrology work, the time of metrology personnel is occupied by "running errands" and "keeping accounts":
- Go to the workshop to deliver the calibration plan and collect paper records.
- Manually register the ledger and calculate the "three rates".
Networked management liberates metrology personnel through electronic transmission.
- Replacing "running to different departments to deliver materials" with file transfer within the local area network saves 20% of working time.
- The system automatically counts the "three rates", replacing the "manual calculation of reports" and reducing 30% of repetitive work.
Measurement personnel can be freed from "routine work" and focus more on creative work. For example, they can analyze the reasons for "frequent failures of a certain type of instrument" and put forward suggestions for "optimizing the verification cycle", truly realizing the value of a "data analyst".
III. The Current Situation and Lagging Characteristics of Measurement Management in Chinese Enterprises
Although networking is a trend, most enterprises still remain in the stage of "traditional model + partial computer assistance". The lag is mainly reflected in four aspects:
(I) Management of measuring instruments: From "chaotic ledger" to "scattered data"
The drawbacks of traditional ledger management become increasingly prominent as the scale of the enterprise expands:
- The varieties (such as temperature, pressure, and flow) and quantities (ranging from dozens to thousands) of measuring instruments have increased significantly, doubling the workload of manually modifying the ledger.
- Manual registration is prone to the situation of "discrepancy between accounts and physical items" (for example, the equipment has been scrapped, but the ledger has not been updated).
- Even when computers are used, it is mostly in the form of "storing data on individual computers" – the data of the workshop is stored on the workshop's computer, and that of the metrology department is stored on the metrology computer. There is no way to share data, and summarizing data requires "copy + paste", resulting in extremely low efficiency.
(II) Measurement verification management: From difficulty in recording to confusion in status
The maintenance history and status management of measuring instruments are the "hard-hit areas" of the traditional model.
- Manually recording the maintenance history of each piece of equipment requires rummaging through a large number of paper archives. It takes several days to calculate "how many times a certain type of equipment has been repaired in a year".
- The status of equipment (in use, sealed up, scrapped) is manually counted, which is prone to errors. For example, a piece of equipment has been sealed up, but the system still arranges for its verification, wasting resources.
- These errors not only increase the management cost but may also lead to the poor operation of the quality management system (for example, using overdue inspection instruments in production, which affects the product quality).
(III) Measurement indicator system: From slow statistics to low efficiency
The "three rates" (weekly inspection rate, qualified rate of weekly inspections for in-use items, and qualified rate of spot checks) are the core indicators of metrology management, but the traditional statistical method is "regular collection + manual summarization":
- At the end of each month, each department reports data to the measurement management personnel, and then the management personnel compile it into a report.
- The problems with this method are poor timeliness (the statistics at the end of the month are "last month's data", which cannot reflect the current status), heavy workload (managers have to verify dozens of data sets), and weak analysis ability (it is impossible to immediately detect the trend of "a continuous decline in the qualification rate of a certain type of equipment").
(IV) Quantitative decision-making: From experience-driven to data distortion
Traditional quantitative decision-making relies on "layer-by-layer reporting" and has two fatal problems:
Time delay: It takes days or even weeks for reports to reach the decision-making level, and the data has become "outdated".
Information loss: Each layer may "filter" or "modify" the data. For example, the operation layer reports a "pass rate of 90%", the management layer changes it to "95%", and the decision-making layer sees "98%", ultimately making wrong decisions.
IV. Implementation path for networking of measurement management: System development and application
The core of metrology management networking is to build a metrology management system that meets the needs of the enterprise and achieve "accurate data entry and in - depth value mining" through standardized processes.
(I) Development of the measurement management system: Full - process design from requirements to modules
System development should revolve around the principle of "adapting to business and meeting user needs" and be carried out in three steps:
1. Define the core functions and anchor the development direction
A set of metrology management systems that are usable and easy to use must have six core functions:
Basic query: Support queries with any conditions (e.g., "Query the measuring instruments scrapped in Workshop A in the past 3 months").
Data exchange: Connect with the enterprise's ERP and MES systems to avoid "information silos".
Instant reports: Automatically generate reports such as the "three rates" and calibration plans without manual summarization.
Dynamic modeling: Adapt to enterprise business changes (such as adding new appliance types and adjusting verification cycles);
Business process reengineering: Transform the traditional process (application → planning → verification → recording) into an online automated process.
Collaborative work: Multiple departments and roles operate simultaneously (e.g., the operation level enters records while the management level views them synchronously).
2. Preparatory work: Avoid making a cart behind closed doors
Before system development, two key issues need to be resolved:
Establish management specifications suitable for computers: For example, unify the numbering rules for measuring instruments ("department + type + number") and data entry standards (e.g., for "verification result", only "qualified/unqualified/awaiting repair" can be selected).
Collect user requirements: Conduct in - depth communication with the decision - making level (What reports are needed?), the management level (What analysis functions are needed?), and the operation level (Is it convenient for data entry?) to form a requirements document. For example, the operation level requires that "the data entry interface should be simple and capable of batch data import", and the management level requires that "trend charts can be generated".
3. Modular design: Covers all scenarios of measurement management
A complete system needs to include eight core modules (covering the entire metrology process):
Module Name Core Functions
Management of metrology basic file Manage metrology personnel information, instrument numbering rules, and technical data
Management of measuring instrument allocation Automatically count the allocation quantity and allocation rate of instruments in each department (e.g., "Workshop A should be allocated 10 units, but actually 8 units are allocated").
Measurement system management Store management system files (procedure files, verification regulations) and support version control
Management of measuring instruments Establish a full-life cycle archive and conduct real-time statistics on the status (marked with colors: green for in use, yellow for sealed, red for scrapped)
Measurement verification (calibration) management Automatically generate periodic plans, issue overdue alarms, and statistics the "three rates".
Traceability management of measurement values Tree-type display of traceability relationships (enterprise standards → National Institute of Metrology)
System management Set permissions, perform data synchronization, and maintain work logs (recording "who operated what at what time")
Toolbox module Supports secondary development (such as custom reports and query functions)
(II) Application of the measurement management system: Standard process from authorization to usage
After the system development is completed, the key is to "put it into use", and two core issues need to be addressed:
1. Permission settings: Ensure data security
Measurement data is the core information of an enterprise (for example, product quality data directly affects customer trust). It is necessary to set permissions to ensure that "the right people can access the right data":
Decision - making level: Full authority (view all data and use all functions);
Management: Full permissions except for "System Management" (able to analyze data and generate reports);
Operation layer:
- Verification/maintenance personnel: Only allowed to enter and modify their own verification records.
- Department metrologist: Can only enter data of the department and query the situation of the department.
2. Usage process: From "accurate recording" to "good utilization"
The system usage is divided into two steps:
Data collection: It is completed by the operation level, and the core is "accurate recording". The verification personnel enter the verification records (instrument numbers, results, maintenance content) every day, and the department metrologists enter the instrument information (newly added, sealed) of their own departments.
Data usage: It is completed by the management and decision - making levels, with the core being "using well". The management analyzes problems through the system - generated fixed reports (monthly "three rates") and dynamic reports (the qualification rate trend of a certain type of equipment). The decision - making level views macro - data (the overall "three rates" and the allocation rate of the enterprise) and formulates strategies (such as "adding new measurement standards" and "adjusting the verification cycle").
V. Conclusion
In the era of the digital economy, the networking of measurement management is not an "optional question" but a "compulsory question". It can not only address the pain points of "slowness, errors, and high costs" in the traditional model, but also upgrade measurement data from a "recording tool" to a "decision-making support" - shifting from "post-event remediation" to "pre-event prediction" (such as predicting the failure risk of instruments through AI).
For enterprise metrology workers, the core of the transformation is to shift from being "traditional bookkeepers" to "data analysts": instead of just entering data, they should dig out the value of data and provide accurate basis for enterprise decision-making. In the future, with the integration of artificial intelligence and big data technologies, the networking of metrology management will be further deepened, but the logic of "data at the core and users at the center" will always remain unchanged - only by grasping this core can one take the initiative in the digital wave.
Core responsibilities of the management: Full - process standardized control of the measurement system
As the overall control center of measurement management, the management needs to build a traceable and verifiable management system around four major dimensions: personnel competence, technical compliance, instrument operation, and process closure.
Management of metrology personnel and technical data: Dynamically file the qualifications of metrology personnel (such as national verifier certificates and industry calibration qualifications) and training records (such as annual update training on the Metrology Law and new instrument operation assessments) to ensure that the personnel's capabilities match the job requirements. Classify and store metrology technical data (such as national/industry verification regulations, enterprise internal calibration SOPs, historical verification reports, and instrument maintenance manuals) according to "regulation version - instrument type - using workshop". For example, the electronic balance in the workshop needs to be associated with the latest JJG 98 - 2006 "Mechanical Balance" regulation to avoid calibration deviations caused by using expired technical documents.
Management and control of measuring instrument allocation and measurement value traceability: According to the accuracy requirements of the production process (e.g., the weight deviation of the food packaging line ≤ ±0.5%), match measuring instruments with corresponding accuracy levels (e.g., select an electronic scale with an accuracy of 0.1g instead of a platform scale with an accuracy of 1g); strictly control the measurement value traceability path - all measuring instruments need to be traceable to national measurement standards or calibration institutions recognized by CNAS. For example, the temperature sensors in the workshop need to be sent to the local metrology institute for verification and traced back to the national temperature standard to ensure the legality and accuracy of the measurement results.
Tracking the codes of newly purchased instruments and maintenance progress: For newly purchased measuring instruments, a unique coding rule of "type - specification - year - serial number" is adopted (for example, "SC - 100g - 2023 - 001" represents an electronic scale of 100g purchased in 2023) to achieve the unique identification of the instrument's identity. The maintenance progress is tracked in real - time through the management system. The nodes of the instrument from "sent for inspection" to "under maintenance" and then to "calibration completed" will be automatically updated. The management can check the status of a certain instrument at any time (for example, "The electronic scale sent for inspection on October 15, 2023, is currently in the 'replacing the sensor' stage"), so as to avoid the impact on production due to maintenance delays.
Equipment status statistics and spot - check management: Count the number of equipment according to three statuses of "in use - sealed - scrapped". The statistical dimension can be refined to workshops, equipment types, and service life (e.g., "In the assembly workshop, there are 30 vernier calipers in use, 5 sealed, and 2 scrapped"). Determine the spot - check ratio based on the risk level of the equipment (e.g., equipment in key processes is of high risk, while that in auxiliary processes is of low risk). The spot - check ratio for high - risk equipment is 20%, and that for low - risk equipment is 5%. Automatically generate spot - check forms. The spot - check forms include equipment numbers, locations, and spot - check requirements (e.g., "Check whether the indication error of the vernier caliper is ≤ 0.02mm") to ensure the pertinence and compliance of the spot - checks.
Verification cycle planning and statistics of the "three rates": Determine the verification/calibration cycle based on national regulations, frequency of use, and environmental impact. For example, the cycle for an electronic scale used 8 hours a day is 6 months, while that for a platform scale used only once a month is 12 months. Prepare a periodic verification plan in combination with the production schedule (e.g., avoid peak seasons) to ensure the plan is executable (e.g., arrange the verification of measuring instruments on the packaging line during the Spring Festival shutdown period). Statistically analyze the "three rates" (Verification rate = Number of verified instruments / Number of instruments to be verified; Pass rate = Number of qualified instruments / Number of verified instruments; Traceability rate = Number of instruments traceable to compliant institutions / Total number of instruments), and use the data for the effectiveness evaluation of the measurement system. For example, if the verification rate increases from 95% to 98% in a certain quarter, it indicates that the plan is implemented more effectively. If the pass rate drops from 92% to 88%, it is necessary to investigate issues such as instrument aging or improper operation.
Core responsibilities of the operation layer: Practical entry for measurement data
The operation layer is the "execution terminal" of measurement management, focusing on the real - time nature and accuracy of data entry, record update, and query output.
Input and output of metrology information: Input the basic information of measuring instruments (model, specification, manufacturer, purchase date, department receiving the instrument, installation location) and initial parameters (such as the maximum weighing capacity and graduation value of an electronic scale); Output the approved verification result notices and calibration reports. For example, after the calibration of the quantitative filling machine on the packaging line is completed, the operator needs to input "The indication error at the calibration point of 1000g is +0.3g" and output the calibration report to the workshop director as the basis for process adjustment.
Management of verification/calibration/repair records: Enter the operation records of measuring instruments in real time. For example, "On October 15, 2023, the electronic scale passed the verification, and the certificate number is J20231015001", "On November 01, 2023, the calibration result of the thermometer: the indicated value is 25.1℃ at 25℃, meeting the requirements", "On November 05, 2023, the vernier caliper was stuck and returned to normal after replacing the spring". The records should be synchronized with the actual operations to avoid data deviation caused by "retroactive entry".
Multi - condition query and standardized output: Support querying by any combination of conditions such as "appliance number, using department, verification date, status", etc. - For example, the workshop director can query "the verification results of all electronic scales in use in the assembly workshop since October 2023"; the query results can be printed in the enterprise standard format (including appliance information, verification date, results, and signature of the verifier) to meet the requirements of internal audits or customer factory inspections.
Network system security: Three barriers for data reliability
The core risks of networked management are data leakage, tampering, or loss. A security defense line needs to be established through "permission control + data backup":
Workstation permission and password management: Based on the user permission management of Windows NT, set passwords according to the "principle of least privilege" – administrators can modify system configurations, meter readers can only enter data, and workshop directors can only view the data of their own workshops. Users need to enter the correct password to access the corresponding data to avoid unauthorized modification.
Software hierarchical permission and password management: The system sets passwords in a hierarchical manner according to the "decision-making level - management level - operation level". The decision-making level (such as the deputy leader in charge) can manage the passwords of the management level and the operation level. The management level (such as the metering section chief) can manage the passwords of the operation level. The operation level can only modify its own password. This "top-down" management prevents the abuse of permissions (for example, operation personnel cannot modify the data of other departments).
Backup and recovery of raw data: The management needs to conduct "local + cloud" dual backups regularly - perform a full backup every Sunday (stored in the enterprise server and Alibaba Cloud OSS), and conduct an incremental backup at 18:00 every day (only back up the data of the current day); carry out recovery tests every quarter to ensure that the data can be recovered within 1 hour after data loss, so as to avoid data unavailability caused by hard disk damage or virus attacks.
Trends and Practices of Networked Measurement Management
The networking of measurement management is by no means a simple act of "buying a system", but rather a systematic project that needs to be combined with the actual situation of the enterprise and involve cross - departmental collaboration:
Demand-oriented: Before implementation, it is necessary to conduct research on the production process (for example, chemical enterprises have much higher accuracy requirements for pressure transmitters than textile enterprises), existing resources (such as the quantity, accuracy, and traceability status of existing instruments), and personnel capabilities (such as the computer proficiency of metrologists) to avoid "formalistic networking".
System design: It is necessary to focus on "usability" and "scalability". For example, it supports the access of IoT devices (such as real-time data upload from smart meters), and can be extended for big data analysis in the future (such as predicting maintenance time through historical fault data).
Promotion and implementation: Training needs to be strengthened (such as system operation for metrologists and data analysis for management) to ensure that the system is integrated into daily work rather than being just for show.
In terms of trends, the networking of measurement management is an important part of the digital transformation of enterprises. In the future, it will shift from "passive verification" to "active prediction" (for example, monitoring the temperature of machine tools through vibration sensors and calibrating instruments in advance), and from "manual statistics" to "intelligent analysis" (for example, the system automatically generates measurement system reports).
Metrology workers in our country need to actively embrace changes. On the one hand, they should learn about the integration of metrology and information technology (for example, connecting metrology data to the MES system). On the other hand, they should participate in system requirement surveys (for example, providing feedback like "hoping to add a reminder for the expiration of measuring instruments") and explore models suitable for their own enterprises. Only in this way can the efficiency of metrology management be improved and the metrology level in our country be promoted to catch up with the international advanced level.
References
[1] Chen Wei, Liang Chunyu. Guide to the Grading and Upgrading of Measurement in Industrial Enterprises [M]. Beijing: China Metrology Press, 1986: 9.
[2] Yang Zhengming. Several Issues in the Informatization Construction of Grain Enterprises [J]. Grain Science and Technology and Economy, 1999(4).
[3] Yang Zhengming. Construction Plan for Flour Production, Operation and Management Network [J]. Western China Cereals & Oils Technology, 1999(1).