A mold pre-machine forced measurement and error proofing system based on timing compliance verification

Abstract

This invention belongs to the field of mold preparation and quality control technology in the production process of high-end aluminum alloy extruded flat bars for aerospace applications. It discloses a mandatory measurement and error-proofing system for molds before machine operation based on time-series compliance verification, solving the problem that existing technologies cannot fundamentally eliminate "missed measurements" before mold operation. It includes: a mold digital identity module: establishing a unique electronic identity for each mold, which is linked to the mold lifecycle file in a database; an error-proofing logic module: containing a built-in machine operation permission algorithm to generate temporary authorization codes or locking signals; a locking execution module: used to receive and execute instructions from the error-proofing logic module and the measurement data feedback and self-learning module; and a measurement data feedback and self-learning module. This invention helps eliminate blind spots of empiricism, achieve mandatory error-proofing, improve quality traceability capabilities, and enhance intelligence.

Description

Technical Field

[0001] This invention belongs to the field of mold preparation and quality control technology in the production process of high-end aluminum alloy extruded flat bars for aviation, and particularly relates to a forced measurement and error prevention system for molds before they are put into operation based on time sequence compliance verification. Background Technology

[0002] In the production of aluminum alloy extruded flat bars for aerospace applications, the dimensional accuracy of the die directly determines the cross-sectional geometry and performance of the product. In accordance with quality management standards, the key dimensions (such as working strip width, thickness, and fillet radius) of the die must be re-measured before each use to confirm that no deformation or damage has occurred after storage or die repair, ensuring compliance with process requirements.

[0003] However, in actual production, due to reliance on the experience and judgment of operators or mold repair technicians, it is common to skip the pre-production measurement because "the dimensions were acceptable in the last production". This empirical behavior leads to two major technical problems: (1) Quality control blind spots: The mold may be slightly deformed due to bumps, corrosion or environmental temperature changes during storage. If it is put directly into the machine without measurement, it may cause the dimensions of the entire batch of products to be out of tolerance, resulting in batch scrap. (2) Difficulty in tracing the problem: Once a quality defect occurs, due to the lack of baseline data before the mold is put into the machine, it is impossible to distinguish whether it is a mold problem or a process parameter problem, which makes it impossible to conduct root cause analysis.

[0004] In existing technologies, although there are mold management systems or barcode traceability methods, most of them rely on manual execution and lack mandatory technical locking mechanisms, which cannot fundamentally eliminate the behavior of "missed testing". Summary of the Invention

[0005] The purpose of this invention is to provide a forced measurement and error prevention system for molds before they are put into operation based on timing compliance verification, which effectively solves the problem that existing technologies cannot fundamentally eliminate the "missed measurement" behavior before molds are put into operation.

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: a forced measurement and error prevention system for molds before machine installation based on time sequence compliance verification, comprising: a mold digital identity module: establishing a unique electronic identity for each set of molds, the electronic identity being associated with the mold lifecycle file in the database; an error prevention logic module: having a built-in machine installation permission algorithm to generate a temporary authorization code or a locking signal; a locking execution module: used to receive and execute instructions from the error prevention logic module and the measurement data feedback and self-learning module; and a measurement data feedback and self-learning module.

[0007] Furthermore, the logical judgment steps of the machine access permission algorithm built into the error prevention logic module include: S1, when reading the electronic identity of the mold, automatically retrieve the actual measured size data of the mold before the most recent machine access, denoted as D_last.

[0008] S2. Calculate the time interval between the current time and the most recent measurement time. According to the trust decay function Determine the level of trust.

[0009] S3, Automatic retrieval within time intervals Within the mold, if a preset event has occurred, an event trigger signal is generated. ;otherwise .

[0010] S4. Output the judgment result: If D_last meets the product process standards, and Greater than the preset trust threshold, and If the test is successful, the device is deemed exempt from testing and a temporary authorization code is generated; otherwise, the device is deemed to be subject to mandatory testing and a lockout signal is generated.

[0011] Furthermore, the control logic of the measurement data feedback and self-learning module is as follows: B1. When in a forced measurement state, perform the measurement and upload the measurement data D_new to the database in real time.

[0012] B2. Compare D_new with D_last: B21. Determine if D_new is within the preset process tolerance range. If D_new exceeds the process tolerance range, it is determined that the measurement is unqualified, and a lock-up signal is output and transmitted to the lock-up execution module and the management terminal. If D_new is within the process tolerance range, it is determined that the measurement is qualified, and a measurement qualification confirmation signal is output and transmitted to the lock-up execution module.

[0013] B22. Based on the determination that the measurement is qualified, retrieve the historical measurement data sequence of the mold and analyze the changing trend of the historical measurement data sequence: if D_new shows a monotonically increasing or monotonically decreasing trend relative to the historical measurement data sequence and is within the process tolerance zone, it is determined to be a trend anomaly. The validity of the measurement qualification confirmation signal is maintained, but an additional warning message is generated and pushed to the management terminal.

[0014] B3. Based on the actual data from each measurement, dynamically optimize the model parameters of the trust decay function. The model parameters include one or more of the following: decay rate, decay coefficient, trust threshold, and initial trust value. The measurement data feedback and self-learning module establishes differentiated parameter sets for different mold types, materials, storage environments, and operating conditions, and updates them to the error prevention logic module in real time.

[0015] Furthermore, the locking execution module includes a programmable logic controller (PLC) and a physical locking mechanism driven by the PLC. The physical locking mechanism includes material flow locking and equipment start locking. Material flow locking means that after receiving a locking signal, the material flow equipment in the mold storage area refuses to transport the mold from the inspection area to the waiting area or machine, and only unlocks after receiving a measurement pass confirmation signal. Equipment start locking means that after receiving a locking signal, the equipment start control system remains locked until it receives a measurement pass confirmation signal before unlocking.

[0016] Furthermore, the mold lifecycle file includes the mold number, initial design dimensions, actual dimensions after each mold repair, actual dimensions before the most recent machine installation, dimensions of the last product after the most recent production, and a timestamp.

[0017] Furthermore, in step S3, the preset events include mold repair operation, collision alarm, and abnormal environment record.

[0018] Furthermore, in step S2, the trust decay function It can be an exponential decay function or a linear decay function; when the trust decay function is an exponential decay function: ; When the trust decay function is a linear decay function: ; In the formula, and Both represent the attenuation coefficient.

[0019] Furthermore, in step S4, the validity period management of the temporary authorization code includes: validity period setting: configuring different validity periods based on production cycle time and mold turnover speed; expiration determination: when scanning the temporary authorization code to unlock, comparing the current time with the temporary authorization code generation time in real time. If the validity period has expired, it is determined to be expired, the unlocking operation is refused, and a prompt is made to re-perform compliance verification; dynamic adjustment: optimizing the validity period parameters based on historical data through self-learning.

[0020] Compared with the prior art, the beneficial technical effects of the present invention are: (1) Eliminating the blind spot of empiricism: by introducing the time decay factor and the event triggering factor, the vague experience of "last time qualified" is transformed into a quantifiable mathematical judgment model, thus eliminating human negligence from the algorithm level.

[0021] (2) Achieve mandatory error prevention: The software judgment result is linked with the hardware locking mechanism to form a technical closed loop of "judgment-execution". Any mold that fails the conformity verification cannot enter the production process, thus physically eliminating illegal operations.

[0022] (3) Enhance quality traceability: The system automatically records the measured data before each use, providing accurate data assets for the full life cycle management of the mold, which facilitates subsequent analysis of mold wear patterns and process optimization.

[0023] (4) High level of intelligence: Through measurement data feedback and self-learning module, the system can dynamically adjust the trust model according to historical data, making the management logic more in line with the actual production conditions and conforming to the trend of intelligent manufacturing. Attached Figure Description

[0024] Figure 1 This is a flowchart of the error prevention logic module of the present invention. Detailed Implementation

[0025] Example 1: A forced measurement and error prevention system for molds before they are put into operation based on timing compliance verification, including: a mold digital identity module, an error prevention logic module, a locking execution module, and a measurement data feedback and self-learning module.

[0026] (1) Mold Digital Identity Module.

[0027] A unique electronic identity (such as a passive RFID tag or a high-temperature resistant QR code) is established for each mold, and this electronic identity is linked to the mold lifecycle file in the background database.

[0028] The lifecycle file shall include at least: mold number, initial design dimensions, actual dimensions after each mold modification, actual dimensions before the most recent machine installation, dimensions of the last product after the most recent production, and timestamp.

[0029] (2) Error prevention logic module based on timing compliance.

[0030] The error prevention logic module has a built-in machine access permission algorithm. Its logic judgment steps include: S1, historical data retrieval: when the electronic identity of the mold is read, the measured size data of the mold before the last machine access is automatically retrieved and recorded as D_last.

[0031] S2. Time decay factor calculation: Calculate the time interval between the current time and the most recent measurement time. The system has a built-in preset trust decay function. The trust decay function is used to quantify the decrease in trust over time, and the trust level is determined by the trust decay function.

[0032] The trust decay function is the time interval. For monotonically non-increasing functions (exponential decay functions or linear decay functions), the measurement data feedback and self-learning module can automatically identify and select the trust decay function model with higher fit or dynamically adjust the model parameters based on historical measurement data. When the trust decay function is an exponential decay function: ; When the trust decay function is a linear decay function: ; In the formula, and Both represent the attenuation coefficient.

[0033] S3, Event Trigger Detection: Automatically retrieves events triggered within time intervals. The system checks whether the mold has experienced any preset events such as "mold repair operation," "collision alarm," or "abnormal environment record." If such a preset event has occurred, an event trigger signal is generated. ;otherwise .

[0034] S4. Compliance Determination: Output the determination result based on the following logic: If D_last conforms to the product process standard, and Greater than the preset trust threshold, and If the test is successful, the device is deemed exempt from testing and a temporary authorization code is generated; otherwise, the device is deemed to be subject to mandatory testing and a lockout signal is generated.

[0035] The temporary authorization code is bound to the mold's electronic identity (ID) and its generation timestamp is recorded. The temporary authorization code can be generated using encryption algorithms (such as HMAC, RSA digital signature) and contains information such as the mold's electronic identity, generation time, validity period, and allowed number of uses to prevent forgery and tampering.

[0036] The attribute fields of a temporary authorization code include: ① Authorization Code ID: A unique identifier. ② Bound Mold ID: Restricts the use of this authorization code to the specified mold. ③ Generation Time: A timestamp accurate to the second. ④ Validity Period: A preset valid time window (e.g., 24 hours, 8 hours, etc.). ⑤ Maximum Number of Uses: Usually once to prevent repeated use. ⑥ Status Indicator: Valid, Used, Expired, or Invalid.

[0037] Temporary Authorization Code Validity Management: ① Validity Setting: The system can be configured with different validity periods based on production cycle time and mold turnover speed. For example, it is normally set to 24 hours, but can be shortened to 8 hours if the production line is fast-paced. The validity period is calculated from the time the authorization code is generated. ② Expiration Judgment: When an operator scans the authorization code at the equipment startup or access control, the system compares the current time with the authorization code generation time in real time. If the validity period has expired, it is judged as expired, the unlocking operation is refused, and a prompt is made to re-perform compliance verification. ③ Dynamic Adjustment: The system can learn and optimize the validity period parameters based on historical data. For example, if it is found that a certain type of mold has not been used for a long time after the authorization code is generated, leading to an increased risk, the default validity period of that type of mold can be automatically shortened.

[0038] Temporary authorization code usage restrictions: ① Single use restriction: Authorization codes are set to be used only by default. Once an authorization code is successfully used to unlock access control or start a device, the system immediately marks its status as "used," and any subsequent attempts will be invalid. This prevents the authorization code from being copied and reused multiple times across multiple shifts. ② Device binding restriction: Authorization codes can be bound to target devices (such as a specified extruder) to prevent them from being used on other unauthorized devices. For example, the machine number planned for use can be recorded when generating the authorization code, and the machine number must be compared when unlocking. ③ Operator permission association: Authorization codes can be bound to operator employee numbers or roles, and are only valid when operated by designated personnel, increasing security.

[0039] Temporary Authorization Code Usage and Verification Process: Step 1: Obtain Authorization Code: When the error prevention logic module determines that the machine can be used without testing, the system generates a temporary authorization code and sends it to the operator's terminal (such as a handheld PDA or mobile APP) or displays it directly on the system interface. Step 2: Unlock Request: The operator enters or scans the authorization code at the mold library access control or extruder start interface, and the system backend receives the request. Step 3: Real-time Verification: Parse the authorization code and verify the signature's legality; compare whether the bound mold ID matches the currently scanned mold ID; check whether the current time is within the validity period; check whether the authorization code status is "valid" and the number of uses has not exceeded the limit; if device binding is involved, compare the current device ID with the bound device ID. Step 4: When verification is successful, the system sends an unlock command to the locking execution module, allowing mold circulation or equipment start-up, and updates the authorization code status to "used"; when verification fails, the operation is rejected, an exception log is recorded, and the operator is prompted to re-perform the compliance verification.

[0040] Temporary Authorization Code Anomaly Handling and Security Assurance: ① Authorization Code Revocation Mechanism: If an unexpected event occurs to the mold during the authorization code's validity period (such as strong vibration detected by the sensor or abnormal temperature), the system can proactively invalidate all valid authorization codes corresponding to that mold, forcing a re-measurement upon next use. ② Brute-force Protection: In the event of multiple consecutive incorrect authorization code entries, the system can temporarily lock the mold or operator account to prevent malicious attempts. ③ Audit Log: All authorization code generation, usage, and invalidation operations are recorded in the database for easy traceability and auditing.

[0041] This embodiment achieves refined access control by binding temporary authorization codes with multiple dimensions such as time, mold ID, and device ID; it prevents the abuse and reuse of authorization codes by combining the one-time use of temporary authorization codes with strict validity periods; it ensures the closed loop of the system's error prevention logic by using a dynamic invalidation mechanism to deal with real-time changes in mold status; and it guarantees the anti-counterfeiting and integrity of authorization codes through encrypted signatures.

[0042] (3) Locking Execution Module: Receives and executes instructions from the error prevention logic module and the measurement data feedback and self-learning module.

[0043] The locking execution module includes a programmable logic controller (PLC) and a physical locking mechanism driven by the PLC. The physical locking mechanism includes material flow locking and equipment start locking. Material flow locking refers to the process where, upon receiving a locking signal, the electronic access control system, intelligent shelf, or AGV (Automated Guided Vehicle) in the mold storage area refuses to transport the mold from the inspection area to the waiting area or machine, and only unlocks after receiving a measurement confirmation signal. Equipment start locking refers to the process where, upon receiving a locking signal, the equipment start control system, such as the upper mold fixture or main motor start circuit of an extruder, remains locked until a measurement confirmation signal is received, at which point it unlocks.

[0044] (4) Measurement data feedback and self-learning module.

[0045] The control logic of the measurement data feedback and self-learning module is as follows: B1. When the system is in a forced measurement state, the operator needs to use a smart measuring tool connected to the system to perform the measurement and upload the measurement data D_new to the database in real time.

[0046] B2. Compare D_new with D_last: B21. Determine if D_new is within the preset process tolerance range. If D_new exceeds the process tolerance range, it is determined that the measurement is unqualified, and a lock-up signal is output and transmitted to the lock-up execution module and the management terminal. If D_new is within the process tolerance range, it is determined that the measurement is qualified, and a measurement qualification confirmation signal is output and transmitted to the lock-up execution module.

[0047] B22. Based on the determination that the measurement is qualified, retrieve the historical measurement data sequence of the mold and analyze the changing trend of the historical measurement data sequence: if D_new shows a monotonically increasing or monotonically decreasing trend relative to the historical measurement data sequence and is close to the process tolerance boundary (such as being within the process tolerance zone), it is determined to be a trend anomaly. The validity of the measurement qualification confirmation signal is maintained (without interrupting production), but an additional warning message is generated and pushed to the management terminal to prompt preventive maintenance of the mold or enhanced process sampling inspection.

[0048] B3. Based on the actual data from each measurement, dynamically optimize the model parameters of the trust decay function. These model parameters include one or more of the following: decay rate, decay coefficient, trust threshold, and initial trust value. The measurement data feedback and self-learning module establishes differentiated parameter sets for different mold types, materials, storage environments, and operating conditions, and updates them to the error prevention logic module in real time.

[0049] This embodiment provides a system that can forcibly trigger measurement, automatically determine compliance, and interlock with the equipment, thereby technically eliminating the possibility of putting the mold on the machine without measurement. It effectively solves the technical problem in existing extrusion production where the mold size measurement process before being put on the machine relies on manual experience and there is a risk of missed measurement.

[0050] This embodiment can (1) eliminate the blind spot of empiricism: by introducing time decay factor and event triggering factor, the vague "last qualified" experience is transformed into a quantifiable mathematical judgment model, eliminating human negligence from the algorithm level. (2) realize mandatory error prevention: by linking the software judgment result with the hardware locking mechanism, a technical closed loop of "judgment-execution" is formed. Any mold that fails the conformity verification cannot enter the production process, physically eliminating the violation operation. (3) improve the quality traceability capability: the system automatically records the actual measurement data before each machine, providing accurate data assets for the full life cycle management of the mold, which is convenient for subsequent analysis of mold wear patterns and process optimization. (4) have a high level of intelligence: through measurement data feedback and self-learning module, the system can dynamically adjust the trust model according to historical data, making the management logic more in line with the actual production conditions and conforming to the trend of intelligent manufacturing.

[0051] Of course, the above description is not intended to limit the present invention, and the present invention is not limited to the examples given above. Any changes, modifications, additions or substitutions made by those skilled in the art within the scope of the present invention should also fall within the protection scope of the present invention.

Claims

1. A forced measurement and error prevention system for molds before machine installation based on timing compliance verification, characterized in that, include: Mold Digital Identity Module: Establishes a unique electronic identity for each mold, which is linked to the mold lifecycle file in the database; Error prevention logic module: Built-in on-machine permission algorithm to generate temporary authorization code or lock signal; Lockout execution module: Used to receive and execute instructions from the error prevention logic module and the measurement data feedback and self-learning module; In addition, there is a measurement data feedback and self-learning module.

2. The forced measurement and error prevention system for molds before machine installation based on timing compliance verification according to claim 1, characterized in that, The logical judgment steps of the built-in machine access permission algorithm in the error prevention logic module include: S1. When the electronic identification of the mold is read, the measured dimension data of the mold before the last time it was put into operation is automatically retrieved and recorded as D_last; S2. Calculate the time interval between the current time and the most recent measurement time. According to the trust decay function Determine the level of trust; S3, Automatic retrieval within time intervals Within the mold, if a preset event has occurred, an event trigger signal is generated. ;otherwise ; S4. Output the judgment result: If D_last meets the product process standards, and Greater than the preset trust threshold, and If the test is successful, the device is deemed exempt from testing and a temporary authorization code is generated; otherwise, the device is deemed to be subject to mandatory testing and a lockout signal is generated.

3. The forced measurement and error prevention system for molds before machine installation based on timing compliance verification according to claim 2, characterized in that, The control logic of the measurement data feedback and self-learning module is as follows: B1. When in forced measurement state, perform measurement and upload the current measurement data D_new to the database in real time; B2. Compare D_new with D_last: B21. Determine whether D_new is within the preset process tolerance range. If D_new exceeds the process tolerance range, it is determined that the measurement is unqualified, and a lock-up signal is output and transmitted to the lock-up execution module and the management terminal. If D_new is within the process tolerance range, the measurement is deemed qualified, a measurement qualification confirmation signal is output and transmitted to the lock-up execution module; B22. Based on the determination that the measurement is qualified, retrieve the historical measurement data sequence of the mold and analyze the changing trend of the historical measurement data sequence: If D_new shows a monotonically increasing or monotonically decreasing trend relative to the historical measurement data sequence and is within the process tolerance zone, it is judged as a trend anomaly. The validity of the measurement qualification confirmation signal is maintained, but an additional warning message is generated and sent to the management terminal. B3. Based on the actual data from each measurement, dynamically optimize the model parameters of the trust decay function, wherein the model parameters include one or more of the following: decay rate, decay coefficient, and trust threshold. The measurement data feedback and self-learning module establishes differentiated parameter sets for different mold types, materials, storage environments, and operating conditions, and updates them to the error prevention logic module in real time.

4. The forced measurement and error prevention system for molds before machine installation based on timing compliance verification according to claim 3, characterized in that, The locking execution module includes a programmable logic controller and a physical locking mechanism driven by the programmable logic controller. The physical locking mechanism includes material flow locking and equipment start locking. Material flow lock means that after receiving a lock signal, the material flow equipment in the mold storage area refuses to transport the mold from the inspection area to the waiting area or machine until a measurement qualification confirmation signal is received before unlocking. Equipment start-up lockout means that after the equipment start-up control system receives the lockout signal, it remains locked until a measurement pass confirmation signal is received before it is unlocked.

5. The forced measurement and error prevention system for molds before machine installation based on timing compliance verification according to claim 1, characterized in that, The mold lifecycle file includes the mold number, initial design dimensions, actual dimensions after each mold repair, actual dimensions before the most recent machine installation, dimensions of the last product after the most recent production, and a timestamp.

6. A forced measurement and error prevention system for molds before machine installation based on timing compliance verification according to claim 2, characterized in that, In step S3, the preset events include mold repair operation, collision alarm and abnormal environment record.

7. A forced measurement and error prevention system for molds before machine installation based on timing compliance verification according to claim 3, characterized in that, In step S2, the trust decay function It is either an exponentially decaying function or a linearly decaying function; When the trust decay function is an exponential decay function: ； When the trust decay function is a linear decay function: ； In the formula, and Both represent the attenuation coefficient.

8. A forced measurement and error prevention system for molds before machine installation based on timing compliance verification according to claim 2, characterized in that, In step S4, the expiration management of the temporary authorization code includes: Validity period settings: Configure different validity periods based on production cycle time and mold turnover speed; Expiration determination: When scanning the temporary authorization code to unlock, the current time is compared with the time the temporary authorization code was generated in real time. If the expiration date has passed, it is determined to be expired, the unlocking operation is refused, and a prompt is made to re-verify the compliance. Dynamic adjustment: The validity period parameter is optimized by self-learning based on historical data.

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