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CN-121722087-B - Multi-module collaborative integration method based on intelligent factory management and control system

CN121722087BCN 121722087 BCN121722087 BCN 121722087BCN-121722087-B

Abstract

The invention discloses a multi-module collaborative integration method based on an intelligent factory management and control system, in particular relates to the technical field of intelligent manufacturing, and aims to solve the problem of inconsistent cross-module control caused by the fact that an interface receipt is not equivalent to an actual state in the prior art. The method comprises the steps of receiving control intention, generating a cooperative control transaction risk index, packaging the cooperative control transaction risk index into a control transaction recording unit, distributing unique identification and an idempotent key, issuing a control instruction after executing cross-module consistency check, collecting preparation receipt and acceptance receipt, entering a verification state to be validated, constructing an execution validation evidence chain based on equipment and business state evidence in an allowable validation time window, calculating a control validation confidence index, judging a validation result, executing compensation rollback and consistency recovery on an abnormal validation transaction, and updating an execution reliability image. According to the invention, observable evidence is used for replacing the receipt as a closed-loop basis, so that verifiability, rollability and traceability of cross-module linkage control are improved.

Inventors

  • ZHANG JIAREN

Assignees

  • 上海正项信息科技有限公司

Dates

Publication Date
20260512
Application Date
20260224

Claims (10)

  1. 1. The multi-module collaborative integration method based on the intelligent factory management and control system is characterized by comprising the following steps of: The control method comprises the steps of receiving a control intention, generating a cooperative control transaction risk index, packaging the control intention into a control transaction request unit, distributing a unique control transaction identifier for the control transaction request unit, and generating an idempotent key; Executing cross-module consistency check based on the control transaction record unit, initiating consistency preparation, and converging preparation receipt returned by each module; after the consistency preparation meets the preset conditions, issuing a control instruction, collecting acceptance receipts returned by each module, and transferring the control transaction state to a verification state to be validated; In the permission validation time window, an execution validation evidence chain which is bound with the control transaction identifier is constructed based on state change evidence collected from the equipment side and the service side, a control validation confidence index is calculated according to the execution validation evidence chain, and a validation result of the control transaction is judged based on the control validation confidence index; And executing the compensation rollback and consistency recovery operation on the control transaction judged to be abnormal in efficiency based on the control transaction recording unit and the effective deviation type, and updating the execution reliability portrait.
  2. 2. The method of claim 1, wherein the generating the collaborative control transaction risk index is based on at least statistics of historical control transaction files matched with the current control type and the target object identifier, and the statistics are calculated in combination with recent statistics in the execution reliability portrait, the recent statistics include at least a consistency preparation failure rate, an effectiveness anomaly rate, a split statistics of effectiveness delay distribution, and a compensation cost statistics, and the link and execution end reachability states acquired in real time are further corrected.
  3. 3. The method of claim 1, wherein the idempotent keys are generated by combining target object identification, control type, expected effective state and control trigger time slices for identifying and combining identical control intents under repeated triggering or repeated delivery conditions.
  4. 4. The multi-module collaborative integration method based on the intelligent factory control system, which is disclosed by claim 1, is characterized by comprising the steps of checking cross-module consistency and initiating consistency preparation, specifically comprising the steps of analyzing and obtaining an associated object set of the linkage control according to a control type and a target object identifier, initiating a consistency preparation request to a manufacturing execution system MES, an equipment state monitoring system, an energy consumption management system and a quality tracing system, wherein the consistency preparation request at least carries a control transaction identifier, the target object identifier, the control type and an expected effective state, converging preparation returns returned by all modules, and transferring the control transaction state to be submittable when all the preparation returns corresponding to the associated object set represent preparation success.
  5. 5. The multi-module collaborative integration method based on the intelligent factory control system is characterized by comprising the steps of constructing an execution validation evidence chain, acquiring equipment side state change evidence from an equipment state monitoring system and acquiring service side state change evidence from a Manufacturing Execution System (MES), a quality tracing system and an energy consumption management system in an allowed validation time window according to an execution validation evidence rule corresponding to a desired validation state loading of a control type, generating an execution validation evidence recording unit and forming an execution validation evidence chain bound with a control transaction identifier according to time sequence after object consistency matching, time window constraint and direction consistency verification of the acquired evidence.
  6. 6. The method of claim 1, wherein the validation confidence index is controlled to be calculated based on at least evidence coverage, evidence consistency score and validation delay normalization amount, wherein the evidence coverage is determined based on the proportion of the number of objects for which the execution validation evidence meeting the evidence condition is obtained in the total number of objects in the associated object set.
  7. 7. The method of claim 1, wherein when performing a rollback and consistency recovery operation on a control transaction determined to be abnormal in efficiency, selecting a corresponding rollback compensation path based on an effective deviation type, the effective deviation type including at least submitting non-effective, partially effective, super window effective, and receipt and evidence inconsistent.
  8. 8. The method of claim 1, wherein updating the execution reliability representation comprises incorporating the preparation result, validation delay and compensation cost data of the current control transaction into statistics according to equipment, production line, control type and link dimensions to roll update consistency preparation failure rate, validation anomaly rate, validation delay distribution high-ranking statistics and compensation cost statistics.
  9. 9. The method of claim 1, wherein the received control intent comprises at least a target object identification, a control type, a desired validation state, and a trigger reason reference, wherein the control type comprises one or more of shutdown, speed reduction, switching of a safe mode, work order suspension, production freeze, batch isolation marking, and energy consumption policy switching.
  10. 10. The multi-module collaborative integration method based on an intelligent factory control system of claim 1, wherein the method is performed by the intelligent factory control system and is collaborative interacted with a manufacturing execution system MES, an equipment status monitoring system, an energy consumption management system and a quality traceability system.

Description

Multi-module collaborative integration method based on intelligent factory management and control system Technical Field The invention relates to the technical field of intelligent manufacturing, in particular to a multi-module collaborative integration method based on an intelligent factory management and control system. Background In an intelligent factory scene, field control is often not triggered by actions of a single equipment layer, but a control side generates a control intention after identifying production abnormality, energy consumption abnormality, quality risk or equipment safety risk, and accordingly drives a cross-system and cross-object linkage control process. The control intention is usually directed to the controlled equipment object and the associated business object at the same time, and the type and expected effective state are required to be explicitly controlled so as to enable equipment side actions such as shutdown, speed reduction, safety mode switching and the like to be landed in cooperation with business side actions such as work order suspension, production freezing, batch isolation marking, energy consumption strategy switching and the like, thereby realizing consistent production state convergence and risk suppression. When the prior intelligent factory control system implements the linkage control, control instructions are respectively issued to modules such as a manufacturing execution system, a device side control link and the like through interface call or a message bus, and flow state migration and alarm closed-loop record are pushed after each module returns to accept a receipt. However, such receipts are often used to prove that an instruction has been received and entered into an internal process flow, which is not equivalent to the expected validation state having been actually achieved at the physical or business layer, and under conditions of network jitter, interface queuing, asynchronous execution within the module, etc., situations are likely to occur in which the receipt has arrived but is not actually validated or the validation delay exceeds the allowed time window. When the system directly uses the receipt as the control closed loop completion basis, the state judgment of the management and control side is possibly disjointed with the real state of the field, and the deviation risk of the cross-module is further amplified, for example, inconsistent states such as frozen work orders on the business side but not shutdown on the equipment side, marked work orders to be isolated but continuous execution of work orders still exist on the batch side, and further, the follow-up scheduling decision, risk disposal and audit tracing are affected. The present invention proposes a solution to the above-mentioned problems. Disclosure of Invention In order to overcome the above-mentioned drawbacks of the prior art, embodiments of the present invention provide a multi-module collaborative integration method based on an intelligent factory control system to solve the problems set forth in the background art. In order to achieve the above purpose, the present invention provides the following technical solutions: a multi-module collaborative integration method based on an intelligent factory management and control system comprises the following steps: The control method comprises the steps of receiving a control intention, generating a cooperative control transaction risk index, packaging the control intention into a control transaction request unit, distributing a unique control transaction identifier for the control transaction request unit, and generating an idempotent key; Executing cross-module consistency check based on the control transaction record unit, initiating consistency preparation, and converging preparation receipt returned by each module; after the consistency preparation meets the preset conditions, issuing a control instruction, collecting acceptance receipts returned by each module, and transferring the control transaction state to a verification state to be validated; In the permission validation time window, an execution validation evidence chain which is bound with the control transaction identifier is constructed based on state change evidence collected from the equipment side and the service side, a control validation confidence index is calculated according to the execution validation evidence chain, and a validation result of the control transaction is judged based on the control validation confidence index; And executing the compensation rollback and consistency recovery operation on the control transaction judged to be abnormal in efficiency based on the control transaction recording unit and the effective deviation type, and updating the execution reliability portrait. In a preferred embodiment, when generating the cooperative control transaction risk index, calculating based on at least the statistical result of the historical control transac