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CN-121998590-A - Equipment maintenance cost management and control system and method

CN121998590ACN 121998590 ACN121998590 ACN 121998590ACN-121998590-A

Abstract

The invention discloses a system and a method for managing and controlling equipment maintenance cost, and relates to the technical field of industrial equipment management. The system comprises an Internet of things data sensing layer, a maintenance digital twin body construction module, a multidimensional dynamic preventive maintenance cost prediction engine, a cost control and execution layer based on intelligent contracts and a self-adaptive cost allocation and optimization feedback loop, and the method comprises the steps of collecting data in real time and constructing an equipment maintenance digital twin body, enabling the prediction engine to generate a virtual maintenance unit containing the predicted cost based on the twin body data, automatically triggering a blockchain intelligent contract when the risk exceeds a threshold value, automatically and traceably controlling budget, flow and payment, automatically allocating the cost after maintenance is completed, and feeding back the data to optimize a model. The method realizes the transition from passive response to active prediction, recording after the operation and automatic control of the whole process of maintenance cost, ensures transparency through intelligent contracts, forms a self-optimizing closed loop and improves the refinement level and cost effectiveness of the cost control.

Inventors

  • LI RUI

Assignees

  • 广东万能工科技有限公司

Dates

Publication Date
20260508
Application Date
20260128

Claims (10)

  1. 1. An equipment maintenance expense management and control system, comprising: the data perception layer of the Internet of things is used for collecting running state data of the equipment in real time; The maintenance digital twin body construction module is used for creating and dynamically updating a maintenance digital twin body integrating the static file, the real-time operation data and the historical maintenance record for the equipment; A multidimensional dynamic preventive maintenance expense prediction engine connected with the maintenance digital twin body construction module and used for predicting equipment fault risks and generating a virtual maintenance unit containing a predicted expense interval based on a multidimensional time sequence data stream of the maintenance digital twin body; The cost management and execution layer is deployed on the blockchain network and is used for automatically creating and executing the maintenance intelligent contract in response to the risk overrun of the virtual maintenance unit so as to automatically manage and control maintenance budget, flow nodes and payment conditions; and the self-adaptive cost allocation and optimization feedback loop is used for automatically allocating the actual cost after the maintenance is completed to a cost object according to a preset rule and feeding back execution result data to the maintenance digital twin body construction module and the multidimensional dynamic preventive maintenance cost prediction engine so as to realize model optimization.
  2. 2. The equipment servicing charge management system of claim 1, wherein the multi-dimensional dynamic preventative maintenance charge prediction engine employs a hybrid neural network model based on a two-way long and short term memory network (LSTM) fused with a Transformer architecture.
  3. 3. The equipment maintenance expense control system according to claim 1, wherein the virtual maintenance unit comprises at least a predicted failure mode, a recommended maintenance strategy, a required parts list, a predicted man-hour, a recommended service provider list, and a predicted expense interval.
  4. 4. The equipment maintenance expense control system according to claim 1, wherein in the intelligent contract-based expense control and execution layer, the execution logic of the maintenance intelligent contract comprises automatically locking a predicted expense upper limit to a budget, recording maintenance key node information in a blockchain, and automatically comparing an actual settlement expense with the predicted expense interval to trigger a payment or audit process.
  5. 5. The equipment maintenance expense control system according to claim 1, wherein the preset rule is to allocate expenses according to the actual operating man-hour ratio of the equipment on a specific production order or product in the adaptive expense allocation and optimization feedback loop.
  6. 6. The equipment servicing expense management system of any of claims 1-5, wherein the multi-dimensional dynamic preventative maintenance expense prediction engine is further configured to perform expense coupling analysis to evaluate a synergistic or conflicting expense impact of a virtual servicing unit for a target equipment on an associated equipment servicing plan.
  7. 7. An equipment maintenance cost management and control method applied to the equipment maintenance cost management and control system according to any one of claims 1 to 6, wherein the method comprises: acquiring running state data of equipment in real time through an Internet of things data perception layer; Constructing and dynamically updating a maintenance digital twin body of the equipment; generating, by a multi-dimensional dynamic preventative maintenance expense prediction engine, a virtual maintenance unit comprising a predicted expense interval based on the data of the maintenance digital twin; when the risk evaluation value of the virtual maintenance unit exceeds a preset threshold value, automatically triggering and executing a maintenance intelligent contract bound with the virtual maintenance unit so as to automatically control maintenance flow and cost; After maintenance is completed, the cost sharing is completed through the self-adaptive cost sharing and optimizing feedback loop, and actual data is fed back to the system to optimize the prediction model.
  8. 8. The method of claim 7, wherein the step of generating a virtual repair unit includes outputting a device-level risk representation and performing a fee-coupling analysis on the predicted repair activity.
  9. 9. The method of claim 7, wherein the step of executing the maintenance intelligence contract includes automatically initiating a price inquiry or bid to a service provider, recording key actions in the maintenance process in the blockchain, and automatically verifying that actual costs and material consumption meet a contract agreement.
  10. 10. The method of claim 7, further comprising performing global simulation and optimization adjustments to the preventative maintenance strategy threshold, spare part inventory strategy, and service provider valuation hierarchy based on the historical maintenance data and the cost data on a periodic basis.

Description

Equipment maintenance cost management and control system and method Technical Field The invention relates to the technical field of industrial equipment management, in particular to an equipment maintenance cost management and control system and method. Background In large industrial enterprises, infrastructure operations and equipment intensive service areas, equipment maintenance costs are a core component of the operational costs, which effectively govern economic benefits and competitiveness directly related to the enterprise. Traditional equipment maintenance cost management relies primarily on post-mortem reimbursement, periodic budget approval, and fixed-cycle based preventative maintenance planning. The mode has the following remarkable defects: First, management has severe hysteresis and passivity. The cost is advanced, the record analysis is later, and the pre-warning and the in-process intervention of the potential high maintenance expenditure cannot be carried out. The mainstream "repair after failure" mode often results in production interruption and overflow costs from emergency repair. However, preventive maintenance based on a fixed time or a running period often causes failure due to insufficient maintenance or excessive maintenance, which is caused by failure to accurately sense the actual health state of the equipment. Second, data isolation results in decision-making faceting. Equipment operational status data, repair order records, spare part inventory information, vendor contracts, and financial payment data are typically dispersed in different informative systems or paper files to form "data islands". The management layer has difficulty in obtaining a global and associated view, cannot perform collaborative optimization analysis between maintenance strategies and costs, and is dependent on experience rather than data driving. Further, the cost is due to rough apportionment. Maintenance costs are usually simply counted into departments or workshops and cannot be traced precisely to the specific equipment monomer, production lot or product item that caused the cost, which is not conducive to developing fine cost accounting, product pricing and performance assessment. In recent years, there have been attempts to use Computerized Maintenance Management Systems (CMMS) or Enterprise Asset Management Systems (EAMs) for informationized management, but these systems have focused on worksheet process electronization and asset information recording, and have not essentially broken through the above-mentioned framework. The prediction function is mostly based on a simple statistical model, the precision is limited, the cost control still depends on a manual approval process, the transparency and rigidity constraint are insufficient, and the data flow can not realize end-to-end automatic closed loop from the physical equipment state to the financial cost settlement. Based on the above, the present invention provides a system and a method for controlling equipment maintenance cost to solve the above-mentioned problems. Disclosure of Invention In order to overcome the above-mentioned drawbacks of the prior art, the present invention provides a system and a method for controlling equipment maintenance cost, so as to solve the above-mentioned problems in the prior art. The invention provides a device maintenance cost management and control system, which comprises the following technical scheme: the data perception layer of the Internet of things is used for collecting running state data of the equipment in real time; The maintenance digital twin body construction module is used for creating and dynamically updating a maintenance digital twin body integrating the static file, the real-time operation data and the historical maintenance record for the equipment; A multidimensional dynamic preventive maintenance expense prediction engine connected with the maintenance digital twin body construction module and used for predicting equipment fault risks and generating a virtual maintenance unit containing a predicted expense interval based on a multidimensional time sequence data stream of the maintenance digital twin body; The cost management and execution layer is deployed on the blockchain network and is used for automatically creating and executing the maintenance intelligent contract in response to the risk overrun of the virtual maintenance unit so as to automatically manage and control maintenance budget, flow nodes and payment conditions; and the self-adaptive cost allocation and optimization feedback loop is used for automatically allocating the actual cost after the maintenance is completed to a cost object according to a preset rule and feeding back execution result data to the maintenance digital twin body construction module and the multidimensional dynamic preventive maintenance cost prediction engine so as to realize model optimization. The multidimensional dynamic preventative maintenance exp