Chemical equipment management system based on FMEA risk analysis

Abstract

The invention relates to an equipment management technology, and provides a chemical equipment management system based on FMEA risk analysis, which comprises an equipment information management unit used for carrying out detailed input and storage on basic information, technical parameters, purchase information, installation and debugging records and the like of equipment; the real-time monitoring and early warning unit is used for collecting equipment operation data, such as key indexes such as temperature, pressure and rotating speed, by means of the Internet of Things technology, and once data abnormity is found, the system can give an alarm immediately; and the FMEA risk analysis unit constructs an equipment failure mode library, dynamically calculates a risk priority number (RPN = severity * occurrence frequency * detection difficulty), and outputs a high-risk equipment list. A maintenance window is intelligently planned through a series equipment group co-stop period identification and synchronous maintenance set mechanism. By accurately judging the shutdown time period of the equipment group, the equipment of which the RPN value is higher than 100 is included in the synchronous maintenance category, so that the utilization rate of a local maintenance window is greatly improved.

Description

Technical Field

[0001] The present invention relates to equipment management technology, in particular to a chemical equipment management system based on FMEA risk analysis. Background Art

[0002] The chemical equipment management system is a critical information technology tool for chemical companies to ensure efficient and safe production operations. It digitally integrates the management of chemical equipment throughout its entire lifecycle, from procurement to decommissioning. During the equipment procurement phase, the system helps companies identify suitable suppliers, compare key factors such as performance and price, and ensure that they purchase equipment that meets production needs and offers the best value for money. It also provides detailed records of purchase contracts, delivery inspections, and other related information. During equipment installation and commissioning, the system tracks installation progress and records commissioning parameters for easy retrospective review. Once operational, real-time monitoring functions play a vital role. Through various sensors and network connectivity, it continuously collects equipment operating parameters such as liquid level, flow rate, and pressure. If data exceeds normal ranges, it immediately issues an alert, enabling maintenance personnel to respond promptly and prevent escalating faults from impacting production. Regarding maintenance, intelligent maintenance plans are generated based on information such as equipment operating time and past failures, allowing for precise scheduling of repair tasks. The system also provides a complete record of the maintenance process for easy experience sharing. In spare parts management, real-time monitoring of spare parts inventory quantities and inbound and outbound activity allows for the proper setting of inventory warning thresholds to ensure sufficient spare parts for timely replacement, minimizing equipment downtime. Furthermore, the system boasts powerful data analysis capabilities, generating various reports that intuitively display comprehensive equipment status. This provides robust data support for optimizing equipment configurations and developing update strategies, comprehensively improving equipment management and production efficiency for chemical companies.

[0003] Chemical equipment management systems are core tools for ensuring production safety, but traditional solutions suffer from numerous shortcomings. Relying on threshold alarm mechanisms within DCS systems, traditional solutions can only respond passively to limit violations and lack risk prediction capabilities. Furthermore, firefighting facility management relies on manual scheduling, resulting in delayed emergency response. Consequently, existing technologies suffer from three major flaws: extensive maintenance strategies, static risk analysis, and fragmented data from multiple sources. These issues lead to frequent production line interruptions, an inability to dynamically monitor equipment status, and a high rate of false alarms, making them unable to meet the stringent real-time and interconnected requirements of chemical production. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention provides a chemical equipment management system based on FMEA risk analysis, which solves the problems of frequent production line interruptions, inability to dynamically monitor equipment status, and high false alarm rate.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: A chemical equipment management system based on FMEA risk analysis, comprising: Equipment information management unit, used to enter and store detailed information about the equipment, including basic information, technical parameters, procurement information, installation and commissioning records, etc. Real-time monitoring and early warning unit, which uses IoT technology to collect equipment operating data, such as temperature, pressure, speed and other key indicators. Once abnormal data is detected, the system will immediately issue an alarm; FMEA risk analysis unit builds an equipment failure mode library, dynamically calculates the risk priority number (RPN = severity × frequency of occurrence × difficulty of detection), and outputs a list of high-risk equipment; Maintenance optimization decision-making unit, which generates hierarchical maintenance strategies based on RPN values ​​and synchronizes downtime periods for associated equipment groups to minimize production interruptions; Multi-source data fusion unit, integrating process parameters, electrical data and video monitoring information, and correlating failure mode characteristics; The maintenance evaluation unit calculates the error impact index based on the operation time and downtime, and then outputs the effect evaluation coefficient based on the maintenance task volume to evaluate the effectiveness of the maintenance work; The emergency linkage unit matches the emergency plan based on the failure mode and links the fire-fighting facilities to locate them.

[0006] Preferably, the FMEA risk analysis unit includes: Failure mode library associates equipment type, material characteristics and environmental parameters; Dynamic update module to adjust the occurrence frequency score based on real-time monitoring data.

[0007] Preferably, the maintenance optimization decision unit includes: Identify the common outage periods of the series equipment group and include equipment with RPN>100 in the synchronous maintenance set; Based on the maintenance complexity formula Assign task duration ( is the complexity weight).

[0008] Preferably, the generation logic of the synchronization maintenance set is: Compare the downtime period of the equipment group with the estimated maintenance duration; If the maintenance duration exceeds the downtime period, the device group is split into independent collections.

[0009] Preferably, the real-time monitoring and early warning unit includes: The video analysis sub-module identifies illegal operations by personnel or the accumulation of dangerous goods, and initiates emergency warnings.

[0010] Preferably, the multi-source data fusion unit includes: The mathematical analysis model matches the accident precursor conditions to input process parameters, electrical data and video features; the accident type and emergency measures index are output.

[0011] Preferably, the emergency linkage unit performs: Locate the nearest fire-fighting facilities based on the equipment location; Push customized emergency plans based on the failure mode library.

[0012] Preferably, the maintenance evaluation unit includes: Based on operation time and downtime Calculating impact indicators ; Combined with the maintenance workload Output effect evaluation coefficient .

[0013] Preferably, the device information management unit includes: Integrate procurement, installation, and commissioning data, and associate RPN values ​​to generate equipment lifecycle reports.

[0014] Preferably, the risk level is divided by dynamic RPN thresholds: RPN ≥ 150: immediate shutdown for maintenance; 100 ≤ RPN < 150: simultaneous maintenance during the common shutdown period; RPN < 100: postponement to the planned maintenance window.

[0015] The present invention provides a chemical equipment management system based on FMEA risk analysis. It has the following beneficial effects: 1. This invention intelligently plans maintenance windows by identifying the common downtime periods of tandem equipment groups and integrating them into a synchronous maintenance aggregation mechanism. By accurately determining the downtime periods of equipment groups, devices with RPN values ​​above 100 are included in the synchronous maintenance scope, significantly improving the utilization of local maintenance windows.

[0016] 2. This invention utilizes the FMEA risk analysis unit to dynamically update RPN frequency scores. This allows for timely adjustments to equipment failure mode probabilities based on real-time equipment operational data, significantly improving the accuracy of identifying high-risk equipment. Furthermore, by combining the maintenance complexity formula to allocate task durations, this allows for precise scheduling of maintenance resources.

[0017] 3. This invention integrates process parameters, electrical data, and video surveillance information through a multi-source data fusion module. By linking video events with a failure mode library, the system effectively reduces the system's false alarm rate. The emergency linkage unit automatically locates the nearest firefighting facility based on the equipment's location and, in conjunction with the failure mode library, delivers customized emergency plans, significantly shortening emergency response time. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a unit module diagram of the present invention; Figure 2 It is the workflow diagram of the present invention. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0020] Example: As one aspect of the present invention, please refer to the attached Figure 1 The embodiment of the present invention provides a chemical equipment management system based on FMEA risk analysis, including: The equipment information management unit is used to record and store detailed basic equipment information (including equipment number, model specifications, design parameters, etc.), technical parameters (key indicators such as material, power, and capacity), procurement information (including supplier information, contract number, procurement date, and cost), and installation and commissioning records (including installation location, commissioning parameters, and acceptance reports). By integrating procurement, installation, and commissioning data throughout the equipment's lifecycle and linking it with the real-time RPN value (Risk Priority Number) output by the FMEA risk analysis unit, a complete equipment lifecycle report is automatically generated, including the equipment's static attributes, dynamic operating status, and risk level assessment. This report intuitively displays data from the entire equipment process, from procurement and installation to operation and maintenance, and provides data support for maintenance decisions. The real-time monitoring and early warning unit uses IoT technology to collect equipment operating data (including key indicators such as temperature, pressure, and speed) in real time, and integrates process parameters, electrical data, and video monitoring features through a multi-source data fusion platform. The system uses intelligent mathematical analysis models to analyze the collected data in real time. Once data anomalies are detected or match preset accident precursor conditions, a graded early warning mechanism is immediately triggered, and the corresponding accident type diagnosis results and emergency response index are output to provide decision support for rapid response. This unit realizes the full process automation from data collection and anomaly detection to intelligent early warning, significantly improving the accuracy of equipment monitoring and the efficiency of emergency response. The FMEA risk analysis unit builds an equipment failure mode library that deeply correlates key factors such as equipment type, material characteristics, and environmental parameters. It achieves precise risk assessment by dynamically calculating the risk priority number (RPN = severity × frequency of occurrence × difficulty of detection). The system is equipped with an intelligent dynamic update module that automatically adjusts the frequency of occurrence score based on real-time monitoring data, ensuring that the RPN value is updated in real time with the equipment's operating status. Ultimately, it outputs a list of high-risk equipment that accurately reflects the current risk status. By combining a static failure mode library with a dynamic data update mechanism, this unit achieves real-time and accurate risk warnings, providing a scientific basis for preventive maintenance. The maintenance optimization decision unit generates a hierarchical maintenance strategy based on the RPN value, identifies the common downtime period of the series equipment group through an intelligent algorithm, automatically includes high-risk equipment with RPN>100 into the synchronous maintenance set, and based on the maintenance complexity formula ( ,in The unit accurately allocates the required time for each maintenance task (based on complexity weights). This unit utilizes advanced synchronous maintenance set generation logic, comparing the downtime of a group of equipment with the estimated maintenance duration in real time. When the maintenance duration exceeds the available downtime window, the system automatically splits the equipment group into independent maintenance sets, ensuring that critical equipment maintenance can be completed without impacting production plans, minimizing production interruptions. This intelligent maintenance decision-making mechanism prioritizes high-risk equipment while optimizing the overall efficiency of maintenance resources. The multi-source data fusion unit uses IoT technology to integrate process parameters (such as temperature and pressure), electrical data (such as current and voltage), and video surveillance information (including personnel operating behavior and equipment operating status) in real time, and deeply correlates key indicators in the failure mode feature library. The unit uses an intelligent mathematical analysis model to perform real-time matching analysis on the input multi-dimensional data. When a data feature combination that meets the accident precursor conditions is detected, the system immediately outputs an accurate accident type diagnosis result and a corresponding emergency measure index, including recommended disposal plans, required emergency resources, and priority execution steps, providing decision support for rapid response. This model, which combines multi-source information fusion with intelligent analysis, significantly improves the accuracy of accident warnings and the timeliness of emergency responses, and realizes intelligent processing of the entire process from data collection to decision support. The maintenance evaluation unit calculates the error impact index through an algorithm based on the difference data between the actual operation time of the maintenance personnel and the planned downtime (in is the operation duration, is the downtime, Δt is the allowable delay threshold), and further combined with the maintenance task volume (i.e., the number of synchronized maintenance equipment), using the evaluation coefficient formula , outputs a quantitative maintenance effect evaluation coefficient. By establishing a dual-dimensional evaluation system of operational efficiency and task load, this unit can not only objectively reflect the timeliness of a single maintenance operation, but also comprehensively evaluate the overall work efficiency of maintenance personnel when performing multiple tasks in parallel, providing data support for maintenance team performance appraisal and skills training; The emergency linkage unit intelligently matches the optimal emergency plan based on failure modes and uses IoT technology to precisely locate plant firefighting facilities, enabling rapid emergency response. It also employs a dynamic RPN threshold grading mechanism to categorize equipment risks into three response levels: An RPN ≥ 150 immediately triggers a shutdown maintenance process; 100 ≤ RPN < 150 automatically includes the equipment in the most recent downtime period for simultaneous maintenance; and RPN < 100 intelligently schedules the equipment to a planned maintenance window. By combining emergency plan matching, firefighting resource positioning, and dynamic risk grading, this unit has established a complete closed-loop management system from risk warning to emergency response. This ensures the timely handling of high-risk equipment and optimizes the overall scheduling efficiency of maintenance resources.

[0021] As another aspect of the present invention, please refer to the attached Figure 2 Based on a chemical equipment management system based on FMEA risk analysis, in order to better illustrate the data collection and feedback implementation scheme of the present invention, the following experiment is used as an example: Step 1: Initialize the device information management unit Enter reactor equipment parameters Step 2: Real-time monitoring and early warning unit operation The sensor collects data every 5 seconds and triggers abnormal conditions Step 3: Dynamic calculation of FMEA risk analysis unit When the R-101 pressure rises to 2.3 MPa, the system dynamically updates the RPN Step 4: Maintain and optimize the decision-making unit generation strategy Generate maintenance plan based on RPN value Step 5: Emergency linkage unit response When the video analysis submodule detects that combustibles are illegally stacked next to R-101, the system executes Technical effect verification (compared with traditional solutions) This embodiment quantitatively displays the specific application of the system in equipment management, risk warning and emergency linkage through tables, proving its effectiveness in improving efficiency and reducing costs.

[0022] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A chemical equipment management system based on FMEA risk analysis, characterized in that: include: Equipment information management unit, used to enter and store detailed information about the equipment, including basic information, technical parameters, procurement information, installation and commissioning records, etc. Real-time monitoring and early warning unit, which uses IoT technology to collect equipment operating data, such as temperature, pressure, speed and other key indicators. Once abnormal data is detected, the system will immediately issue an alarm; FMEA risk analysis unit builds an equipment failure mode library, dynamically calculates the risk priority number (RPN = severity × frequency of occurrence × difficulty of detection), and outputs a list of high-risk equipment; Maintenance optimization decision-making unit, which generates hierarchical maintenance strategies based on RPN values ​​and synchronizes downtime periods for associated equipment groups to minimize production interruptions; Multi-source data fusion unit, integrating process parameters, electrical data and video monitoring information, and correlating failure mode characteristics; The maintenance evaluation unit calculates the error impact index based on the operation time and downtime, and then outputs the effect evaluation coefficient based on the maintenance task volume to evaluate the effectiveness of the maintenance work; The emergency linkage unit matches the emergency plan based on the failure mode and links the fire-fighting facilities to locate them.

2. A chemical equipment management system based on FMEA risk analysis according to claim 1, characterized in that: The FMEA risk analysis unit includes: Failure mode library associates equipment type, material characteristics and environmental parameters; Dynamic update module to adjust the occurrence frequency score based on real-time monitoring data.

3. A chemical equipment management system based on FMEA risk analysis according to claim 1, characterized in that: The maintenance optimization decision unit includes: Identify the common outage periods of the series equipment group and include equipment with RPN>100 in the synchronous maintenance set; Based on the maintenance complexity formula Assign task duration ( is the complexity weight).

4. A chemical equipment management system based on FMEA risk analysis according to claim 3, characterized in that: The generation logic of the synchronization maintenance set is: Compare the downtime period of the equipment group with the estimated maintenance duration; If the maintenance duration exceeds the downtime period, the device group is split into independent collections.

5. The chemical equipment management system based on FMEA risk analysis according to claim 1, characterized in that: The real-time monitoring and early warning unit includes: The video analysis sub-module identifies illegal operations by personnel or the accumulation of dangerous goods, and initiates emergency warnings.

6. A chemical equipment management system based on FMEA risk analysis according to claim 1, characterized in that: The multi-source data fusion unit includes: The mathematical analysis model matches the accident precursor conditions to input process parameters, electrical data and video features; the accident type and emergency measures index are output.

7. The chemical equipment management system based on FMEA risk analysis according to claim 1, characterized in that: The emergency linkage unit performs: Locate the nearest fire-fighting facilities based on the equipment location; Push customized emergency plans based on the failure mode library.

8. The chemical equipment management system based on FMEA risk analysis according to claim 1, characterized in that: The maintenance evaluation unit includes: Based on operation time and downtime Calculating impact indicators ; Combined with the maintenance workload Output effect evaluation coefficient .

9. The chemical equipment management system based on FMEA risk analysis according to claim 1, characterized in that: The device information management unit includes: Integrate procurement, installation, and commissioning data, and associate RPN values ​​to generate equipment lifecycle reports.

10. The chemical equipment management system based on FMEA risk analysis according to claim 1, characterized in that: Risk levels are divided by dynamic RPN thresholds. RPN ≥ 150: immediate shutdown for maintenance. 100≤RPN<150: The system will be included in the maintenance during the common downtime period; RPN<100: Defer to the scheduled maintenance window.

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