Intelligent maintenance system based on Internet of Things
The intelligent maintenance system addresses inefficiencies in conventional maintenance practices by optimizing resource allocation and predictive maintenance, enhancing production efficiency and reducing costs through an IoT-based approach.
Patent Information
- Application Number
- CN202411041825.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-07-31
- Publication Date
- 2024-12-24
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
Conventional large-scale regular maintenance practices in fixed asset-intensive enterprises are inflexible, costly, and result in downtime, affecting production efficiency and increasing expenditure, while existing buffer solutions are inadequate in managing equipment maintenance timelines.
An intelligent maintenance system based on the Internet of Things that divides maintenance impact coefficients, establishes an equipment maintenance asset impact model, predicts equipment degradation, and determines preventive maintenance thresholds to optimize resource allocation and reduce maintenance costs.
The system enhances maintenance efficiency, reduces waste, and improves the competitiveness of enterprises by minimizing maintenance costs and ensuring timely equipment maintenance.
Smart Images
Figure CN119180628A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of intelligent maintenance of manufacturing enterprises, and in particular to an intelligent maintenance system based on the Internet of Things. Background Art
[0002] Enterprise asset maintenance has always been a big problem for fixed asset-intensive enterprises. Conventional large-scale regular maintenance practices have problems such as inflexibility, high costs, and the need for downtime. On the one hand, it reduces the efficiency of the enterprise, and on the other hand, it increases the expenditure of the enterprise. In addition, fixed asset-intensive enterprises often use a production system with multiple devices in series. This system will face the phenomenon that when one device is shut down for maintenance, the rest of the devices will also be shut down. Most existing enterprises solve this problem by introducing the concept of buffer, but the capacity of the buffer has a great impact on the system performance of fixed asset-intensive enterprises. When the equipment maintenance cannot be completed in time, the role of the buffer is still small. Moreover, production and maintenance are two important links in the asset maintenance of manufacturing enterprises. When producing products, they need to be maintained to avoid equipment degradation and reduce product quality. When the equipment is maintained, it takes up production time, which leads to reduced production efficiency. Therefore, it is necessary to design a targeted maintenance mode and improve the scalability of maintenance. An intelligent maintenance system based on the Internet of Things is very necessary. Summary of the invention
[0003] The purpose of the present invention is to provide an intelligent maintenance system based on the Internet of Things to solve the problems raised in the above background technology.
[0004] In order to solve the above technical problems, the present invention provides the following technical solutions: an intelligent maintenance method based on the Internet of Things, comprising the following steps: Step 1: For the operation and maintenance of multiple equipment in manufacturing enterprises, divide the maintenance impact coefficient of each equipment on the multi-equipment operation line and establish the equipment maintenance asset impact model brought by the multi-equipment operation line; Step 2: Based on the equipment status distribution of multi-equipment production line time series, develop a status assessment method for equipment preventive maintenance; Step 3: Determine the preventive maintenance of the equipment on the entire production line; Step 4: Determine the threshold for equipment maintenance and the system maintenance time, calculate the maintenance cost for equipment maintenance, and take corresponding maintenance measures.
[0005] According to the above technical solution, the step of establishing the equipment maintenance asset impact model brought about by multiple equipment operation lines includes: Step a1: On a multi-device hybrid production line of a manufacturing enterprise, multi-dimensional time series data of monitoring sensors of each device on the production line is obtained through multiple monitoring sensors; Step a2: Calculate the total maintenance resource consumption of the multi-equipment operation line within a set period based on the equipment impact resources of the production line operation. The equipment impact resources include the operation resources of the equipment on the multi-equipment production line, the production material resources invested, and the time resources invested in operation; Step a3: In the existing multi-equipment serial production system of the manufacturing enterprise, the equipment on the multi-equipment production line is graded according to the difficulty of equipment maintenance. The more difficult the equipment is to maintain, the higher the grade; Step a4: The maintenance resources required for the maintenance of each level of equipment on the production line are also divided, and the maintenance resource requirements corresponding to different equipment are described using the influencing factors of the maintenance level; Step a5: using the divided equipment maintenance resource impact coefficients to divide the equipment maintenance resource demand priorities, the greater the equipment maintenance resource impact coefficient, the higher the maintenance resource demand priority, that is, the greater the equipment maintenance resource demand for this multi-equipment operation line; Step a6: Sort the maintenance resource requirements of all equipment on a multi-equipment production line from high to low. The total amount of maintenance resources invested in each equipment on each production line is limited. The types of maintenance resources required by each equipment on a multi-equipment production line are different, and different equipment has different requirements for the same maintenance resources. The maintenance resources are allocated to different equipment according to the total maintenance resource consumption of the equipment on a production line. Step a7: Select the allocation of equipment maintenance resources for the enterprise production line as the optimization target, build an equipment maintenance asset impact model, and match the model's needs and iterate output according to the maintenance difficulty and maintenance needs of each equipment on the multi-equipment production line.
[0006] According to the above technical solution, the step of providing evaluation data includes: The prediction method based on time series data uses the interval method to predict the degradation trend. The deep neural network model is used in real time to evaluate the working status of the equipment using the input equipment operating time. The equipment's working performance is evaluated through equipment operating status statistics, and evaluation data is provided for preventive maintenance or replacement of the equipment.
[0007] According to the above technical solution, the step of using the assessment data to formulate a condition assessment for equipment preventive maintenance includes: Step b1: Analyze the structure of each component device of the multi-device production line, and convert the input-output relationship between the devices and the importance in the device network into the initial weight of each device; Step b5: Calculate the Mahalanobis distance between the feature data extracted from the real-time monitoring sensor data of the equipment and the feature data set of the ideal health state of the equipment, and construct the health index of the production line equipment by using the comprehensive histogram method; Step b2: The weighted health index of each device is calculated by using the initial weight and performance health index of each device, and the importance of data is distinguished to calculate the importance of health data of each device; Step b3: Set a threshold of data importance and divide the health index of the device into two sets according to the importance threshold; Step b4: Deterministically classify the health status of the equipment that makes up the production line, and classify the equipment health status into four states: healthy, sub-healthy, abnormal, and faulty based on empirical maintenance data.
[0008] According to the above technical solution, the step of performing preventive maintenance determination on the equipment on the entire production line includes: Step c1: Determine the equipment that needs preventive maintenance based on the previous ranking of equipment maintenance resource demand priorities and preventive maintenance thresholds; Step c2: List all equipment that requires preventive maintenance, sort them by maintenance resource requirement priority, and select the equipment with the lowest maintenance priority as the standard for preventive maintenance; Step c3: Determine the equipment that needs preventive maintenance, and determine the equipment that needs preventive maintenance according to the maintenance resource demand degree and preventive maintenance value of the equipment on the multi-equipment production line within the selected time period; Step c4: When the maintenance resource requirement of the equipment is less than or equal to the preventive maintenance threshold, the equipment is set to require preventive maintenance; when the maintenance difficulty of the equipment is greater than the preventive maintenance threshold, the equipment is set to perform direct maintenance.
[0009] According to the above technical solution, the method steps of calculating the maintenance cost for equipment maintenance and taking corresponding maintenance measures include: Step d1: setting the preventive maintenance threshold of the multi-equipment production line as a whole, the preventive maintenance threshold of each equipment on the production line, and the maintenance threshold of the production line as a whole and the maintenance threshold of each equipment on the production line; Step d2: In the same time period, the time when all equipment on the production line starts running is used as the starting point for calculating the maintenance cost of the production line and equipment. The equipment that needs preventive maintenance is determined based on the maintenance difficulty and preventive maintenance threshold of the equipment. The maintenance cost consumed during the overall maintenance and the preventive maintenance cost in the corresponding time period are analyzed to calculate the maintenance cost. Step d3: Establish a mathematical model with the overall maintenance cost as the target, output the maintenance plan corresponding to the set maintenance threshold and the total maintenance cost of the entire time period. When the difference between the preventive maintenance threshold and the maintenance threshold is too large, the maintenance cost of the production line is high, and when the preventive maintenance threshold is small; Step d4: setting a threshold for the health index of the multi-equipment production line, and setting a preventive maintenance judgment for the production line and equipment when the health index of the multi-equipment production line reaches the threshold; Step d5: When the preventive maintenance action of the production line is triggered, it is determined whether the equipment in the production line has reached the preventive maintenance threshold and the maintenance threshold. The equipment that has reached the maintenance threshold is subjected to joint maintenance, that is, the production line is shut down for maintenance, and maintenance measures are taken for all equipment that meets the maintenance conditions on the multi-equipment production line; Step d6: When the health index of a multi-equipment production line does not reach the maintenance threshold, but a certain equipment in the multi-equipment production line reaches the preventive maintenance threshold, preventive maintenance measures are taken for the equipment. The maintenance measures are determined by the replacement threshold of the equipment to be maintained. Equipment below the equipment replacement threshold is replaced, and other equipment is repaired.
[0010] According to the above technical solution, the intelligent maintenance system includes: Equipment maintenance model module, used to establish equipment maintenance asset impact model brought by multiple equipment operation lines; Preventive maintenance module, used to develop condition assessment methods for equipment preventive maintenance; The maintenance cost analysis calculation module is used to calculate the maintenance cost for equipment maintenance.
[0011] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention, by dividing the maintenance impact coefficient of each device on a multi-device operation line, establishes an equipment maintenance asset impact model brought about by a multi-device operation line, determines the threshold for equipment maintenance and the maintenance time of the system, calculates the maintenance cost for equipment maintenance, and establishes a model with the goal of reducing the system maintenance cost, which can enhance the competitiveness of the enterprise. With the goal of minimizing the total maintenance cost of a multi-equipment production line, a production line preventive maintenance model is established, which effectively improves the maintenance rate of the equipment and reduces the waste of startup costs caused by frequent startup maintenance actions. BRIEF DESCRIPTION OF THE DRAWINGS
[0012] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 A flowchart of an intelligent maintenance method based on the Internet of Things provided in Embodiment 1 of the present invention; Figure 2 A schematic diagram of the module composition of an intelligent maintenance system based on the Internet of Things provided in Embodiment 2 of the present invention. DETAILED DESCRIPTION
[0013] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.
[0014] Embodiment 1: Figure 1 This is a flowchart of an intelligent maintenance method based on the Internet of Things provided in Example 1 of the present invention. This embodiment can be applied to the targeted and scalable intelligent maintenance scenarios of enterprise equipment and assets. The method can be executed by an intelligent maintenance system based on the Internet of Things provided in this embodiment, such as Figure 1 As shown, the method specifically comprises the following steps: Step 1: For the operation and maintenance of multiple equipment in manufacturing enterprises, divide the maintenance impact coefficient of each equipment on the multi-equipment operation line and establish the equipment maintenance asset impact model brought by the multi-equipment operation line; In the embodiment of the present invention, the method for dividing the maintenance impact coefficient of each device on the multi-device operation line and establishing the device maintenance asset impact model brought by the multi-device operation line is as follows: Step a1: On a multi-device hybrid production line of a manufacturing enterprise, multi-dimensional time series data of monitoring sensors of each device on the production line is obtained through multiple monitoring sensors; Step a2: Calculate the total maintenance resource consumption of the multi-equipment operation line within a set period based on the equipment impact resources of the production line operation. The equipment impact resources include the operation resources of the equipment on the multi-equipment production line, the production material resources invested, and the time resources invested in operation; Step a3: In the existing multi-equipment serial production system of the manufacturing enterprise, the equipment on the multi-equipment production line is graded according to the difficulty of equipment maintenance. The more difficult the equipment is to maintain, the higher the grade; Step a4: The maintenance resources required for the maintenance of each level of equipment on the production line are also divided, and the maintenance resource requirements corresponding to different equipment are described using the influencing factors of the maintenance level; Step a5: using the divided equipment maintenance resource impact coefficients to divide the equipment maintenance resource demand priorities. The larger the equipment maintenance resource impact coefficient, the higher the maintenance resource demand priority, that is, the greater the maintenance resource demand of the equipment for this multi-equipment operation line; Step a6: Sort the maintenance resource requirements of all equipment on a multi-equipment production line from high to low. The total amount of maintenance resources invested in each equipment on each production line is limited. The types of maintenance resources required by each equipment on a multi-equipment production line are different, and different equipment has different requirements for the same maintenance resources. The maintenance resources are allocated to different equipment according to the total maintenance resource consumption of the equipment on a production line. Step a7: Select the allocation of equipment maintenance resources for the enterprise production line as the optimization target, build an equipment maintenance asset impact model, and match the model's needs and iterate output according to the maintenance difficulty and maintenance needs of each equipment on the multi-equipment production line.
[0015] Step 2: Based on the equipment status distribution of multi-equipment production line time series, develop a status assessment method for equipment preventive maintenance; In the embodiment of the present invention, the prediction method based on time series data uses an interval method to predict the degradation trend. When the equipment is working, due to its aging or wear, its action time will become longer. The input equipment operation time is used to evaluate the working status of the equipment in real time using a deep neural network model. The working performance of the equipment is evaluated through equipment operation status statistics, and evaluation data is provided for preventive maintenance or replacement of the equipment. Exemplarily, the condition assessment method for equipment preventive maintenance is formulated using the assessment data as follows: Step b1: Analyze the structure of each component device of the multi-device production line, and convert the input-output relationship between the devices and the importance in the device network into the initial weight of each device; Step b5: Calculate the Mahalanobis distance between the feature data extracted from the real-time monitoring sensor data of the equipment and the feature data set of the ideal health state of the equipment, measure the degree of deviation of the current state of the equipment from the ideal state through the distance algorithm, and construct the health index of the production line equipment by the comprehensive histogram method. Use the distance algorithm to measure the difference in space, plane and set, and realize the real-time health status evaluation of all equipment in the production line; Step b2: The weighted health index of each device is calculated by using the initial weight and performance health index of each device, and the importance of data is distinguished to calculate the importance of health data of each device; Step b3: Set a threshold for data importance, and divide the health index of the equipment into two sets according to the importance threshold. The first set is a set with high importance, which represents a part of data with low redundancy. The importance data of the equipment with the worst health status corresponding to the minimum value in the set is taken as the fusion value of the set. The second set is a set with low importance, which reflects the overall health status of the multi-equipment production line. The health index of the entire production line is obtained by the fusion value of the two sets. Step b4: Determine the health status of the equipment in the production line and classify it into four states: healthy, sub-healthy, abnormal and faulty based on empirical maintenance data. The health status of the equipment is only a qualitative result. In order to conduct a more detailed health assessment of the equipment, the health level of the equipment needs to be quantified.
[0016] Step 3: Determine the preventive maintenance of the equipment on the entire production line; In an embodiment of the present invention, the method for determining whether to perform preventive maintenance on the equipment on the entire production line is as follows: Step c1: Determine the equipment that needs preventive maintenance based on the previous ranking of equipment maintenance resource demand priorities and preventive maintenance thresholds; Step c2: List all equipment that requires preventive maintenance, sort them by maintenance resource requirement priority, and select the equipment with the lowest maintenance priority as the standard for preventive maintenance; Step c3: Determine the equipment that needs preventive maintenance, and determine the equipment that needs preventive maintenance according to the maintenance resource demand degree and preventive maintenance value of the equipment on the multi-equipment production line within the selected time period; Step c4: When the maintenance resource requirement of the equipment is less than or equal to the preventive maintenance threshold, the equipment is set to require preventive maintenance; when the maintenance difficulty of the equipment is greater than the preventive maintenance threshold, the equipment is set to perform direct maintenance.
[0017] Step 4: Determine the threshold for equipment maintenance and the system maintenance time, calculate the maintenance cost for equipment maintenance, and establish a mathematical model with the overall maintenance cost as the target; In an embodiment of the present invention, the method for calculating the maintenance cost for equipment maintenance is: Step d1: setting the preventive maintenance threshold of the multi-equipment production line as a whole, the preventive maintenance threshold of each equipment on the production line, and the maintenance threshold of the production line as a whole and the maintenance threshold of each equipment on the production line; Step d2: In the same time period, the time when all equipment on the production line starts running is used as the starting point for calculating the maintenance cost of the production line and equipment. The equipment that needs preventive maintenance is determined based on the maintenance difficulty and preventive maintenance threshold of the equipment. The maintenance cost consumed during the overall maintenance and the preventive maintenance cost in the corresponding time period are analyzed to calculate the maintenance cost. Step d3: Establish a mathematical model with the overall maintenance cost as the target, output the maintenance plan corresponding to the set maintenance threshold and the total maintenance cost of the entire time period. When the difference between the preventive maintenance threshold and the maintenance threshold is too large, the maintenance cost of the production line is high. When the preventive maintenance threshold is small, the maintenance times of the multi-equipment production line will be reduced, and the accuracy and stability of the equipment will decrease, which will lead to an increase in the cost of a maintenance. Step d4: Therefore, a threshold is set for the health index of the multi-equipment production line, and when the health index of the multi-equipment production line reaches the threshold, a preventive maintenance judgment of the production line and the equipment is made; Step d5: When the preventive maintenance action of the production line is triggered, it is determined whether the equipment in the production line has reached the preventive maintenance threshold and the maintenance threshold. The equipment that has reached the maintenance threshold is subjected to joint maintenance, that is, the production line is shut down for maintenance, and maintenance measures are taken for all equipment that meets the maintenance conditions on the multi-equipment production line; Step d6: When the health index of a multi-equipment production line does not reach the maintenance threshold, but a certain equipment in the multi-equipment production line reaches the preventive maintenance threshold, preventive maintenance measures are taken for the equipment. The maintenance measures are determined by the replacement threshold of the equipment to be maintained. Equipment below the equipment replacement threshold is replaced, and other equipment is repaired.
[0018] Embodiment 2: Embodiment 2 of the present invention provides an intelligent maintenance system based on the Internet of Things. Figure 2 A schematic diagram of the module composition of an intelligent maintenance system based on the Internet of Things provided in the second embodiment of the present invention is shown in FIG. Figure 2 As shown, the system includes: Equipment maintenance model module, used to establish equipment maintenance asset impact model brought by multiple equipment operation lines; Preventive maintenance module, used to develop condition assessment methods for equipment preventive maintenance; The maintenance cost analysis calculation module is used to calculate the maintenance cost for equipment maintenance.
[0019] In some embodiments of the present invention, the equipment maintenance model module includes: The multi-dimensional time series data module is used to obtain the multi-dimensional time series data of each equipment monitoring sensor on the production line through multiple monitoring sensors; The maintenance resource module is used to divide the maintenance resources required for each level of equipment maintenance on the production line; The maintenance asset impact model module is used to build an equipment maintenance asset impact model.
[0020] In some embodiments of the present invention, the preventive maintenance release module includes: An evaluation data providing module, used for providing evaluation data for preventive maintenance or replacement of equipment; Equipment status assessment module, used to assess the real-time health status of all equipment on the production line; Health data importance module, used to calculate the importance of health data of each device; The health status deterministic classification module is used to deterministically classify the health status of the equipment that constitutes the production line.
[0021] In some embodiments of the present invention, the maintenance cost analysis calculation module includes: The preventive maintenance determination module is used to make preventive maintenance determinations for the equipment on the entire production line; A maintenance time determination module is used to determine the threshold at which equipment requires maintenance and the maintenance time of the system; Maintenance cost calculation module, used to analyze the maintenance cost consumed during overall maintenance and the preventive maintenance cost within the corresponding time period, and calculate the maintenance cost; The maintenance measures taking module is used to take maintenance measures for all equipment that meets the maintenance conditions on a multi-equipment production line.
[0022] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.
[0023] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.
Claims
1. An intelligent maintenance method based on the Internet of Things, characterized in that: The method comprises the following steps: Step 1: For the operation and maintenance of multiple equipment in manufacturing enterprises, divide the maintenance impact coefficient of each equipment on the multi-equipment operation line and establish the equipment maintenance asset impact model brought by the multi-equipment operation line; Step 2: Based on the equipment status distribution of multi-equipment production line time series, develop a status assessment method for equipment preventive maintenance; Step 3: Determine the preventive maintenance of the equipment on the entire production line; Step 4: Determine the threshold for equipment maintenance and the system maintenance time, calculate the maintenance cost for equipment maintenance, and take corresponding maintenance measures.
2. The intelligent maintenance method based on the Internet of Things according to claim 1, characterized in that: The steps of establishing the equipment maintenance asset impact model brought about by multiple equipment operation lines include: Step a1: On a multi-device hybrid production line of a manufacturing enterprise, multi-dimensional time series data of monitoring sensors of each device on the production line is obtained through multiple monitoring sensors; Step a2: Calculate the total maintenance resource consumption of the multi-equipment operation line within a set period based on the equipment impact resources of the production line operation. The equipment impact resources include the operation resources of the equipment on the multi-equipment production line, the production material resources invested, and the time resources invested in operation; Step a3: In the existing multi-equipment serial production system of the manufacturing enterprise, the equipment on the multi-equipment production line is graded according to the difficulty of equipment maintenance. The more difficult the equipment is to maintain, the higher the grade; Step a4: The maintenance resources required for the maintenance of each level of equipment on the production line are also divided, and the maintenance resource requirements corresponding to different equipment are described using the influencing factors of the maintenance level; Step a5: using the divided equipment maintenance resource impact coefficients to divide the equipment maintenance resource demand priorities. The larger the equipment maintenance resource impact coefficient, the higher the maintenance resource demand priority, that is, the greater the maintenance resource demand of the equipment for this multi-equipment operation line; Step a6: Sort the maintenance resource requirements of all equipment on a multi-equipment production line from high to low. The total amount of maintenance resources invested in each equipment on each production line is limited. The types of maintenance resources required by each equipment on a multi-equipment production line are different, and different equipment has different requirements for the same maintenance resources. The maintenance resources are allocated to different equipment according to the total maintenance resource consumption of the equipment on a production line. Step a7: Select the allocation of equipment maintenance resources for the enterprise production line as the optimization target, build an equipment maintenance asset impact model, and match the model's needs and iterate output according to the maintenance difficulty and maintenance requirements of each equipment on the multi-equipment production line.
3. The intelligent maintenance method based on the Internet of Things according to claim 2 is characterized in that: The step of providing evaluation data comprises: The prediction method based on time series data uses the interval method to predict the degradation trend. The deep neural network model is used in real time to evaluate the working status of the equipment using the input equipment operating time. The equipment's working performance is evaluated through equipment operating status statistics, and evaluation data is provided for preventive maintenance or replacement of the equipment.
4. The intelligent maintenance method based on the Internet of Things according to claim 3 is characterized in that: The step of using the assessment data to formulate a condition assessment for equipment preventive maintenance includes: Step b1: Analyze the structure of each component device of the multi-device production line, and convert the input-output relationship between the devices and the importance in the device network into the initial weight of each device; Step b5: Calculate the Mahalanobis distance between the feature data extracted from the real-time monitoring sensor data of the equipment and the feature data set of the ideal health state of the equipment, and construct the health index of the production line equipment by using the comprehensive histogram method; Step b2: The weighted health index of each device is calculated by using the initial weight and performance health index of each device, and the importance of data is distinguished to calculate the importance of health data of each device; Step b3: Set a threshold of data importance and divide the health index of the device into two sets according to the importance threshold; Step b4: Deterministically classify the health status of the equipment that makes up the production line, and classify the equipment health status into four states: healthy, sub-healthy, abnormal, and faulty based on empirical maintenance data.
5. The method for intelligent maintenance based on the Internet of Things according to claim 4, characterized in that: The step of performing preventive maintenance determination on the equipment on the entire production line includes: Step c1: Determine the equipment that needs preventive maintenance based on the previous ranking of equipment maintenance resource demand priorities and preventive maintenance thresholds; Step c2: List all equipment that requires preventive maintenance, sort them by maintenance resource requirement priority, and select the equipment with the lowest maintenance priority as the standard for preventive maintenance; Step c3: Determine the equipment that needs preventive maintenance, and determine the equipment that needs preventive maintenance according to the maintenance resource demand degree and preventive maintenance value of the equipment on the multi-equipment production line within the selected time period; Step c4: When the maintenance resource requirement of the equipment is less than or equal to the preventive maintenance threshold, the equipment is set to require preventive maintenance; when the maintenance difficulty of the equipment is greater than the preventive maintenance threshold, the equipment is set to perform direct maintenance.
6. The method for intelligent maintenance based on the Internet of Things according to claim 5, characterized in that: The method steps of calculating the maintenance cost for equipment maintenance and taking corresponding maintenance measures include: Step d1: setting the preventive maintenance threshold of the multi-equipment production line as a whole, the preventive maintenance threshold of each equipment on the production line, and the maintenance threshold of the production line as a whole and the maintenance threshold of each equipment on the production line; Step d2: In the same time period, the time when all equipment on the production line starts running is used as the starting point for calculating the maintenance cost of the production line and equipment. The equipment that needs preventive maintenance is determined based on the maintenance difficulty and preventive maintenance threshold of the equipment. The maintenance cost consumed during the overall maintenance and the preventive maintenance cost in the corresponding time period are analyzed to calculate the maintenance cost. Step d3: Establish a mathematical model with the overall maintenance cost as the target, output the maintenance plan corresponding to the set maintenance threshold and the total maintenance cost of the entire time period. When the difference between the preventive maintenance threshold and the maintenance threshold is too large, the maintenance cost of the production line is high, and when the preventive maintenance threshold is small; Step d4: setting a threshold for the health index of the multi-equipment production line, and setting a preventive maintenance judgment for the production line and equipment when the health index of the multi-equipment production line reaches the threshold; Step d5: When the preventive maintenance action of the production line is triggered, it is determined whether the equipment in the production line has reached the preventive maintenance threshold and the maintenance threshold. The equipment that has reached the maintenance threshold is subjected to joint maintenance, that is, the production line is shut down for maintenance, and maintenance measures are taken for all equipment that meets the maintenance conditions on the multi-equipment production line; Step d6: When the health index of a multi-equipment production line does not reach the maintenance threshold, but a certain equipment in the multi-equipment production line reaches the preventive maintenance threshold, preventive maintenance measures are taken for the equipment. The maintenance measures are determined by the replacement threshold of the equipment to be maintained. Equipment below the equipment replacement threshold is replaced, and other equipment is repaired.
7. An intelligent maintenance system for executing the intelligent maintenance method based on the Internet of Things as claimed in claim 1, characterized in that: The system comprises: Equipment maintenance model module, used to establish equipment maintenance asset impact model brought by multiple equipment operation lines; Preventive maintenance module, used to develop condition assessment methods for equipment preventive maintenance; The maintenance cost analysis calculation module is used to calculate the maintenance cost for equipment maintenance.
8. The intelligent maintenance system according to claim 7, characterized in that: The equipment maintenance model module includes: The multi-dimensional time series data module is used to obtain the multi-dimensional time series data of each equipment monitoring sensor on the production line through multiple monitoring sensors; The maintenance resource module is used to divide the maintenance resources required for each level of equipment maintenance on the production line; The maintenance asset impact model module is used to build an equipment maintenance asset impact model.
9. The intelligent maintenance system according to claim 8, characterized in that: The preventive maintenance release module includes: An evaluation data providing module, used for providing evaluation data for preventive maintenance or replacement of equipment; Equipment status assessment module, used to assess the real-time health status of all equipment on the production line; Health data importance module, used to calculate the importance of health data of each device; The health status deterministic classification module is used to deterministically classify the health status of the equipment that constitutes the production line.
10. The intelligent maintenance system according to claim 9, characterized in that: The maintenance cost analysis and calculation module includes: The preventive maintenance determination module is used to make preventive maintenance determinations for the equipment on the entire production line; A maintenance time determination module is used to determine the threshold at which equipment requires maintenance and the maintenance time of the system; Maintenance cost calculation module, used to analyze the maintenance cost consumed during overall maintenance and the preventive maintenance cost within the corresponding time period, and calculate the maintenance cost; The maintenance measures taking module is used to take maintenance measures for all equipment that meets the maintenance conditions on a multi-equipment production line.