CN118735307A - Multi-component equipment string co-production line opportunity maintenance method considering multiple correlations - Google Patents
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Abstract
The invention discloses a multi-component equipment string co-production line opportunity maintenance method considering multiple correlations in the field of intelligent manufacturing, which comprises two interrelated planning periods of a component predictive maintenance period and a system predictive maintenance period: in a component predicting maintenance period, optimizing a component layer predicting maintenance time point based on a maintenance cost rate model constructed by the component state decay information, and inputting a result into a system predicting maintenance period; in the system predictive maintenance period, the economic evaluation of the advanced maintenance of each component is carried out based on the establishment of the equipment layer and system layer maintenance cost balance model considering multiple correlations, the maintenance resource constraint is considered, the equipment maintenance selection is carried out to obtain the final component maintenance decision of the current maintenance opportunity, and the feedback of the decision result to the next component predictive maintenance period is carried out to carry out the subsequent opportunity maintenance planning. The invention can effectively reduce the maintenance cost of the multi-component equipment string co-production line, thereby realizing the remarkable improvement of the economic benefit of a processing workshop.
Description
Technical Field
The invention relates to a technology in the field of intelligent manufacturing, in particular to a multi-component equipment string co-production line opportunity maintenance method considering multiple correlations.
Background
The multi-component equipment serial co-production line has multiple correlations, economic correlations exist among the serial equipment, and the shutdown maintenance of one equipment can lead to the shutdown of the whole production line; structural correlation exists among key parts of the equipment, and maintenance of one part needs to disassemble other correlated parts at the same time. Existing production line maintenance strategies do not take this feature into account.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention provides a multi-component equipment string co-production line opportunity maintenance method considering multiple correlations. The opportunistic maintenance cost balance algorithm considering the structural correlation and the economic correlation is provided, the independent health evolution of the components, the component disassembly sequence and the equipment procedure correlation are integrated to analyze the maintenance cost benefit, a maintenance decision frame and a closed-loop interaction mechanism of a component layer-equipment layer-system layer are constructed, maintenance resource limitation is further introduced, and a component maintenance plan of a complex manufacturing system is dynamically output. The invention can effectively reduce the maintenance cost of the multi-component equipment string co-production line, thereby realizing the remarkable improvement of the economic benefit of a processing workshop.
The invention is realized by the following technical scheme: the invention relates to a multi-component equipment string co-production line opportunity maintenance method considering multiple correlations, which comprises two interrelated planning periods of a component predictive maintenance period and a system predictive maintenance period; in a component predictive maintenance period, a maintenance cost rate model is constructed based on component state decay information, a component layer predictive maintenance time point is optimized, and a result is input into a system predictive maintenance period; in a system predictive maintenance period, multiple correlations are considered, a device layer maintenance cost balance model and a system layer maintenance cost balance model are established, and the economy of the advanced maintenance of each component is evaluated; taking maintenance resource constraint into consideration, carrying out equipment maintenance selection, obtaining a final component maintenance decision of the current maintenance opportunity, further feeding back the final component maintenance decision to a next component predictive maintenance period, and continuing to carry out subsequent opportunity maintenance planning.
The multi-component equipment string co-production line specifically comprises: a manufacturing system is formed by connecting a plurality of multi-component devices in series, wherein each device contains a plurality of critical components having structural correlation, and the states of the components are required to carry out preventive maintenance work to restore them due to degradation or to carry out fault repair work to restore them from a failure state to an operation state.
The component predictive maintenance period and the system predictive maintenance period specifically refer to: the invention carries out two mutually input and output decision-making processes of the production line maintenance planning, and the planning cycle of two periods is developed to obtain a maintenance scheme in a planning period; the component predicts maintenance period, and performs maintenance interval optimization and initial maintenance time point allocation which only consider the state decay process of the component for each independent component; the system predicts maintenance period, aims at the whole production line, takes planning results of the part predicting maintenance period as input, performs maintenance time point adjustment decision of each part in consideration of multiple correlation and maintenance resource limitation at maintenance opportunities, generates a final part maintenance execution scheme, feeds back the final part maintenance execution scheme to the part predicting maintenance period, and performs subsequent part maintenance interval optimization.
The optimizing component layer predicts maintenance time points, which means that: in a component predictive maintenance period, based on real-time monitoring information of state data of each component of the system, a maintenance cost rate model is established by combining maintenance and disassembly parameters of each component, and the model is solved to obtain an optimal maintenance period interval of the component corresponding to the minimum cost rate; the maintenance and disassembly parameters of each component comprise, but are not limited to, preventive maintenance time consumption, preventive maintenance cost, fault first-aid repair operation time consumption, fault first-aid repair operation cost, component disassembly time consumption, component disassembly cost and component fault rate distribution function; solving to obtain the optimal maintenance period interval of the component corresponding to the minimum cost rate specifically means that the optimal maintenance period interval of the equipment corresponding to the minimum cost rate is obtained by calculating a derivative equation of a maintenance cost rate model to enable the derivative equation to be equal to 0; the optimal maintenance period interval is entered as an input into the system predictive maintenance period.
The evaluation of the economy of the advanced maintenance of each component means that: in the current system predictive maintenance period, a trigger component triggers a maintenance opportunity when the trigger component firstly reaches an optimal maintenance time point obtained by planning the component predictive maintenance period, other components can be pre-maintained to the maintenance opportunity, the preventive maintenance of a plurality of components can be simultaneously carried out, compared with independent maintenance operation, the time and economic cost of disassembly, maintenance and equipment installation and debugging can be remarkably saved, and the influence of the pre-maintenance pre-decision on the economical efficiency of a maintenance scheme is quantified based on the real-time health decline state of each component and multiple maintenance correlation analysis covering the disassembly of the components and the system configuration.
The consideration of maintenance resource constraint refers to: because of the shortage of maintenance personnel, inconvenient traffic, and lack of maintenance tools, the number of maintenance teams dispatched in a single maintenance is limited, resulting in the implementation of predictive maintenance operations on only parts in a part of the equipment, and thus the number of equipment that can perform maintenance on the parts per maintenance opportunity is set to be limited.
The device maintenance selection is that: and calculating equipment maintenance benefits based on the maintenance cost balance result output of each component, wherein the value is the sum of the positive maintenance cost balance values in the equipment minus the disassembly cost and the equipment installation and debugging cost, and the obtained equipment maintenance benefits are ordered in a descending order, and besides maintenance triggering equipment, equipment components are selected to maximize the total equipment maintenance benefits, and preventive maintenance is carried out on the components with positive total maintenance cost balances in the selected equipment.
The feedback of the final component maintenance decision to the next component predictive maintenance cycle refers to: after making a decision of predicting maintenance period of the system, updating the actual maintenance time point of each current device according to an actual decision scheme; and assigning values to the components for performing preventive maintenance, and circularly executing the component layer predictive maintenance period planning of the next period to realize long-term high-economical maintenance of the production line.
Drawings
FIG. 1 is a flow chart of the present invention;
fig. 2 is a schematic structural diagram of a multi-component equipment string co-production line in an embodiment of the present invention.
Detailed Description
As shown in fig. 1, this embodiment relates to a multi-component device string co-production line opportunity maintenance method considering multiple correlations, including the following steps:
The first step: the directional node diagram is used for representing the serial production line structure of the multi-component equipment, the whole equipment is represented by a node 0, and other nodes represent key components installed in the equipment; the component nodes with structural correlation are connected by directional arrows, and the direction of the arrows represents the sequence relation of disassembly between the two connected components; the arrow starts from the father node and points to the child node, and the disassembly of the parts represented by the child node needs to be performed firstly, namely the parts represented by the father node have higher disassembly sequence; the part node from the node 0 to the part node without arrow is a disassembly path; the nodes 0 representing the respective devices are connected by line segments, and the economic correlation between the devices connected in series is represented.
Step two, obtaining part state decline information in a part predictive maintenance period: predicting maintenance cycles from a first componentStarting, i.e; Obtaining a fault rate distribution function based on reliability parameters of all parts in all equipment of the production line。
Third, defining parameters and symbolic representations thereof: definition of the definitionFor a set of equipment contained in a production line, the index isApparatus and methodSymbolically as a symbolA representation; Is a device The disassembly path set contained in the file is indexed as，In a disassembly path of (a)To be used forA representation; Is that Is a component set of (a) with index of，In (a) partsSymbolically as a symbolA representation; Is that A collection of parts in (a); Is that A disassembly sequence in its disassembly path; Is that Has a ratio ofA higher order of disassembly of the component sets; Is that Has a ratio ofA lower order of disassembly of the component sets;、 Predicting maintenance periods and indexes of system maintenance periods for the components respectively; Installing an index of debug activities for the device; 、、 Respectively is Preventive maintenance operation cost, fault rush repair operation cost, and component disassembly cost;、、 Respectively is Is time-consuming in preventive maintenance operation, time-consuming in fault repair operation and time-consuming in component disassembly;、 Respectively is The installation and debugging cost and time consumption of the system; Is that A single maintenance team employment cost; Is that A production delay cost rate of (2); Is that Is a devaluation rate of (2);、 Respectively is Value at the beginning and end of the planning period; the maximum equipment number which can be maintained for each maintenance opportunity; for the length of the planning period.
Fourth step, define variable and its formula expression: definition of the definitionIs thatIn the first placeThe individual components predict an optimal maintenance interval obtained by optimizing a maintenance period through a maintenance cost rate model; Is that In the first placeThe individual components predict an optimal maintenance time point obtained by optimizing a maintenance period through a maintenance cost rate model; Is that In the first placeActual maintenance intervals after system predictive maintenance adjustment in the individual component predictive maintenance period; Is the first The individual systems predict maintenance decision-making time points of maintenance cycles, i.e. maintenance opportunity start time points;、 Respectively the first The system predicts a triggering part and a triggering device of a maintenance period, wherein the triggering device refers to the device where the triggering part is located; Is that Is the first of (2)Time of completion of sub-mount debug activity, where；、、Respectively isAt the position ofA device layer maintenance cost balance, a system layer maintenance cost balance and a total maintenance cost balance at moment; Is that At the position ofEquipment maintenance benefits at the moment; Is that In the first placePredicting a fault rate function of a maintenance period by each component; Is that At the position ofA maintenance decision at the moment; after decision making by the method of the invention A time component maintenance assembly; Is that Is not limited by the depth of disassembly; Indexing a part corresponding to a disassembly depth in a currently planned disassembly path; Is the first Total predictive maintenance, component disassembly and equipment installation and commissioning of individual system predictive maintenance cycles is time consuming.
Fifth, solving the component layer preventive maintenance period in the component predictive maintenance period: constructing a maintenance cost rate model based on failure rate distribution functions of all componentsAnd obtaining the optimal maintenance interval of the component with the minimum cost rate through derivation。
Sixth, component layer preventive maintenance time point allocation and update in component predictive maintenance period: optimal maintenance intervals based on componentsCalculating optimal preventive maintenance time points for each componentThe distribution result is as follows:，。
Seventh step: determining whether the cycle is ended: judging whether the optimal preventive maintenance time points of all the components are larger than the length of a planning period, if so, ending the preventive maintenance planning of the production line; if not, turning to the eighth step.
Eighth step, the decision system predicts the maintenance opportunity in the maintenance period: searching for the component with the smallest value in all parts of the production lineA component of value, defining the component and the equipment thereof as a maintenance triggering component and a maintenance triggering equipment, and correspondingThe value is defined as the decision-making point in time of the current system predictive maintenance cycle:，。
ninth, the computing system predicts a total maintenance cost balance in the maintenance cycle: for each non-repair part, in And calculating the total maintenance cost balance at any time, and simultaneously updating the disassembly depth until a final total maintenance cost balance calculation result is output, wherein the method is implemented in the following manner.
9-1 Initial disassembly depth: before making the predictive maintenance adjustment decision, only the maintenance trigger componentIs determined to be assigned for maintenance activities, thusThe components which are initially disassembled in the system are provided with the deepest disassembly position in the disassembly path, while the components in other disassembly paths are not decided to be disassembled temporarily, so that the deepest disassembly depth in the other disassembly paths is 0.
9-2 Component indexes corresponding to the removal depths in the respective removal paths set in consideration of structural correlation between componentsEstablishing equipment layer maintenance cost balance of each componentThe calculation model specifically comprises the following steps: repair work remaindersExpressed as by the formulaRepresenting that the advance of the predicted maintenance reduces the accumulated failure rate of the current period component and correspondingly reduces the repairability maintenance cost; equipment production delay cost balance itemExpressed as by the formulaRepresenting that advancing the individual components to the current maintenance opportunity saves additional predictive maintenance work and disassembly time compared to the individual disassembly maintenance of the components, thereby shortening the downtime delay time and corresponding penalty cost of the equipment, classifying the components for different typesAnd (3) withThe corresponding time saving is calculated respectively; predicting maintenance operation cost balanceExpressed as by the formulaFrom the aspect of long-term planning, the advanced predictive maintenance operation is to promote the predictive maintenance operation frequency, so that the corresponding operation cost is increased, and the balance items are also calculated according to different part classifications; component accelerated depreciation cost balance itemExpressed as by the formulaIndicating that frequent maintenance operations result in accelerated depreciation of the component; device layer maintenance cost balanceEqual to the sum of the four cost junction terms, and is written as。
9-3 Establishing a system level maintenance cost balance for each component taking into account economic dependencies between the series devicesThe calculation model is specifically as follows: maintenance team dispatch cost balanceExpressed as by the formulaIndicating that maintenance of each machine component requires a dispatch of a specialized maintenance team for maintenance triggering equipmentTo divide thereinMaintenance of other components outside can save the additional maintenance team dispatch cost of individual maintenance, which would not be avoided for other devices; equipment installation and debugging cost balanceExpressed as by the formulaRepresenting a trigger device for maintenanceTo divide thereinThe maintenance of other parts can save the additional installation and debugging cost and time-consuming penalty of the whole equipment, and the corresponding installation and debugging cost still needs to be paid for the combined maintenance of the parts of the other equipment, but the corresponding time-consuming penalty is saved; installation and debugging frequency lifting cost balance itemExpressed as by the formulaRepresentation of division ofThe frequency of installation and debugging is increased when other equipment performs component maintenance in advance, so that the long-term installation and debugging operation cost is correspondingly increased, and the method is suitable forNo additional cost is incurred; for each device, the overall system layer maintenance cost balance is the sum of the three items and is expressed by a formula; Further, the system layer of each component in the device maintains a cost balanceBy dividing the total system layer maintenance cost sum term of each device by the number of components in the corresponding device, expressed by the formula。
9-4 Comprehensive equipment layer maintenance cost balance and system layer maintenance cost balance, total maintenance cost balance of each componentFrom the sum of the two, expressed asIf (if)Description will be givenIs advanced to the maintenance opportunityProceeding can bring about cost reduction at the current disassembly depth setting, whereas the description will increase maintenance costs.
Tenth step, the selection system predicts that the equipment in the maintenance period performs maintenance: based on the total maintenance cost balance calculation result of each component, the maintenance benefits of each device are further calculated and are arranged in descending order, and the maximum number of devices which can be maintained at each maintenance opportunityUnder the constraint of (2) select divideOutside at most frontThe station apparatus is the current maintenance apparatus selection result.
Eleventh step, the output system predicts the maintenance decision in the maintenance period: summing the maintenance equipment selection result obtained in the tenth stepThe component with positive total maintenance cost balance is used as the maintenance result of the current system predictive maintenance period to carry out maintenance activities.
Twelfth step: the feedback system predicts the actual preventive maintenance execution results in the maintenance period: acquiring actual maintenance execution results including actual maintenance execution time points and actual maintenance intervals of all componentsExpressed asWherein; And calculateTime consuming actual maintenance executionExpressed as; Feeding the result back to the following component to predict the maintenance period, and planning the following period, which is expressed as the following formulaLong-term high-economical maintenance of the production line is realized.
The method is applied to a maintenance scheme making example of the multi-component equipment string co-production line shown in fig. 2, wherein maintenance related parameters of each component are shown in table 1, fault rate function distribution of each component can be obtained according to historical data, and the fault rate function distribution is obeyed with Weibull distribution #) ; The maintenance and production related parameters of each device of the production line are shown in table 2. Duration of planning period24000H, maximum number of devices that can be maintained per maintenance opportunity=3。
Table 1 maintenance related parameters for the various components of the apparatus
TABLE 2 maintenance and production-related parameters for various devices in production line
The maintenance decision optimization method provided by the invention is applied to the example, and the obtained maintenance decision scheme is shown in table 3, wherein the first column is a time point of each system maintenance decision, the second column is trigger equipment of each maintenance opportunity, the third column is a trigger part of each maintenance opportunity, and the fourth to eighth columns are part serial numbers of each equipment in the production line for executing maintenance in each maintenance opportunity.
TABLE 3 maintenance decision scheme results for embodiments of the invention
To verify the effectiveness of the multi-component equipment string co-production line opportunity maintenance method taking multiple correlations into consideration, five other conventional line maintenance strategies are applied to the case, and total cost comparison is performed, and the comparison results are shown in table 4. The following conventional strategies are adopted: the first strategy is an independent preventive maintenance strategy, which is marked as IPM, and the maintenance decision of each component in the system is only carried out based on the maintenance interval optimization result in the component predictive maintenance period, and the structural correlation of component disassembly and the economic correlation of series equipment are not considered; the second strategy is a trigger equipment maintenance strategy, which is marked as TMM, maintenance interval optimization of each component in the system is carried out based on component prediction maintenance period, structural correlation of disassembly among components is considered, equipment layer maintenance cost balance of each component in the maintenance trigger equipment is calculated at each maintenance opportunity, and only the component with positive balance in the equipment is maintained; a third is a single-component hypothesis maintenance strategy, denoted SCA, which uses the assumption that each device widely adopted in the related research at present is composed of a single critical component, develops maintenance interval optimization of a component with minimum maintenance interval of each device in the system based on a component forecast maintenance period, takes the component as a representative critical component of the whole device, considers the economic relevance of the serial devices, calculates a system layer maintenance cost balance of each device at each maintenance opportunity, and at each maintenance opportunityPerforming equipment maintenance selection under constraint, and performing maintenance activities on all components contained in the selected equipment; a fourth strategy, denoted SMS, is to simplify the equipment selection strategy, which considers the structural correlation of the disassembly of the components and the economic correlation of the equipment in series, without performing the equipment selection process, randomly selecting among the equipment with a balance of components of positive maintenance costsA stage device that performs maintenance on a component having a positive maintenance cost balance contained therein; a fifth maintenance time window strategy, denoted as MTW, is developed for optimizing maintenance intervals for each component in the system based on component-aware maintenance cycles, and setting a maintenance time window at each maintenance opportunityCounting the components with the optimal maintenance time points in the time window range of the components in each device, arranging the obtained numbers in a descending order, and selecting and dividingFront of the outsideAnd a stage device for performing maintenance on the component in which the optimal maintenance time point is within the time window range.
Table 4 comparison of the method of the present invention with the total maintenance costs of other conventional line maintenance strategies
As can be seen from the comparison of the total cost, the multi-component equipment string co-production line opportunity maintenance method considering the multiple correlations can realize remarkable total maintenance cost optimization aiming at the multi-component equipment serial system.
Compared with the prior art, the invention innovatively establishes a multi-component equipment string co-production line maintenance framework considering multiple correlations, and the system analyzes the influence of the component disassembly structure correlations and the equipment serial economic correlations on the maintenance activity economy through the maintenance cost balance model construction, and further provides an equipment maintenance selection method under the constraint of limited maintenance resources to obtain a high-economy production line maintenance scheme. Compared with the traditional method, the multi-component equipment string co-production line maintenance scheme can effectively reduce the total maintenance cost.
The foregoing embodiments may be partially modified in numerous ways by those skilled in the art without departing from the principles and spirit of the invention, the scope of which is defined in the claims and not by the foregoing embodiments, and all such implementations are within the scope of the invention.
Claims (8)
1. The multi-component equipment string co-production line opportunity maintenance method considering multiple correlations is characterized by comprising two interrelated planning periods of a component predictive maintenance period and a system predictive maintenance period; in a component predictive maintenance period, a maintenance cost rate model is constructed based on component state decay information, a component layer predictive maintenance time point is optimized, and a result is input into a system predictive maintenance period; in a system predictive maintenance period, multiple correlations are considered, a device layer maintenance cost balance model and a system layer maintenance cost balance model are established, and the economy of the advanced maintenance of each component is evaluated; taking maintenance resource constraint into consideration, carrying out equipment maintenance selection, obtaining a final component maintenance decision of the current maintenance opportunity, further feeding back the final component maintenance decision to a next component predictive maintenance period, and continuing to carry out subsequent opportunity maintenance planning.
2. The multi-component equipment string co-production line opportunity maintenance method considering multiple correlations according to claim 1, wherein the multi-component equipment string co-production line specifically refers to: a manufacturing system is formed by connecting a plurality of multi-component devices in series, wherein each device contains a plurality of critical components having structural correlation, and the states of the components are required to carry out preventive maintenance work to restore them due to degradation or to carry out fault repair work to restore them from a failure state to an operation state.
3. The multi-component equipment string co-production line opportunity maintenance method considering multiple correlations according to claim 1, wherein the component predictive maintenance period and the system predictive maintenance period specifically refer to: the invention carries out two mutually input and output decision-making processes of the production line maintenance planning, and the planning cycle of two periods is developed to obtain a maintenance scheme in a planning period; the component predicts maintenance period, and performs maintenance interval optimization and initial maintenance time point allocation which only consider the state decay process of the component for each independent component; the system predicts maintenance period, aims at the whole production line, takes planning results of the part predicting maintenance period as input, performs maintenance time point adjustment decision of each part in consideration of multiple correlation and maintenance resource limitation at maintenance opportunities, generates a final part maintenance execution scheme, feeds back the final part maintenance execution scheme to the part predicting maintenance period, and performs subsequent part maintenance interval optimization.
4. The multi-component equipment string co-production line opportunity maintenance method considering multiple correlations according to claim 1, wherein the optimizing component layer predicts maintenance time points by: in a component predictive maintenance period, based on real-time monitoring information of state data of each component of the system, a maintenance cost rate model is established by combining maintenance and disassembly parameters of each component, and the model is solved to obtain an optimal maintenance period interval of the component corresponding to the minimum cost rate; the maintenance and disassembly parameters of each component comprise, but are not limited to, preventive maintenance time consumption, preventive maintenance cost, fault first-aid repair operation time consumption, fault first-aid repair operation cost, component disassembly time consumption, component disassembly cost and component fault rate distribution function; solving to obtain the optimal maintenance period interval of the component corresponding to the minimum cost rate specifically means that the optimal maintenance period interval of the equipment corresponding to the minimum cost rate is obtained by calculating a derivative equation of a maintenance cost rate model to enable the derivative equation to be equal to 0; the optimal maintenance period interval is entered as an input into the system predictive maintenance period.
5. The multi-component equipment string co-production line opportunity maintenance method considering multiple correlations according to claim 1, wherein the evaluation of the economy of the advance maintenance of each component means: in the current system predictive maintenance period, a trigger component triggers a maintenance opportunity when the trigger component firstly reaches an optimal maintenance time point obtained by planning the component predictive maintenance period, other components can be pre-maintained to the maintenance opportunity, the preventive maintenance of a plurality of components can be simultaneously carried out, compared with independent maintenance operation, the time and economic cost of disassembly, maintenance and equipment installation and debugging can be remarkably saved, and the influence of the pre-maintenance pre-decision on the economical efficiency of a maintenance scheme is quantified based on the real-time health decline state of each component and multiple maintenance correlation analysis covering the disassembly of the components and the system configuration.
6. The multi-component equipment string co-production line opportunity maintenance method considering multiple correlations according to claim 1, wherein the maintenance resource constraint is: because of the shortage of maintenance personnel, inconvenient traffic, and lack of maintenance tools, the number of maintenance teams dispatched in a single maintenance is limited, resulting in the implementation of predictive maintenance operations on only parts in a part of the equipment, and thus the number of equipment that can perform maintenance on the parts per maintenance opportunity is set to be limited.
7. The multi-component equipment string co-production line opportunity maintenance method considering multiple correlations according to claim 1, wherein the performing equipment maintenance selection means: and calculating equipment maintenance benefits based on the maintenance cost balance result output of each component, wherein the value is the sum of the positive maintenance cost balance values in the equipment minus the disassembly cost and the equipment installation and debugging cost, and the obtained equipment maintenance benefits are ordered in a descending order, and besides maintenance triggering equipment, equipment components are selected to maximize the total equipment maintenance benefits, and preventive maintenance is carried out on the components with positive total maintenance cost balances in the selected equipment.
8. The multi-component equipment string co-production line opportunity maintenance method considering multiple correlations according to claim 1, wherein the feeding back the final component maintenance decision to the next component predictive maintenance cycle means: after making a decision of predicting maintenance period of the system, updating the actual maintenance time point of each current device according to an actual decision scheme; and assigning values to the components for performing preventive maintenance, and circularly executing the component layer predictive maintenance period planning of the next period to realize long-term high-economical maintenance of the production line.
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