CN113393049A - Maintenance security object consumption prediction method based on linear regression model - Google Patents
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- 230000008439 repair process Effects 0.000 claims abstract description 48
- 238000012545 processing Methods 0.000 claims abstract description 14
- 238000007781 pre-processing Methods 0.000 claims abstract description 9
- 230000003449 preventive effect Effects 0.000 claims description 12
- 238000005259 measurement Methods 0.000 claims description 9
- 230000008569 process Effects 0.000 claims description 8
- 238000012360 testing method Methods 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 6
- 238000010206 sensitivity analysis Methods 0.000 claims description 6
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- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
Abstract
The invention relates to a maintenance guarantee object consumption prediction method based on a linear regression model, which belongs to the technical field of maintenance statistics and comprises the following steps of based on standard equipment comparison, and is characterized in that the method comprises the following steps: the method comprises the following steps: selecting basic type equipment; step two: selecting a basic equipment task project; step three: preprocessing the task working hour data of the basic equipment; step four: acquiring task working hour data of basic equipment; step five: processing the task project man-hour data of the basic equipment; step six: the standard repair man-hour and the man-hour quota of the single equipment are specified, the repair man-hour of the equipment can be calculated through a computer, the accuracy of the method can be improved, the manpower is simplified, the task is processed with the optimal man-hour, and the manpower cost is saved to the maximum extent.
Description
Technical Field
The invention belongs to the technical field of maintenance statistics, and relates to a task quantity calculation method, in particular to a method for calculating annual consumption of equipment.
Background
The equipment maintenance is the combination of equipment maintenance and repair. Technical management measures are taken according to a predetermined plan or according to the specification of technical conditions in order to prevent the deterioration of the performance of the equipment or reduce the probability of the failure of the equipment. After the technical state of the equipment is degraded or has a fault, the technical activities for recovering the function of the equipment comprise various scheduled repairs, unscheduled fault repairs and accident repairs, which are also called equipment repairs.
The man-hour required by equipment maintenance is generally manually calculated according to experience at present, the method is seriously dependent on experts and difficult to popularize, the accuracy cannot be guaranteed, and the calculation result varies from person to person.
Disclosure of Invention
In order to solve the problems, the invention designs a maintenance guarantee object consumption prediction method based on a linear regression model, and the method has the characteristics of strong operability, convenience and high feasibility.
The specific technical scheme of the invention is as follows:
a maintenance security object consumption prediction method based on a linear regression model is based on standard equipment comparison and comprises the following steps:
the method comprises the following steps: selecting basic type equipment;
step two: selecting a basic equipment task project;
step three: preprocessing the task working hour data of the basic equipment;
step four: acquiring task working hour data of basic equipment;
step five: processing the task project man-hour data of the basic equipment;
step six: standard repair time and time quota specification for single equipment.
The first step comprises the following steps: and selecting base type equipment, wherein all major systems are selected to form comprehensive and typical new equipment as the base type equipment. The functional structural members of subsystems, equipment, combinations and the like of the basic equipment have typicality and comparability, and are convenient for converting when standard working hours and working hour quota measurement and calculation are carried out on other equipment maintenance.
The second step is as follows: the method comprises the steps of selecting basic equipment task items, measuring and calculating standard working hours and working hour quotients of all maintenance items of selected professional basic equipment according to a maintenance task allocation table of army equipment and related requirements of measuring and calculating the standard working hours and the working hour quotients of the maintenance standard working hours and the working hour quotients, selecting proper equipment function structure levels on the maintenance task allocation table to measure and calculate the working hours, and facilitating comparison and statistical analysis of the working hours of all professional equipment and the working hours of the standard equipment.
The third step is that: the basic equipment task man-hour data preprocessing comprises S1 data acquisition, S2 data screening, S3 data integration, S4 data transformation, S5 data reduction and S6 sensitivity analysis.
And S6, performing sensitivity analysis on the processed data, executing the next step if the processed data meet the indexes, and returning S3 data inheritance to the processed data if the processed data do not meet the sensitivity indexes.
Basic type equipment maintenance task standard is gathered man-hour, and modes such as accessible direct collection, comprehensive statistics go on, wherein:
(a) and directly collecting, recording the participants and the completion time of each maintenance task item by item in the repair process of corresponding equipment of the army, calculating the tasks aiming at the field replacement and repair time of the typical equipment in the test point, and collecting related data by each professional according to the arrangement of the actual assembly and repair plan of the army.
(b) Comprehensive statistics, namely comprehensively considering relevant data such as other troops, repair institutions, major repair factories, research and development units and the like to calculate and calculate the maintenance man-hour of the equipment, wherein the data comprises the following data: firstly, various logging statistical data generated by early train army of related equipment in the processes of trial repair and actual repair of the equipment; and secondly, related data is measured and calculated in maintenance man-hours generated in the related trial repair and verification process in the previous various equipment maintenance and guarantee business work.
Step five, including the data processing of the basic equipment task project man-hour, dividing the task project into a army level and a base level, wherein each level includes preventive maintenance such as timing and fixed distance and repairability after fault, and considering the two items respectively:
(1) for preventive maintenance, maintenance work is carried out on the leaf node at the lowest layer of the formed equipment structure tree according to a maintenance flow, and the maintenance working hours of the upper node are counted according to the maintenance flow; for the repairability maintenance work, maintenance is carried out after the leaf node at the bottommost layer fails, the fault distribution corresponding to the repairability maintenance work is random, the maintenance man-hour of the node at the upper layer is counted, the preset post-set time such as the disassembly equipment of other related components needs to be counted into the man-hour, and all the leaf nodes are processed in the same way.
(2) A base-level repair project.
The processing mode of the labor hour data of each project is the same as the labor hour data processing mode of the army-level preventive maintenance project.
Step six, standard repair working hours and working hour quota specification of the single-unit equipment,
(1) distinguishing different mechanism types of army level (use teams), army level (repair teams), base (campaign) level and base (strategy) level and different maintenance work types of maintenance, replacement, test, debugging, repair, other types and the like to form a single-assembly standard working hour summary table;
(2) finishing the work of measuring and calculating the maintenance working hours of the reference equipment, and providing a single-mounted and main subsystem thereof, and a standard working hour and working hour quota table of large components;
(3) finishing the comparison and measurement work of other equipment and reference equipment;
(4) and forming a plurality of army equipment maintenance man-hour quota tables.
The invention has the beneficial effects that:
by the method, the maintenance man-hour of the equipment can be calculated through a computer, the accuracy of the method can be improved, the simplification of manpower is realized, and meanwhile, the task is processed with the optimal man-hour, so that the manpower cost is saved to the maximum extent.
Drawings
FIG. 1 is a flow chart of basic equipment task labor hour data preprocessing.
Detailed Description
The technical solutions of the present invention are further described in detail below with reference to specific examples and drawings, but the scope and implementation of the present invention are not limited thereto.
The specific implementation mode is as follows: a maintenance security object consumption prediction method based on a linear regression model is based on standard equipment comparison and comprises the following steps:
the method comprises the following steps: selecting basic type equipment;
step two: selecting a basic equipment task project;
step three: preprocessing the task working hour data of the basic equipment;
step four: acquiring task working hour data of basic equipment;
step five: processing the task project man-hour data of the basic equipment;
step six: standard repair time and time quota specification for single equipment.
The first step comprises the following steps: and selecting base type equipment, wherein all major systems are selected to form comprehensive and typical new equipment as the base type equipment. The functional structural members of subsystems, equipment, combinations and the like of the basic equipment have typicality and comparability, and are convenient for converting when standard working hours and working hour quota measurement and calculation are carried out on other equipment maintenance.
The second step is as follows: the method comprises the steps of selecting basic equipment task items, measuring and calculating standard working hours and working hour quotients of all maintenance items of selected professional basic equipment according to a maintenance task allocation table of army equipment and related requirements of measuring and calculating the standard working hours and the working hour quotients of the maintenance standard working hours and the working hour quotients, selecting proper equipment function structure levels on the maintenance task allocation table to measure and calculate the working hours, and facilitating comparison and statistical analysis of the working hours of all professional equipment and the working hours of the standard equipment. For example, a functional structure selected by a certain base type HP in a maintenance task allocation table mainly comprises a firepower system, a fire control system, a communication system, a sighting instrument, a navigation positioning device, a chassis and other general large components and a next-level main component; the functional structure selected from the maintenance task allocation table of a certain base type LD mainly comprises large common parts such as an LD system, photoelectric equipment, an interrogator, a power station, a chassis and the like and the next level.
The functional structural members at all levels selected in the maintenance task allocation table can form an equipment structural tree applied to equipment maintenance man-hour measurement and calculation.
As shown in the attached fig. 1 of the specification, the third step: the basic equipment task man-hour data preprocessing comprises S1 data acquisition, S2 data screening, S3 data integration, S4 data transformation, S5 data reduction and S6 sensitivity analysis.
And S6, performing sensitivity analysis on the processed data, executing the next step if the processed data meet the indexes, and returning S3 data inheritance to the processed data if the processed data do not meet the sensitivity indexes.
Basic type equipment maintenance task standard is gathered man-hour, and modes such as accessible direct collection, comprehensive statistics go on, wherein:
in the processing work of the equipment maintenance support data, on one hand, a scientific and effective preprocessing method needs to be established, and on the other hand, a large amount of accurate and reliable information needs to be obtained, wherein the information comprises maintenance support data accumulated in each stage of the equipment, updating information of tactical technical indexes of the equipment in each stage and various data in the use process of the equipment support. The sources of these data are all manually collected, and therefore the data must have the aforementioned disadvantages and must be subject to specification. Basic type equipment maintenance task standard is gathered man-hour, and modes such as accessible direct collection, comprehensive statistics go on, wherein:
(a) and directly collecting, recording the participants and the completion time of each maintenance task item by item in the repair process of corresponding equipment of the army, calculating the tasks aiming at the field replacement and repair time of the typical equipment in the test point, and collecting related data by each professional according to the arrangement of the actual assembly and repair plan of the army.
(b) Comprehensive statistics, namely comprehensively considering relevant data such as other troops, repair institutions, major repair factories, research and development units and the like to calculate and calculate the maintenance man-hour of the equipment, wherein the data comprises the following data: firstly, various logging statistical data generated by early train army of related equipment in the processes of trial repair and actual repair of the equipment; and secondly, related data is measured and calculated in maintenance man-hours generated in the related trial repair and verification process in the previous various equipment maintenance and guarantee business work. When the data are used for establishing equipment maintenance standard working hours and working hour quota, repeated analysis and demonstration are required, and the formed data are real, reliable and applicable.
Among the collected data, there may be some data that is not qualified due to subjective factors or other reasons. Which may include redundant data, noisy data, anomalous data, etc. Depending on the type of data, it is handled by different methods.
(a) Lauda method
When collating Data, it is often the case that a few particularly divergent suspect Data are found in a set of Data, called Outlier or excepting Data, which are often caused by gross errors. For such erroneous data, we can use the Lauda method for screening.
And performing equal-precision measurement on the measured object. Independently obtain x1,x2,x3...xnCalculating the arithmetic mean value
And residual error
And calculating the standard deviation sigma according to Bessel formula, if a certain measured value xbThe residual error vb (1 ≦ b ≦ n) satisfies the following equation:
then xb is considered to be a bad value with a gross error value and should be screened out.
The ralida criterion is premised on a large amount of data, and the method is no longer applicable when the number of trials n < 10.
(b) Xiao Wei le Fa
After n repeated experiments, the measured values are subject to normal distribution, and a discrimination range (-k) is set to be 1/(2n)nS，knS), when residual error (measured value x)iAnd the arithmetic mean thereof
Difference) outside the range, meaning that the measurement is suspect and should be discarded, the decision range is determined by the equation:
in the formula: k is a radical ofnThe Shouyler coefficient is related to n and can be found by a normal distribution coefficient table. The judgment standard of the abnormal value of the Xiaoweiler method is as follows:
(c) grabbs method
When screening data with a small number of samples, we can adopt the Grabbs method.
The Grabbs method assumes that the test result follows normal distribution, and judges the data acceptance or rejection according to the sequence statistics. Let n measured values arrange x in order of magnitude1≤x2≤x3≤…xnLet x benIs abnormal data that needs to be checked for discrimination. S and SnAre all functions of the measured values, the corresponding probability densities are:
therefore:
the value of λ (α, n) can be obtained by looking up a table, given the significance level α and the number of data n. The anomaly data x are then comparednAnd the average value
Is | xnThe magnitude relationship of-x | to λ (α, n) σ determines whether anomalous data should be screened out.
Step five, including the data processing of the basic equipment task project man-hour, dividing the task project into a army level and a base level, wherein each level includes preventive maintenance such as timing and fixed distance and repairability after fault, and considering the two items respectively:
(1) for preventive maintenance, maintenance work is carried out on the leaf node at the lowest layer of the formed equipment structure tree according to a maintenance flow, and the maintenance working hours of the upper node are counted according to the maintenance flow; for the repairability maintenance work, maintenance is carried out after the leaf node at the bottommost layer fails, the fault distribution corresponding to the repairability maintenance work is random, the maintenance man-hour of the node at the upper layer is counted, the preset post-set time such as the disassembly equipment of other related components needs to be counted into the man-hour, and all the leaf nodes are processed in the same way.
For example, if a subsystem a of a certain equipment includes 5 components such as a1, a2, A3, a4, and a5, the different man-hours are considered:
1) preventive maintenance work. For the specified maintenance in the quarter, the procedure of the preventive maintenance work is "detach a1 → detach a2, A3, a4 → detach a5 → identify a2, A3, a4, maintain → identify a5, replace → install a4, A3, a2 → install a 1", and the man-hour of the subsystem a is the sum of the 7 detachment process man-hours;
2) and (5) performing repairable maintenance work. For the repair of the "replacement" type after the failure of a2, A3, a4 and a5, the man-hours of a2, A3 and a4 all include the man-hours of "detaching a1 and attaching a 1", and the man-hours of a5 include the man-hours of "detaching a1, detaching a2, A3 and a4, attaching a4, A3 and a2, and attaching a 1".
(2) A base-level repair project.
The processing mode of the labor hour data of each project is the same as the labor hour data processing mode of the army-level preventive maintenance project.
In each level of task, the repair items are frequently carried out according to two types of preventive maintenance and reparative maintenance.
Step six, standard repair working hours and working hour quota specification of the single-unit equipment,
(1) distinguishing different mechanism types of army level (use teams), army level (repair teams), base (campaign) level and base (strategy) level and different maintenance work types of maintenance, replacement, test, debugging, repair, other types and the like to form a single-assembly standard working hour summary table;
(2) finishing the work of measuring and calculating the maintenance working hours of the reference equipment, and providing a single-mounted and main subsystem thereof, and a standard working hour and working hour quota table of large components;
(3) finishing the comparison and measurement work of other equipment and reference equipment;
(4) and forming a plurality of army equipment maintenance man-hour quota tables.
Claims (8)
1. A maintenance support object consumption prediction method based on a linear regression model is based on standard equipment comparison and is characterized by comprising the following steps:
the method comprises the following steps: selecting basic type equipment;
step two: selecting a basic equipment task project;
step three: preprocessing the task working hour data of the basic equipment;
step four: acquiring task working hour data of basic equipment;
step five: processing the task project man-hour data of the basic equipment;
step six: standard repair time and time quota specification for single equipment.
2. The maintenance and security object consumption prediction method based on the linear regression model according to claim 1, characterized in that: the first step comprises the following steps: and selecting base type equipment, wherein all major systems are selected to form comprehensive and typical new equipment as the base type equipment. The functional structural members of subsystems, equipment, combinations and the like of the basic equipment have typicality and comparability, and are convenient for converting when standard working hours and working hour quota measurement and calculation are carried out on other equipment maintenance.
3. The maintenance and security object consumption prediction method based on the linear regression model according to claim 2, characterized in that: the second step is as follows: the method comprises the steps of selecting basic equipment task items, measuring and calculating standard working hours and working hour quotients of all maintenance items of selected professional basic equipment according to a maintenance task allocation table of army equipment and related requirements of measuring and calculating the standard working hours and the working hour quotients of the maintenance standard working hours and the working hour quotients, selecting proper equipment function structure levels on the maintenance task allocation table to measure and calculate the working hours, and facilitating comparison and statistical analysis of the working hours of all professional equipment and the working hours of the standard equipment.
4. The method for predicting the consumption of maintenance and security objects based on a linear regression model according to claim 3, wherein the third step is: the basic equipment task man-hour data preprocessing comprises S1 data acquisition, S2 data screening, S3 data integration, S4 data transformation, S5 data reduction and S6 sensitivity analysis.
5. The method of claim 4, wherein the step S6 is implemented by performing sensitivity analysis on the processed data, and if the processed data meets the criterion, the next step is executed, and if the processed data does not meet the sensitivity criterion, the processed data is returned to step S3 for data inheritance.
6. The method of claim 5, wherein the standard labor hour collection of the basic equipment maintenance task is performed by direct collection, comprehensive statistics, and the like, wherein:
(a) and directly collecting, recording the participants and the completion time of each maintenance task item by item in the repair process of corresponding equipment of the army, calculating the tasks aiming at the field replacement and repair time of the typical equipment in the test point, and collecting related data by each professional according to the arrangement of the actual assembly and repair plan of the army.
(b) Comprehensive statistics, namely comprehensively considering relevant data such as other troops, repair institutions, major repair factories, research and development units and the like to calculate and calculate the maintenance man-hour of the equipment, wherein the data comprises the following data: firstly, various logging statistical data generated by early train army of related equipment in the processes of trial repair and actual repair of the equipment; and secondly, related data is measured and calculated in maintenance man-hours generated in the related trial repair and verification process in the previous various equipment maintenance and guarantee business work.
7. The method for predicting the consumption of maintenance and safeguard objects based on the linear regression model as claimed in claim 6, wherein the fifth step comprises a basic equipment task project man-hour data processing step, wherein the task project is divided into a army level and a basic level, each level comprises two types of projects of preventive maintenance such as timing and scheduling and repairability after failure, and the projects are considered respectively:
(1) for preventive maintenance, maintenance work is carried out on the leaf node at the lowest layer of the formed equipment structure tree according to a maintenance flow, and the maintenance working hours of the upper node are counted according to the maintenance flow; for the repairability maintenance work, maintenance is carried out after the leaf node at the bottommost layer fails, the fault distribution corresponding to the repairability maintenance work is random, the maintenance man-hour of the node at the upper layer is counted, the preset post-set time such as the disassembly equipment of other related components needs to be counted into the man-hour, and all the leaf nodes are processed in the same way.
(2) A base-level repair project.
The processing mode of the labor hour data of each project is the same as the labor hour data processing mode of the army-level preventive maintenance project.
8. The method of claim 6, wherein the sixth step specifies standard man-hours and a rating of man-hours for repair of one-piece equipment,
(1) distinguishing different mechanism types of army level (use teams), army level (repair teams), base (campaign) level and base (strategy) level and different maintenance work types of maintenance, replacement, test, debugging, repair, other types and the like to form a single-assembly standard working hour summary table;
(2) finishing the work of measuring and calculating the maintenance working hours of the reference equipment, and providing a single-mounted and main subsystem thereof, and a standard working hour and working hour quota table of large components;
(3) finishing the comparison and measurement work of other equipment and reference equipment;
(4) and forming a plurality of army equipment maintenance man-hour quota tables.
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