CN115375126A

CN115375126A - Failure probability analysis method and system for strategic spare parts

Info

Publication number: CN115375126A
Application number: CN202210981166.0A
Authority: CN
Inventors: 谢宏志; 邓孝林; 韩亚泉; 周来; 张建朋; 郭茂雨
Original assignee: China General Nuclear Power Corp; CGN Power Co Ltd; China Nuclear Power Operation Co Ltd
Current assignee: China General Nuclear Power Corp; CGN Power Co Ltd; China Nuclear Power Operation Co Ltd
Priority date: 2022-08-16
Filing date: 2022-08-16
Publication date: 2022-11-22

Abstract

The invention relates to a failure probability analysis method and a system of strategic spare parts, wherein the failure probability analysis method comprises the following steps: determining the replacement type of each replaced strategic spare part according to the work order acceptance data and the acceptance database data of the strategic spare parts in each factory; counting the replacement number corresponding to each replacement type of strategic spare parts in a specific time period; acquiring installation data of strategic spare parts of each factory and unit distribution data of each factory; calculating the operating stacking years of the strategic spare parts in a specific time period according to the installation data of the strategic spare parts and the unit distribution data of each factory; and respectively calculating the annual failure probability of each replacement type of the strategic spare parts according to the number of operating piles of the strategic spare parts and the replacement number corresponding to each replacement type in a specific time period. By implementing the technical scheme of the invention, the standardization and automation of the failure probability analysis method of strategic spare parts are realized, the working efficiency is improved, and the accuracy is improved.

Description

Failure probability analysis method and system for strategic spare parts

Technical Field

The invention relates to the field of computers, in particular to a failure probability analysis method and system for strategic spare parts.

Background

Taking a nuclear power plant as an example, strategic spare parts are important equipment which is directly related to nuclear safety or unit availability of the nuclear power plant, has no expected replacement period within the design life of the nuclear power plant, and has long manufacturing period, high price and long replacement time. And a proper amount of strategic spare parts are reserved, so that the equipment maintenance time can be shortened, the material changing overhaul period can be shortened, and the loss caused by shutdown can be reduced. Due to the above characteristics of the strategic spare parts, the stock quantity of the strategic spare parts cannot be determined directly by using the stock parameter setting principle of the conventional spare parts. The reserve quantity of the strategic spare parts is mainly related to the failure probability of the strategic spare parts, under the same condition, the higher the failure probability is, the larger the quantity of the strategic spare parts to be reserved is, namely, the accuracy of the failure probability of the strategic spare parts determines the reserve quantity of the strategic spare parts and the effectiveness of the maintenance and replacement plan.

At present, failure probability analysis of strategic spare parts is carried out by manually combing the internal operation, maintenance conditions and failure rate of a power plant and determining the failure probability of the strategic spare parts, but the combing process is complex, and the difficulty of combing is high due to inconsistent standards of the failure probabilities of the strategic spare parts of different current nuclear power plants, more links are qualitative analysis, the efficiency is low, and the accuracy is difficult to verify.

Disclosure of Invention

The invention aims to solve the technical problem of providing a failure probability analysis method and system for strategic spare parts aiming at the defects of low efficiency and difficulty in verifying accuracy in the prior art.

The technical scheme adopted by the invention for solving the technical problems is as follows: a failure probability analysis method for strategic spare parts is constructed, and comprises the following steps:

a type determining step: determining the replacement type of each replaced strategic spare part according to the work order acceptance data and the acceptance warehousing data of the strategic spare parts in each factory, wherein the replacement type comprises a repair type and a new purchase type;

and (3) counting the quantity: counting the replacement number corresponding to each replacement type of the strategic spare parts in a specific time period according to the replacement type of each replaced strategic spare part;

a data acquisition step: acquiring installation data of the strategic spare parts of each factory and unit distribution data of each factory;

and (3) year number calculation: calculating the operating stacking years of the strategic spare parts in a specific time period according to the installation data of the strategic spare parts and the unit distribution data of each factory;

and (3) calculating failure probability: and respectively calculating the annual failure probability of each replacement type of the strategic spare parts according to the number of operating piles of the strategic spare parts and the replacement number corresponding to each replacement type in a specific time period.

Preferably, the method further comprises the following steps:

acquiring the operating pile years of the strategic spare parts outside the group and the corresponding replacement number of each replacement type outside the group in a specific time period;

further, the type determining step includes:

determining the replacement type of each replaced strategic spare part in the group according to the work order acceptance data and the acceptance warehouse entry data of each factory of the strategic spare parts in the group;

the number counting step comprises the following steps:

according to the replacement type of each replaced strategic spare part in the group, counting the corresponding replacement number of each replacement type of the strategic spare part in the group in a specific time period;

the data acquisition step comprises:

acquiring installation data of the strategic spare parts in each factory in the group and unit distribution data of each factory in the group;

the year counting step includes:

calculating the operating stacking years of the strategic spare parts in the group in a specific time period according to the installation data and the unit distribution data;

the failure probability calculating step comprises the following steps:

calculating the operating stacking years of the strategic spare parts inside and outside the group according to the operating stacking years of the strategic spare parts inside and outside the group in a specific time period;

calculating the corresponding replacement number of each replacement type of the strategic spare parts inside and outside a group according to the corresponding replacement number of each replacement type of the strategic spare parts inside and outside the group in a specific time period;

and respectively calculating the annual failure probability of each replacement type of the strategic spare parts inside and outside the group according to the operation stacking years of the strategic spare parts inside and outside the group and the corresponding replacement number of each replacement type inside and outside the group.

Preferably, the type determining step includes:

determining the replaced strategic spare parts according to the work order availability data of the strategic spare parts in each factory;

and respectively determining the purchasing period corresponding to each replaced strategic spare part according to the acceptance and storage data of the strategic spare parts in each factory, and judging the replacement type of each replaced strategic spare part according to the purchasing period.

Preferably, the number of the strategic spare parts is multiple, and at least two strategic spare parts are the same type of strategic spare parts;

the number counting step further comprises:

taking at least two strategic spare parts belonging to the same spare part type as a group, and counting the replacement number corresponding to each replacement type of the spare part type in a specific time period according to the replacement type of each replaced strategic spare part;

the year counting step further includes:

calculating the operation stacking years of the spare part types in a specific time period according to the installation data of the strategic spare parts and the unit distribution data of each factory;

the failure probability calculating step further includes:

and respectively calculating the annual failure probability of each replacement type of the spare part types according to the number of the running piles of the spare part types and the replacement number corresponding to each replacement type in a specific time period.

Preferably, the quantity counting step further comprises:

summarizing the operation pile years of all strategic spare parts to obtain the summarized operation pile years of the spare parts;

the year counting step further includes:

respectively summarizing the replacement quantity corresponding to each replacement type of all strategic spare parts to obtain the replacement quantity corresponding to each replacement type summarized by the spare parts;

the failure probability calculating step further includes:

and calculating the annual failure probability of each replacement type summarized by the spare parts according to the operation pile years summarized by the spare parts and the replacement number corresponding to each replacement type.

Preferably, the type determining step includes:

the method comprises the steps of obtaining work order receiving data and acceptance warehousing data of a plurality of strategic spare parts of each factory from an SAP database regularly, determining the replacement type of each replaced strategic spare part according to the work order receiving data and the acceptance warehousing data, and updating a replacement data table, wherein the replacement data table comprises: the code, the replacement type and the replacement number of each replaced strategic spare part;

and/or, the data acquisition step comprises:

the method comprises the steps of periodically obtaining installation data of strategy spare parts of each factory and unit distribution data of each factory, and updating an installation data table and a unit distribution table respectively, wherein the installation data table comprises codes of strategy spare parts which are installed, factory numbers which are applied, installed unit numbers, the number of each unit and the first installation year; the unit distribution table comprises the year, the factory number and the number of the operating units;

and/or the failure probability calculating step comprises the following steps:

periodically and respectively calculating the annual failure probability of each replacement type of each strategic spare part according to the running number of years of each strategic spare part and the replacement number corresponding to each replacement type in a specific time period, and updating a first failure probability table, wherein the first failure probability table comprises: the coding, the replacement type and the annual failure probability of each strategic spare part;

periodically and respectively calculating the annual failure probability of each replacement type of each spare part type according to the operating pile number of each spare part type and the replacement number corresponding to each replacement type in a specific time period, and updating a second failure probability table, wherein the second failure probability table comprises: spare part type, replacement type, annual failure probability;

periodically calculating the annual failure probability of each replacement type summarized by the spare parts according to the operation stack years summarized by the spare parts and the replacement number corresponding to each replacement type in a specific period, and updating a second failure probability table, wherein the second failure probability table comprises: spare part collection, replacement type, annual failure probability.

Preferably, the method further comprises the following steps:

a request receiving step: receiving a query request of a user, wherein the query request comprises: the code of strategic spare parts to be inquired and the type of the spare parts to be inquired;

and (3) query step: inquiring corresponding annual failure probability in the first failure probability table or the second failure probability table according to the inquiry request;

an output step: and outputting the inquired annual failure probability.

Preferably, when the query request includes an encoding of a strategic spare part to be queried, the querying step includes:

judging whether the operation data corresponding to the code of the strategic spare part to be inquired meets a first preset condition or not;

if the first preset condition is met, inquiring the annual failure probability corresponding to each replacement type of the code of the strategic spare parts in the first failure probability table;

and if the first preset condition is not met, inquiring the corresponding annual failure probability in the second failure probability table.

Preferably, querying the second failure probability table for the corresponding annual failure probability comprises:

judging whether the operation data of the spare part type corresponding to the strategic spare part to be inquired meets a second preset condition or not;

if the second preset condition is met, inquiring the annual failure probability corresponding to each replacement type of the spare part types in the second failure probability table;

and if the second preset condition is not met, inquiring the annual failure probability corresponding to each replacement type summarized by the spare parts in the second failure probability table.

The present invention also constructs a failure probability analysis system for strategic spare parts comprising a processor implementing the steps of the above described failure probability analysis method for strategic spare parts when executing a stored computer program.

According to the technical scheme provided by the invention, for a certain strategic spare part, the replacement type of each replaced strategic spare part can be determined according to the work order receiving data and the checking and warehousing data of the strategic spare part in each factory, and then the replacement number corresponding to each replacement type of the strategic spare part in a specific time period is counted. Meanwhile, the operating years of the strategic spare parts in a specific time period are calculated according to the installation data of the strategic spare parts of each factory and the unit distribution data of each factory. And finally, respectively calculating the annual failure probability of each replacement type of the strategic spare parts according to the number of the operating piles of the strategic spare parts and the replacement number corresponding to each replacement type. Therefore, standardization and automation of the failure probability analysis method of strategic spare parts are realized, the working efficiency is improved, and the accuracy is improved.

Drawings

In order to illustrate the embodiments of the invention more clearly, the drawings that are needed in the description of the embodiments will be briefly described below, it being apparent that the drawings in the following description are only some embodiments of the invention, and that other drawings may be derived from those drawings by a person skilled in the art without inventive effort. In the drawings:

FIG. 1 is a flowchart of a first embodiment of a method for analyzing failure probability of strategic components according to the present invention;

fig. 2 is a flowchart of a first embodiment of the query step in the failure probability analysis method of the strategic spare parts of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.

Fig. 1 is a flowchart of a first embodiment of a failure probability analysis method for strategic components of the present invention, where the failure probability analysis method of the embodiment includes steps S10 to S50, and each step will be described below:

type determination step S10: and determining the replacement type of each replaced strategic spare part according to the work order acceptance data and the acceptance warehouse entry data of the strategic spare parts in each factory, wherein the replacement type comprises a repair type and a new purchase type.

In this step, it is first explained that, taking a nuclear power plant as an example, a nuclear power plant maintenance work is used to replace strategic spare parts by a work order. The existing failure frequency calculation method automatically calculates the availability number of spare parts by counting the work orders of strategic spare parts, but has the following problems: 1) The failure modes of the strategic spare parts are divided into two types, namely repairable failure spare parts and irreparable failure spare parts, and because the maintenance work order does not have the failure type information of the strategic spare parts, the conventional method can only calculate the total failure times and cannot distinguish the repairable failure times and the irreparable failure times; 2) The situation that the strategic spare parts are used and returned back to the warehouse exists, the existing method only reads the receiving quantity of the strategic spare parts in the work order, and the warehouse returning situation of the work order is not considered, namely the situation that the strategic spare parts are received and returned back is not considered, so that the calculated receiving quantity of the strategic spare parts is possibly too large.

In the case where a part of the strategic spares have a backup database in which the spare parts are used, for example, in a plan such as overhaul and maintenance, and are not actually replaced, it is necessary to remove the data on the availability of the work orders when counting the number of replacement strategic spares. In this step S10, only the replaced strategic spare parts are subjected to subsequent quantity statistics, and the quantities of those strategic spare parts that received the work order but were returned are rejected. For example, when a strategic spare part is received by a repair order and returned before the order is closed, the actual number of strategic spare parts received by the order is calculated to be 0.

Because the strategic spare parts fail in two types, if the replaced failure strategic spare parts can be repaired, the cost is reduced by adopting a mode of repairing the failure strategic spare parts, for example, the replaced failure strategic spare parts are sent back to a manufacturer for repair; if the replaced fault strategy spare parts can not be repaired, a new strategy spare part purchasing mode is adopted. Therefore, in this step S10, for each strategic spare part that has already been replaced, it can be determined whether its replacement type is repair type or new procurement type, respectively.

Quantity counting step S20: and according to the replacement type of each replaced strategic spare part, counting the replacement quantity corresponding to each replacement type of the strategic spare part in a specific time period.

In this step, the specific time period may be a period from the first installation time of a strategic spare part to the current year. When the replacement number of strategic spare parts is counted, the strategic spare parts are classified and counted according to the replacement types, for example, for a certain strategic spare part, the strategic spare part is replaced by one part in 2016, and the replacement type is repair; one of the repair tools is replaced in 2018, and the replacement type is repair; it was replaced by one in 2020, with the replacement type being new procurement. Then, the replacement number corresponding to the repair type of the strategic spare part is 2, and the replacement number corresponding to the new procurement type is 1.

Data acquisition step S30: and acquiring installation data of the strategic spare parts of each factory and unit distribution data of each factory.

In this step, the installation data of the strategic spare parts mainly include the nuclear power plant corresponding to the strategic spare parts, the number of the installed units, the installation number of 1 unit, and the first use time. If a new unit is put into operation in a certain nuclear power plant or a certain nuclear power plant is replaced by a strategic spare part model in the modes of item replacement, transformation and the like, the first service time of the strategic spare part may be different. Regarding the unit distribution data, the unit distribution data mainly includes the number of operating units of each nuclear power plant in each year, because the number of units of different nuclear power plants is different and the commissioning time of each unit is also different.

Year count calculation step S40: and calculating the operating stacking years of the strategic spare parts in a specific time period according to the installation data of the strategic spare parts and the unit distribution data of each factory.

In this step, it is first stated that a plurality of nuclear power plants in the same group may use the same strategic spare parts, and the conventional method for calculating the number of operating piles is to obtain the installation number of the strategic spare parts, and perform an approximately linear calculation by using the time of the whole commercial operation of the nuclear power plants as a starting point, for example, a certain power plant uses n strategic spare parts, which are commercially operated in 2015, then the number of operating piles in 2020 is (2020-2015) n. However, the conventional calculation method has the following problems: 1) With the increase of the operating time of the nuclear power plant, the operating number of the nuclear power plant reactor is also increased, however, the operating time of each nuclear power plant is different, the number of the used nuclear power plant reactor is also not completely the same, and the operating number of the nuclear power plant reactor is not linearly increased with the operating number of the nuclear power plant, so that the calculated operating number of the nuclear power plant reactor has deviation; 2) The strategic spare parts have model changing conditions such as item replacement, transformation and the like, namely the number of operating reactor years of the strategic spare parts is not necessarily completely related to the operating business time of the nuclear power plant, and the number of operating reactor years calculated by the method has deviation aiming at the strategic spare parts with the model changing conditions.

In order to solve the above problems of the conventional calculation method, in step S40, the operating heap years of the strategic spare parts in a specific time period are calculated according to the installation data of the strategic spare parts and the unit distribution data of each plant, so that the calculated operating heap years of the strategic spare parts are more accurate.

Failure probability calculation step S50: and respectively calculating the annual failure probability of each replacement type of the strategic spare parts according to the number of operating piles of the strategic spare parts and the replacement number corresponding to each replacement type in a specific time period.

In this step, since the annual failure probability of the strategic spare part is determined by the failure frequency (replacement number) of the strategic spare part and the operating heap year of the strategic spare part, after the operating heap year of the strategic spare part and the replacement number corresponding to each replacement type are accurately calculated, the annual failure probability of each replacement type of the strategic spare part can be accurately calculated, and specifically, the replacement number of the repair type of the strategic spare part and the operating heap year of the strategic spare part can be divided, so as to obtain the annual failure probability of the repair type of the strategic spare part; the replacement number of the newly purchased type of strategic spare parts may be divided by the operating heap years of the strategic spare parts to obtain the annual outage probability of the newly purchased type of strategic spare parts.

In the technical solution of this embodiment, for a certain strategic spare part, the replacement type of each replaced strategic spare part can be determined according to the work order acceptance data and the acceptance database data of the strategic spare part in each factory, and then the replacement number corresponding to each replacement type of the strategic spare part in a specific time period is counted. And meanwhile, calculating the operating year of the strategic spare parts in a specific time period according to the installation data of the strategic spare parts of each factory and the unit distribution data of each factory. And finally, respectively calculating the annual failure probability of each replacement type of the strategic spare parts according to the number of the operating piles of the strategic spare parts and the replacement number corresponding to each replacement type. Therefore, standardization and automation of the failure probability analysis method of strategic spare parts are realized, the working efficiency is improved, and the accuracy is improved.

Further, in an optional embodiment, the failure probability analysis method of the present invention further includes: and acquiring the operating pile years of the strategic spare parts outside the group and the corresponding replacement number of each replacement type outside the group in a specific time period. Further, the type determining step S10 includes: and determining the replacement type of each replaced strategic spare part in the group according to the work order acceptance data and the acceptance database data of each factory of the strategic spare parts in the group. The quantity counting step S20 includes: and according to the replacement type of each replaced strategic spare part in the group, counting the corresponding replacement quantity of each replacement type of the strategic spare part in the group in a specific time period. The data acquisition step S30 includes: and acquiring installation data of the strategic spare parts in each factory in the group and unit distribution data of each factory in the group. The year count calculation step S40 includes: and calculating the operating stacking years of the strategic spare parts in the group in a specific time period according to the installation data and the unit distribution data. The failure probability calculating step S50 includes: calculating the operating pile years of the strategic spare parts inside and outside the group according to the operating pile years of the strategic spare parts inside and outside the group in a specific time period; calculating the corresponding replacement quantity of each replacement type of the strategic spare parts inside and outside a group according to the corresponding replacement quantity of each replacement type of the strategic spare parts inside and outside the group in a specific time period;

In this embodiment, it is first explained that, when analyzing the failure probability of tactical spare parts, part of the strategic spare parts can be combined with external (outside the group) failure data, such as those of domestic and foreign nuclear power plants of the same type and strategic spare part manufacturers. After acquiring the annual failure probability data outside the group for a certain strategic spare part, the conventional method is to perform weighted average on the annual failure probability data outside the group of the strategic spare part and the failure data inside the group, for example, if the calculated annual failure probability inside the group is x1 and the acquired annual failure probability outside the group is x2, the failure probability after weighted average is k1 x1+ k2 x2, k1 and k2 are weighting coefficients, and normally, k1 and k2 are set to 0.5. However, this conventional method has the following problems: 1) The calculation standards of the failure probabilities inside and outside the group are not consistent, for example, for a manufacturer, only a large fault is generally recorded as a strategic spare part failure, and for a part of external nuclear power plants, a small fault is also recorded as a strategic spare part failure. In addition, the current method does not distinguish between repairable failure and unrepairable failure, and cannot effectively utilize annual failure probability data provided by different external units; 2) The annual failure probability is related to failure times and operation pile years, and the real failure probability of strategic spare parts is difficult to embody only by carrying out weighted average on different annual failure probabilities.

For the technical problem, the embodiment provides an external failure record of the strategic spare part by performing benchmarking with a unit outside the group or directly contacting a strategic spare part manufacturing plant, and specifically includes the number of operating years of the strategic spare part outside the group and the corresponding replacement number of each replacement type outside the group, where the number of operating years outside the group refers to the total installation and use time of the strategic spare part, for example, 6 locations are commonly installed and used for a certain strategic spare part in a certain nuclear power plant, 8 years are commonly installed and used for the strategic spare part on the site, and the number of operating years of the strategic spare part is 48. If new data exists, the newly added data record is directly stored, as shown in table 1. And reading the latest updated replacement quantity, replacement type and operation heap year in the code of each strategic spare part when in use.

TABLE 1

When the number of operating piles of a certain strategic spare part outside the group and the corresponding replacement number of each replacement type outside the group are obtained, and the number of operating piles of the certain strategic spare part inside the group and the corresponding replacement number of each replacement type inside the group are calculated, summing the number of operating piles inside the group and the number of operating piles outside the group to obtain the number of operating piles of the strategic spare part inside and outside the group; correspondingly summing the corresponding replacement number of each replacement type in the group and the corresponding replacement number outside the group respectively to obtain the corresponding replacement number of each replacement type inside and outside the group respectively; and finally, dividing the corresponding replacement number of each replacement type inside and outside the group by the operation pile years inside and outside the group respectively to obtain the annual failure probability of each replacement type of the strategic spare parts. Therefore, compared with the existing mode, the real failure probability of strategic spare parts can be reflected.

Further, in an optional embodiment, the type determining step S10 specifically includes:

and determining a purchasing period corresponding to each replaced strategic spare part according to the acceptance and storage data of the strategic spare parts in each factory, and judging the replacement type of each replaced strategic spare part according to the purchasing period.

In this embodiment, after acquiring the work order availability data of a certain strategic spare part in each factory, the type of the maintenance work order is selected as the completed work order, and the work orders returned after the strategic spare part is available are removed, that is, the strategic spare parts with actual replacement are selected (the actual availability number of the strategic spare parts is greater than 1). In addition, the work order can trigger the purchase application of strategic spare parts after being used, and the strategic spare parts which are put into storage after being purchased have two types: repairing and newly purchasing, but the time periods of newly purchased strategic spare parts and repaired strategic spare parts are different, generally, the time period for purchasing the new strategic spare parts is far longer than the time period for repairing the original strategic spare parts, therefore, the purchasing period (the time from signing of the purchasing order to warehousing of the strategic spare parts) corresponding to the replaced strategic spare parts can be determined according to the checking and warehousing data of the strategic spare parts, and then whether the newly purchased strategic spare parts are repaired or newly purchased is judged according to the purchasing period data. For example, assuming that the repair cycle of the strategic spare parts is t1 and the procurement cycle is t2, after the procurement cycle of a certain replaced strategic spare part is determined, if the procurement cycle is less than or equal to 0.5 × (t 1+ t 2), the newly arrived strategic spare part is considered to be the repaired spare part; and if the purchasing period is more than 0.5 (t 1+ t 2), the newly arrived strategic spare parts are considered as newly purchased spare parts. In addition, in the practical application process, if the procurement period is around 0.5 × (t 1+ t 2), the fault type of the strategic spare parts can be determined by manually referring to the procurement contract text, so that the probability of misjudgment is reduced.

Further, in an alternative embodiment, the number of strategic spares is plural, and at least two strategic spares are of the same type. Furthermore, the quantity counting step S20 further includes: at least two strategic spare parts belonging to the same spare part type are used as a group, and the replacement number corresponding to each replacement type of the spare part type in a specific time period is counted according to the replacement type of each replaced strategic spare part. The year count calculating step S40 further includes: and calculating the operation stacking years of the type of the spare parts in a specific time period according to the installation data of the strategic spare parts and the unit distribution data of each factory. The failure probability calculating step S50 further includes: and respectively calculating the annual failure probability of each replacement type of the spare part types according to the number of the running piles of the spare part types and the replacement number corresponding to each replacement type in a specific time period.

In this embodiment, in addition to calculating the annual failure probability for each replacement type for a strategic spare part, the annual failure probability for each replacement type for a spare part type can also be calculated for all strategic spare parts belonging to the same spare part type.

Further, in an optional embodiment, the quantity counting step S20 further includes: summarizing the operation pile years of all strategic spare parts to obtain the summarized operation pile years of the spare parts; the year count calculation step S40 further includes: respectively summarizing the replacement quantity corresponding to each replacement type of all strategic spare parts to obtain the replacement quantity corresponding to each replacement type summarized by the spare parts; the failure probability calculating step S50 further includes: and calculating the annual failure probability of each replacement type summarized by the spare parts according to the operation pile years summarized by the spare parts and the replacement number corresponding to each replacement type.

In this embodiment, in addition to calculating the annual failure probability for each replacement type for a strategic spare part, the annual failure probability for each replacement type for a summary of spare parts may also be calculated for all strategic spare parts.

Further, in an optional embodiment, at initialization of the system, at least one of the following tables may be established in the database: an outside group failure probability table (table 1), a replacement data table (table 2), an installation data table (table 3), a group distribution table (table 4), a basic information table (table 5), a first failure probability table (table 6), and a second failure probability table (table 7), which may be updated periodically, for example, once a year.

The type determining step S10 includes: the method comprises the steps of periodically obtaining work order receiving data and acceptance warehousing data of a plurality of strategic spare parts of each factory from an SAP database, determining the replacement type of each replaced strategic spare part according to the work order receiving data and the acceptance warehousing data, and updating a replacement data table, wherein the replacement data table comprises: the coding, the replacement type and the replacement number of each replaced strategic spare part.

In one implementation, as shown in table 2, the replacement data table may include, in addition to the code, the replacement type, and the replacement number of each replaced strategic spare part, the year of replacement and the nuclear power plant in which the replacement is used, where the code of the strategic spare part is a unique identifier of the strategic spare part; the year refers to the time of closing the work order when the strategic spare parts are taken; the nuclear power plant refers to a nuclear power plant used for strategic spare part replacement; the replacement number refers to the number summary of the corresponding replacement types of the nuclear power plant replacement in the year; the replacement type refers to the type of failure when the strategic spare parts are replaced.

TABLE 2

The data acquisition step S30 includes: the method comprises the steps of periodically obtaining installation data of strategy spare parts of each factory and unit distribution data of each factory, and updating an installation data table and a unit distribution table respectively, wherein the installation data table comprises codes of strategy spare parts which are installed, factory numbers which are applied, installed unit numbers, the number of each unit and the first installation year; the unit distribution table comprises the year, the factory number and the number of the operating units.

In one implementation, as shown in table 3, the installation data table of the strategic spare parts includes codes of the strategic spare parts, the nuclear power plants, installation numbers, installation machine group numbers, and first service years, and if a certain nuclear power plant operates a new unit or a certain nuclear power plant changes the model of the strategic spare parts by means of item replacement, modification, and the like, the first service times of the strategic spare parts may be different, where the installation numbers refer to the installation numbers of 1 unit of the strategic spare parts in the nuclear power plant; the installation unit number refers to which units in the nuclear power plant the strategic spare parts are installed and used. The number of the units in different nuclear power bases is different, the operation time of each unit is different, and if the number of the units in a certain nuclear power plant changes, the corresponding year, the nuclear power plant and the number of the units are recorded and added into the table 4.

TABLE 3

Year of year	Nuclear power plant	Number of operating units
			2012	K	2
2014	H	2
			2014	N	2
2015	H	3
			2015	N	3
2015	Y	2
			2016	F	2
2016	H	4
			2016	N	4
2016	Y	4
			2019	Y	5
2020	Y	6

TABLE 4

In addition, the basic information table of the strategic spare parts is shown in table 5, wherein the code of the strategic spare part is the only code of the strategic spare part; the standard manifest name refers to the name of the strategic spare parts in the database and the procurement contract; nuclear power plants refer to which nuclear power plants the strategic spare parts are used; the life cycle refers to the service life of the strategic spare parts; the repair time refers to the time for repairing the strategic spare parts, and comprises the time between signing a purchase order and warehousing the strategic spare parts; the purchasing period refers to the time for purchasing a new strategic spare part, and comprises the time between signing a purchasing order and warehousing the strategic spare part; the spare part type refers to which kind of spare part the strategic spare part is in, i.e., the last-level spare part type (attribute) of the strategic spare part.

TABLE 5

The failure probability calculating step S50 includes:

periodically calculating the annual failure probability of each replacement type of each strategic spare part according to the running number of years of each strategic spare part and the replacement number corresponding to each replacement type in a specific period, and updating a first failure probability table, wherein the first failure probability table comprises: the coding, the replacement type and the annual failure probability of each strategic spare part;

In one embodiment, with reference to tables 1-5, the annual failure probabilities of different strategic spares can be calculated, and the replacement quantity and the annual failure probability data can be recorded for each strategic spare part based on the replacement type, as shown in table 6, and the calculation process of the annual failure probability will be described in detail below:

coding of strategic spares	Number of replacement	Type of replacement	Years of operation	Probability of annual failure
					1001	2	Repair	128	1.56％
1001	0	New purchase	128	0.00％
					1002	3	Repair	480	0.63％
1002	1	New purchase	480	0.20％
					1003	3	Repair	111	2.70％
1003	0	New purchase	111	0.00％

TABLE 6

For the strategic spare part encoded with 1001, its replacement type is 1 for repair and 0 for new procurement within the group based on table 2. With reference to table 1, the replacement number of the replacement type outside the group is 1, so that the replacement number of the 1001 strategic spare parts is 2 when the replacement type is repair, and is 0 when the replacement type is new purchase, and the replacement can be updated to table 6. In addition, the number of operating stack years in table 6 may be updated periodically every year, and assuming that the current year is 2020, based on tables 3 and 4, the operating stack years of the strategic spare parts in the group may be calculated 1001, specifically, the number of installed and used strategic spare parts in the power plant K is 1, the time of first use is 2012, and the number of units in the power plant K from 2012 is 2, then the number of used stacks of the strategic spare parts in K power plants 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020 is 2, and then the number of used stacks in K power plants is 18 (2 × 9). The number of the strategic spare parts in the power plant H is 1, the first use time is 2014, the number of the units of the power plant H in 2014 is 2, the number of the units of the power plant H in 2015 is 3, the number of the units of the power plant H in 2016 is 4, therefore, the using piles of the strategic spare parts in H-power plants 2014, 2015, 2016, 2017, 2018, 2019 and 2020 are respectively 2, 3, 4 and 4, the year of the pile of the gas used in the H power plant is 25 (2 +3+ 4). The number of installed and used strategic spare parts in the power plant N is 1, the first use time is 2014, the number of units of the power plant N in 2014 is 2, the number of units of the power plant N in 2015 is 3, the number of units of the power plant N in 2016 is 4, so that the number of used piles of the strategic spare parts in the N power plants 2014, 2015, 2016, 2017, 2018, 2019 and 2020 is 2, 3, 4 and the number of used piles of the strategic spare parts in the N power plants is 25. Based on the operating pile year number of the strategic spares in the K/H/N power plant, the operating pile year number of the strategic spares in the group can be calculated to be 68 (18 + 25), and in addition, based on the table 1, the operating pile year of the 1001 strategic spares outside the group can be obtained to be 60, so the operating pile year of the strategic spares in the table 6 is 128 (68 + 60). Based on the number of replacement of strategic spares (2) and the operating heap year (128), the annual failure probability of the strategic spares under repair of the replacement type can be calculated 1001 to be 1.56% (2/128), and under new procurement of the replacement type to be 0% (0/128), and then the calculated data can be updated to table 6.

For the strategic spare parts coded as 1002, based on table 2, the replacement numbers are 2 (the replacement type is repair) and 1 (the replacement type is new purchase) in the group, and in combination with table 1, the replacement number is 1, and the replacement type is repair, so that the replacement number of the 1002 strategic spare parts in the case that the replacement type is repair is 3, the replacement number in the case that the replacement type is new purchase is 1, and further, the data can be updated to table 6, and the operating year number in table 6 can be updated periodically every year. Assuming that 2020 is the current year, based on tables 3 and 4, the operating stack years of the strategic spare parts in the group can be calculated 1002, specifically, the number of installed and used strategic spare parts in the power plant K is 3, the time of first use is 2012, and the number of units of the power plant K from 2012 is 2, then the number of used stacks of the strategic spare parts in the K power plants 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, and 2020 is 6, and then the number of used stacks in the K power plant is 54. The number of installed and used strategic spare parts in the power plant H is 3, the first use time is 2014, the number of units in the power plant H in 2014 is 2, the number of units in the power plant H in 2015 is 3, the number of units in the power plant H in 2016 is 4, so that the number of used piles of the strategic spare parts in the power plants H2014, 2015, 2016, 2017, 2018, 2019 and 2020 is 6, 9, 12 and 75 respectively, and the number of used piles in the power plant H is 75. The number of installed and used strategic spare parts in the power plant N is 3, the first use time is 2014, the number of units of the power plant N in 2014 is 2, the number of units of the power plant N in 2015 is 3, the number of units of the power plant N in 2016 is 4, so that the number of used piles of the strategic spare parts in the N power plants 2014, 2015, 2016, 2017, 2018, 2019 and 2020 is 6, 9, 12 and 75 respectively, and the number of used piles of the strategic spare parts in the N power plants is 75. The number of installed and used strategic spare parts in a power plant Y is 3, the first use time is 2015, the number of units of the power plant Y in 2015 is 2, the number of units of the power plant Y in 2016 is 4, the number of units of the power plant Y in 2019 is 5, the number of units of the power plant Y in 2020 is 6, and the number of used piles of the strategic spare parts in Y power plants 2015, 2016, 2017, 2018, 2019 and 2020 is respectively 6, 12 and 12, and the number of used piles of the strategic spare parts in Y power plants 2015, 2016, 2017, 2019 and 2020 is 66. The installation and use number of the strategic spare parts in the power plant F is 3, the first use time is 2016, the unit number of the power plant F in 2016 is 2, so that the use piles of the strategic spare parts in F power plants 2016, 2017, 2018, 2019 and 2020 are 6, 6 and the use pile number in F power plants is 30. Based on the operating pile year number of the strategic spares in the K/H/N/Y/F power plant, the operating pile year number of the strategic spares in the group can be calculated to be 300 (54 +75+66+ 30). In addition, based on table 1, it can be found that 1002 the operating stack year of the strategic spare part outside the group is 180, so the total operating stack year of the strategic spare part is 480 (300 + 180), which can then be updated to table 6. Finally, based on the replacement number and operating heap year of the strategic spare parts, the annual failure probability of 1002 strategic spare parts under repair of the replacement type can be calculated to be 0.63% (3/480), and the annual failure probability of the strategic spare parts under new procurement of the replacement type can be calculated to be 0.20% (1/480).

For the strategic spare parts coded as 1003, based on table 2, the replacement number is 2 (the replacement type is repair) and 0 (the replacement type is new purchase) in the group, and in combination with table 1, the replacement number is 1, and the replacement type is repair, so that the replacement number of the 1003 strategic spare parts is 3 when the replacement type is repair, and the replacement number is 0 when the replacement type is new purchase, and further, the data can be updated to table 6, and the operating number of the pile years in table 6 can be updated periodically every year. Assuming that 2020 years are currently available, the operating stack years of 1003 strategic spare parts in the group can be calculated based on tables 3 and 4, specifically, the number of installed and used strategic spare parts in the power plant K is 1, the time of first use is 2018, and the number of units of the power plant K in 2012 is 2, then the number of used stacks of the strategic spare parts in the K power plants 2018, 2019, and 2020 is 2, and then the number of used stacks in the K power plant is 6. The installation and use number of the strategic spare parts in the power plant H is 1, the first use time is 2018, the unit number of the power plant H in 2014 is 2, the unit number of the power plant H in 2015 is 3, and the unit number of the power plant H in 2016 is 4, so that the use piles of the strategic spare parts in the H power plants 2018, 2019 and 2020 are 4, 4 and 12 respectively, and the use piles of the strategic spare parts in the H power plants are 12. The number of installed and used strategic spare parts in the power plant N is 1, the first use time is 2018, the number of units in the power plant N in 2014 is 2, the number of units in the power plant N in 2015 is 3, and the number of units in 2016 is 4, so that the number of used piles of the strategic spare parts in the N power plants 2018, 2019 and 2020 is 4, 4 and 12 respectively.

The installation and use number of the strategic spare parts in the power plant Y is 1, the first use time is 2018, the unit number of the power plant Y in 2015 is 2, the unit number of the power plant Y in 2016 is 4, the unit number of the power plant Y in 2019 is 5, and the unit number of the power plant Y in 2020 is 6, so that the use piles of the strategic spare parts in N power plants 2018, 2019 and 2020 are 4, 5 and 6 respectively, and the use pile number of the strategic spare parts in the Y power plant is 15.

The installation and use number of the strategic spare parts in the power plant F is 1, the first use time is 2018, and the unit number of the power plant F in 2016 is 2, so that the use piles of the strategic spare parts in the F power plants 2018, 2019 and 2020 are 2, 2 and 2 respectively, and the use pile number of the strategic spare parts in the F power plants is 6. Based on the operating pile year number of the strategic spares in the K/H/N/Y/F power plant, the operating pile year number in the group can be calculated to be 51 (6 +12+15+ 6). In addition, based on table 1, it can be obtained that the operating stack year of 1003 strategic spare parts outside the group is 60, so the operating stack year of the strategic spare parts is 111 (51 + 60), and then it can be updated to table 6. Finally, based on the replacement number and operating heap year of the strategic spare parts, the annual failure probability of the 1003 strategic spare parts under repair of the replacement type is calculated to be 2.70% (3/111), and the annual failure probability of the strategic spare parts under new procurement of the replacement type is calculated to be 0% (0/111).

With reference to tables 5 and 6, for each type of spare part (e.g., rotor, motor), the annual failure probability data can be calculated based on the replacement type, as shown in table 7, and the calculation process of the annual failure probability will be described in detail below:

type of strategic spare parts	Number of replacement	Type of replacement	Year of operation	Probability of annual failure
					Rotor	2	Repair	128	1.56％
Rotor	0	New purchase	128	0.00％
					Electrical machine	6	Repair	591	1.01％
Electric machine	1	New purchase	591	0.17％
					Spare parts collection	8	Repair	719	1.11％
Spare parts collection	1	New purchase	719	0.14％

TABLE 7

Taking the spare part type as the rotor as an example, only the strategic spare part coded 1001 in table 5 is the rotor, so the number of replacement of the rotor, the operating stack year, and the probability of annual failure are the same as the data of the strategic spare part coded 1001 in table 6, and can be updated to table 7. Taking the spare type as the motor as an example, in table 5, the strategic spare types coded as 1002 and 1003 are both motors, so the replacement number of the motors is the sum of the replacement numbers of the strategic spare types coded as 1002 and 1003, that is, the replacement number of the repair type is 6 (3 + 3), and the replacement number of the newly purchased type is 1 (1 + 0); the operating stack year of the motor is the sum of the operating stack years of the strategic spares of the codes 1002 and 1003, i.e., the operating stack year is 591 (480 + 111). Further, the annual failure probability of the repair type of the motor can be calculated to be 1.01% (6/591) and the annual failure probability of the newly purchased type to be 0.17% (1/591), and then the motor can be updated to table 7.

Furthermore, the operating pile years of all strategic spare parts and the replacement quantity corresponding to each replacement type in the first failure probability table (table 6) can be summarized respectively to obtain the operating pile years summarized by the spare parts and the replacement quantity corresponding to each replacement type, and the annual failure probability of each replacement type summarized by the strategic spare parts is calculated according to the operating pile years summarized by the spare parts and the replacement quantity corresponding to each replacement type. With reference to Table 7, the total replacement number of spare parts is the sum of the replacement numbers of all types, i.e., the replacement number of the repair type is 8 (2 + 6), and the replacement number of the newly purchased type is 1 (0 + 1); the number of the spare part aggregated operating stack years is the sum of the operating stack years of all the spare part types, namely, the operating stack year is 719 (128 + 591). Further, the annual failure probability of the repair type summarized by the spare parts may be calculated to be 1.11% (8/719) and the annual failure probability of the new procurement type summarized by the spare parts may be calculated to be 0.14%, which may then be updated to table 7.

Further, in an optional embodiment, the failure probability analysis method of the present invention further includes:

a request receiving step: receiving a query request of a user, wherein the query request comprises: the code of the strategic spare part to be inquired and the type of the spare part to be inquired;

an output step: and outputting the queried annual failure probability.

In this embodiment, when a user needs to check a certain strategic spare part or the annual failure probability of a certain type of strategic spare part, the code of the strategic spare part or the type of the spare part can be input into the system, and then the system can inquire the corresponding annual failure probability in the first failure probability table or the second failure probability table according to the inquiry request of the user and output the inquired annual failure probability to the user, so that the user can determine the optimal reserve quantity of the strategic spare part according to the output annual failure probability.

Further, in an optional embodiment, when the query request includes the code of the strategic spare part to be queried, the querying step includes:

judging whether the operation data corresponding to the code of the strategic spare part to be inquired meets a first preset condition, wherein the first preset condition is as follows: the number of operating piles corresponding to the code of the strategic spare part is greater than a first preset value, and the replacement number corresponding to each replacement type corresponding to the code of the strategic spare part to be inquired is greater than a second preset value;

if the first preset condition is met, inquiring the annual failure probability corresponding to each replacement type of the code of the strategic spare part in the first failure probability table;

In this embodiment, when a user needs to check the annual failure probability of a certain strategic spare part, it may be determined whether the operational data of the strategic spare part is sufficient, that is, whether a first preset condition is satisfied, and if so, the annual failure probability corresponding to each replacement type of the code of the strategic spare part is directly queried from the first failure probability table; if the failure probability of the strategic spare parts cannot be really reflected due to the fact that the number of the failed strategic spare parts is not satisfied, for example, no effective replacement quantity exists, or the number of the operating piles is small because the service life of the strategic spare parts is short, the corresponding annual failure probability is inquired from the second failure probability table.

Fig. 2 is a flowchart of a first embodiment of the query step in the failure probability analysis method for strategic spare parts of the present invention, where the query step of the embodiment includes:

step S71, determining whether the operation data corresponding to the code of the strategic spare part to be queried meets a first preset condition, where the first preset condition is, for example: the number of operating piles corresponding to the code of the strategic spare part is greater than a first preset value, and the replacement number corresponding to each replacement type corresponding to the code of the strategic spare part to be inquired is greater than a second preset value, if yes, executing step S72; if not, executing step S73;

step S72, inquiring the annual failure probability corresponding to each replacement type of the code of the strategic spare parts in the first failure probability table;

step S73, determining whether the operation data of the spare part type corresponding to the strategic spare part to be queried meets a second preset condition, where the second preset condition is, for example: if the number of operating years corresponding to the type of the spare part corresponding to the strategic spare part to be queried is greater than the third preset value, and the number of replacement corresponding to each replacement type corresponding to the type of the spare part corresponding to the strategic spare part to be queried is greater than the fourth preset value, executing step S74; if not, executing step S75;

step S74, inquiring the annual failure probability corresponding to each replacement type of the spare part types in the second failure probability table;

step S75, querying a year failure probability corresponding to each replacement type summarized by the spare parts in the second failure probability table.

In this embodiment, if the operational data of the strategic spare part is sufficient, the annual failure probability data of the strategic spare part is directly used; if the operation data of the strategic spare parts is insufficient but the operation data of the strategic spare parts of the same type is sufficient, using the annual failure probability data of the type of the spare parts corresponding to the strategic spare parts as the annual failure probability data of the strategic spare parts; and if the operation data of strategic spare parts of the same type is insufficient, using the annual failure probability data collected by the spare parts as the annual failure probability data of the strategic spare parts.

The invention also constructs a failure probability analysis system for a strategic spare part, comprising a processor implementing the steps of the method for failure probability analysis of a strategic spare part described above when executing a stored computer program.

It should be understood that IN the embodiment of the present ApplicatioN, the Processor may be a central processing unit (CeN 3 tray processing n3g UN3it, CPU), and may also be other general-purpose processors, digital Signal Processors (DSPs), applicatioN Specific Integrated Circuits (ASICs), field-Programmable Gate arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like. The general purpose processor may be a microprocessor, any conventional processor, etc.

Moreover, since the processor can implement the steps of the method for analyzing failure probability of any strategic spare parts provided by the embodiment of the present invention when executing the computer program, the beneficial effects that can be achieved by the method for analyzing failure probability of any strategic spare parts provided by the embodiment of the present invention can be achieved, for details, see the foregoing embodiments, and are not described herein again.

The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.

Claims

1. A failure probability analysis method of strategic spare parts is characterized by comprising the following steps:

a type determining step: determining the replacement type of each replaced strategic spare part according to the work order acceptance data and the acceptance and storage data of the strategic spare parts in each factory, wherein the replacement type comprises a repair type and a new purchase type;

2. The method of analyzing failure probability of strategic spare parts according to claim 1, further comprising:

acquiring the operating and stacking years of the strategic spare parts outside the group and the corresponding replacement number of each replacement type outside the group in a specific time period;

further, the type determining step includes:

the number counting step comprises the following steps:

the data acquisition step comprises:

the year counting step includes:

the failure probability calculating step comprises the following steps:

3. The method for analyzing failure probability of strategic spare parts according to claim 1, wherein said type determining step comprises:

and respectively determining the purchasing period corresponding to each replaced strategic spare part according to the acceptance and warehousing data of the strategic spare parts in each factory, and judging the replacement type of each replaced strategic spare part according to the purchasing period.

4. The method of analyzing failure probability of strategic spare parts according to any of claims 1-3, wherein the number of strategic spare parts is plural, and at least two strategic spare parts are of the same type;

the number counting step further comprises:

the year count calculating step further includes:

the failure probability calculating step further comprises:

and respectively calculating the annual failure probability of each replacement type of the spare part types according to the number of operating piles of the spare part types and the corresponding replacement number of each replacement type in a specific time period.

5. The method for analyzing failure probability of strategic spare parts according to claim 4, wherein,

the number counting step further comprises:

summarizing the operation pile years of all strategic spare parts to obtain the operation pile years summarized by the spare parts;

the year counting step further includes:

the failure probability calculating step further includes:

6. The method of analyzing failure probability of strategic spare parts according to claim 5, wherein said type determining step comprises:

and/or the data acquisition step comprises:

the method comprises the steps of periodically obtaining installation data of strategy spare parts of each factory and unit distribution data of each factory, and respectively updating an installation data table and a unit distribution table, wherein the installation data table comprises codes of strategy spare parts which are installed, factory numbers which are applied, unit numbers which are installed, the number of each unit which is installed and the first installation year; the unit distribution table comprises the year, the factory number and the number of the operating units;

and/or the failure probability calculating step comprises the following steps:

periodically and respectively calculating the annual failure probability of each replacement type of each spare part type according to the running pile number of each spare part type and the replacement number corresponding to each replacement type in a specific time period, and updating a second failure probability table, wherein the second failure probability table comprises: spare part type, replacement type, annual failure probability;

7. The method for analyzing the failure probability of a strategic spare part according to claim 6, further comprising:

an output step: and outputting the queried annual failure probability.

8. The method of analyzing failure probability of a strategic spare part according to claim 7, wherein when said query request includes a code of a strategic spare part to be queried, said querying step comprises:

9. The method of analyzing failure probability of strategic spare parts according to claim 8, wherein querying said second failure probability table for corresponding annual failure probabilities comprises:

10. A system for failure probability analysis of a strategic spare part, comprising a processor, characterized in that the processor, when executing a stored computer program, implements the steps of the method for failure probability analysis of a strategic spare part according to any of claims 1-9.