CN105404940A - Maintenance resource prediction method for ship usage stage - Google Patents

Abstract

The present invention relates to a maintenance resource prediction method for a ship usage stage. The method comprises: receiving collected key input information by a terminal; performing, by the terminal, a maintenance activity frequency prediction and a maintenance resource prediction of a multi-source maintenance activity according to the key input information, to obtain a requirement type and a quantity of a consumable maintenance resource, and a requirement of occupied time of an occupied maintenance resource; and reporting the predicted requirement type and quantity of the consumable maintenance resource, and the requirement of the occupied time of the occupied maintenance resource to a server, and accordingly, calling a correspondingly required maintenance resource. According to the maintenance resource prediction method for the ship usage stage, an automatic computing pattern of a server terminal is used to provide a technical support for the maintenance resource prediction of the ship usage stage, thereby improving accuracy and increasing a matching degree between the maintenance resource and the requirement.

Description

A kind of Maintenance Resources Prediction method towards boats and ships operational phase

Technical field

The present invention relates to maintenance of the vessel technical field, particularly relate to a kind of Maintenance Resources Prediction method towards boats and ships operational phase.

Background technology

Maintenance Resource is one of important influence factor of boats and ships operational phase, Maintenance Resource carry whether sufficient, utilization factor height directly have influence on boats and ships whether can complete regulation navigational duty, reduce life cycle management support cost.The accurate estimation of Maintenance Resource demand requires guarantee boats and ships mission sustainability, reduce spare parts purchasing amount, reduction managerial cost are significant.The object of Maintenance Resource estimation is exactly effectively utilize the historical data in boats and ships use procedure, in conjunction with the requirement of boats and ships existing Support Resource charging capacity, provide the estimated value of resource required for multinomial maintenance, and in conjunction with boats and ships mission requirements provide boats and ships sail before Maintenance Resource estimation, for technical foundation is established in the accurate estimation realizing Maintenance Resource.

Maintenance Resource, namely the spare part in boats and ships use procedure, consumables, manpower personnel, support equipment, support facility etc., and according to the feature that maintenance of the vessel resource uses in maintenance, from Maintenance Resource estimation angle Maintenance Resource can be divided into two large classes: consumption-type resource with take type resource.

Ship for civil use is in whole world navigation process, emphasis makes the continual navigation of boats and ships under the prerequisite ensureing security, namely its ratio of operation time to total time of a ship and navigation rate is made to maximize, in order to reach such target, boats and ships need to carry out corresponding maintenance activity to maintain the state of the art of boats and ships and each equipment usually, and Maintenance Resource is the necessary condition of carrying out these maintenance activities.

China's boats and ships are when the whole world is navigated by water, be subject to resource supply expensive, the restrictions such as poor in timeliness, Maintenance Resource is estimated then more important, if Maintenance Resource estimation is not enough, then can cause shortage of resources, the equipment that affects recovers, even can produce pernicious hang-up time serious to suspend, reduce production capacity and the efficiency of Shipping; On the contrary, if Maintenance Resource estimation is excessive, then Maintenance Resource can be caused to overstock, increase the storage loss etc. of Maintenance Resource under severe sea condition, production cost is increased, production efficiency reduction.

At present, before boats and ships sail, turbine department need report and load demand suggestion with ship standby redundancy, the method adopted is relatively single, as normally relied on the experience i.e. mode of " bat head ", accuracy rate is low, cause formulated often exceeding with ship Maintenance Resource charging capacity inventory or lower than its actual demand, cause the significant wastage of Maintenance Resource.

Summary of the invention

In view of above-mentioned analysis, the present invention aims to provide a kind of Maintenance Resources Prediction method towards boats and ships operational phase, in order to solve the problem of the accuracy rate existed in prior art low and Maintenance Resource waste.

Object of the present invention is mainly achieved through the following technical solutions:

A kind of Maintenance Resources Prediction method towards boats and ships operational phase of the present invention, comprising:

The key input information compiled by terminal;

Terminal carries out the Maintenance Resources Prediction of the prediction of maintenance number of times and multi-source maintenance according to described key input information, obtains demand type and the quantity of consumption-type Maintenance Resource, and takies the demand of type Maintenance Resource occupied time;

To demand type and the quantity of the consumption-type Maintenance Resource obtained be predicted, and take the demand of type Maintenance Resource occupied time, and report server, and call the Maintenance Resource of corresponding demand accordingly.

Further, described key input information comprises: mission requirements, comprises task time and task intensity; Maintenance kind and frequency; Relation between maintenance and Maintenance Resource, the i.e. occupied quantity of consumption-type resource in a certain maintenance, and take the occupied time of type resource in certain maintenance; The attribute of Maintenance Resource self.

Further, whether be preplanned characteristic according to maintenance, described maintenance if comprising: preventative maintenance activity and temporary repair activity.

Further, if described maintenance is preventative maintenance activity, then the forecasting process of preventative maintenance activity number of times specifically comprises:

For the preventative maintenance dividing the cycle according to calendar time, preventative maintenance number of times computing formula is:

n _PMSEi＝T/t _i

In formula: n _pMSEirepresent the number of times of preventative maintenance activity i; T represents the calendar time belonging to task; t _irepresent the preventative maintenance interval in units of calendar time;

For the preventative maintenance dividing the cycle according to time used, preventative maintenance number of times computing formula is:

n _PMSEi＝H/h _i

In formula: n _pMSEirepresent the number of times of preventative maintenance activity i; H represents the service time in task time; H _irepresent the preventative maintenance interval in units of service time;

For according to the periodic preventative maintenance of actual access times, preventative maintenance number of times computing formula is:

n _PMSEi＝K/k _i

In formula: n _pMSEirepresent the number of times of preventative maintenance activity i; K represents total access times in task time; k _irepresent the preventative maintenance interval in units of access times.

Further, if described maintenance is provisional maintenance, then the forecasting process of provisional maintenance number of times specifically comprises:

The frequency that fault and false-alarm problem occur can quantize with failure rate and false alarm rate; And for misjudgement failure frequency, suppose SRU _g,ifor LRU _iin be numbered the sub-product of g, represent all sub-product set of product i, order represent SRU _m,isRU during fault _n,ithe probability broken down, λ _m,irepresent SRU _m,ifailure rate, then analyze the SRU that causes of misjudgement failure _n,ithe frequency d of temporary repair activity _cMScomputing method:

$d_{CMS}={\mathrm{\Σ}}_{m\∈I_i^s}{P}_r\left\{{\mathrm{SRU}}_{n,i}\right|{\mathrm{SRU}}_{m,i}\}\·{\mathrm{\λ}}_{m,i}$

In conjunction with failure rate, false alarm rate, misjudgement failure frequency three kinds of situations, LRU _iprovisional maintenance items frequency computing method be:

$d_{{\mathrm{CMS}}_i}=A_{OR}\×{\mathrm{\θ}}_i\×N\×n\×({\mathrm{\λ}}_i+{\mathrm{\μ}}_i+{\mathrm{\ΣP}}_r\{{\mathrm{LRU}}_i|{\mathrm{LRU}}_j\}\·{\mathrm{\λ}}_j)/8760$

In formula: A _oRrepresent task time, unit is hour; θ _irepresent the operating ratio between i-th equipment must in office, the navigation rate of such as boats and ships; N indication equipment total quantity; N represents that equipment of the same type installs number; λ _irepresent the failure rate of i-th equipment; μ _irepresent the false alarm rate of i-th equipment; P _r{ LRU _i| LRU _jrepresent LRU _jlRU during fault _ithe probability of fault; λ _jrepresent the failure rate of a jth equipment.

Further, there are following three kinds of relations in described multi-source maintenance:

Ordinal relation, namely multiple maintenance order is carried out;

Concurrency relation, namely multiple maintenance is completed by many people simultaneously;

, namely there is multiple possible maintenance to certain equipment in trial relation, and each maintenance can occur with certain probability.

Further, if described multi-source maintenance is ordinal relation, then

Take type resource: the man-hour of similar resource is added, and resource requirement maximal value is the maximal value in each maintenance; If there is the maintenance of n order, take type Maintenance Resource for jth class, the holding time in i-th maintenance is T _ij, the demand of the jth class Maintenance Resource in i-th maintenance is N _ij, then jth class takies the total holding time T of type Maintenance Resource _j, aggregate demand N _jfor:

$T_j=\underset{i}{\overset{n}{\Σ}}{T}_{ij}$

N _j＝max(N _1j，N _2j，......，N _nj)

Consumption-type resource: the quantity of similar resource is added, if there is the maintenance of n order, for kth class consumption-type resource, the demand of kth class consumption-type Maintenance Resource in i-th maintenance is N _ik, then the aggregate demand N of kth class consumption-type resource _kfor:

$N_k=\underset{i}{\overset{n}{\Σ}}{N}_{ik}.$

Further, if described multi-source maintenance is concurrency relation, then

Take type resource: if need to carry out n maintenance simultaneously, in i-th maintenance, jth class takies the holding time of type Maintenance Resource is T _ij, the jth class Maintenance Resource demand in i-th maintenance is N _ij, then jth class takies the total holding time T of type Maintenance Resource _j, maximum aggregate demand N _jmax, minimum aggregate demand N _jminfor:

$T_j=\underset{i}{\overset{n}{\Σ}}{T}_{ij}$

$N_{jmax}=\underset{i}{\overset{n}{\Σ}}{N}_{ij}$

N _jmin＝max(N ₁，N ₂，......，N _n)

Consumption-type resource: the quantity of similar Maintenance Resource is added, and namely for kth class consumption-type Maintenance Resource, if need to carry out n maintenance simultaneously, the demand of kth class consumption-type Maintenance Resource in i-th maintenance is N _ik, then the aggregate demand N of kth class consumption-type resource _kfor:

$N_k=\underset{i}{\overset{n}{\Σ}}{N}_{ik}.$

Further, if described multi-source maintenance is trial relation, then

Take type resource: if there is n maintenance in trial relation, the frequency of i-th maintenance generation is f _i, in i-th maintenance, jth class takies the holding time of type Maintenance Resource is T _ij, in i-th maintenance, the demand of jth class Maintenance Resource is N _ij, then jth class takies the total holding time T of type resource _j, aggregate demand N _jfor:

$T_j=\underset{i}{\overset{n}{\Σ}}{f}_i{T}_{ij}$

$N_j=\underset{i}{\overset{n}{\Σ}}{f}_i{N}_{ij}$

Consumption-type resource: the quantity of similar resource is added, namely for kth class consumption-type Maintenance Resource, if there is n the maintenance attempted, the frequency of i-th maintenance generation is f _i, the demand of kth class consumption-type Maintenance Resource in i-th maintenance is N _ik, then the aggregate demand N of kth class consumption-type resource _kfor:

$N_k=\underset{i}{\overset{n}{\Σ}}{f}_i{N}_{ik}.$

Further, repair active resource prediction according to following formula to multidimensional to revise:

In formula: represent the net result of the prediction of the i-th class Maintenance Resource; N _irepresent the tentative prediction result of the i-th class Maintenance Resource; n _ijrepresent the demand of the i-th class Maintenance Resource in a jth maintenance.

Beneficial effect of the present invention is as follows:

The present invention provides technical support by this robotization account form of server terminal for the Maintenance Resources Prediction of boats and ships operational phase, improves accuracy rate, adds the matching degree of Maintenance Resource and demand.

Other features and advantages of the present invention will be set forth in the following description, and, becoming apparent from instructions of part, or understand by implementing the present invention.Object of the present invention and other advantages realize by structure specifically noted in write instructions, claims and accompanying drawing and obtain.

Accompanying drawing explanation

Fig. 1 is the schematic flow sheet of method described in the embodiment of the present invention.

Embodiment

Specifically describe the preferred embodiments of the present invention below in conjunction with accompanying drawing, wherein, accompanying drawing forms the application's part, and together with embodiments of the present invention for explaining principle of the present invention.

As shown in Figure 1, Fig. 1 is the schematic flow sheet of method described in the embodiment of the present invention, specifically can comprise:

Step 101: the key input information compiled by computing machine;

In order to predict accurately Maintenance Resource quantity, need to compile key input information, mainly containing:

Mission requirements, comprise task time and task intensity;

Maintenance kind and frequency;

Relation between maintenance and Maintenance Resource, the i.e. occupied quantity of consumption-type resource in a certain maintenance, and take the occupied time of type resource in certain maintenance;

The attribute of Maintenance Resource self, as the consumption rate of consumption-type resource in a certain maintenance, and the operable time etc. in the taking property resource units time.

Step 102: computing machine carries out the prediction of maintenance number of times according to task time and task intensity;

Step 103: according to task time and task intensity, and maintenance kind and frequency, relation between maintenance and Maintenance Resource and Maintenance Resource self attribute, carry out the Maintenance Resources Prediction of multi-source maintenance, obtain demand type and the quantity of consumption-type Maintenance Resource, and take the demand of type Maintenance Resource occupied time.

Step 104: will demand type and the quantity of the consumption-type Maintenance Resource obtained be predicted, and take the demand of type Maintenance Resource occupied time, and report server, and call the Maintenance Resource of corresponding demand accordingly.

Below respectively the Maintenance Resources Prediction of maintenance quantitative forecast and multi-source maintenance is described in detail.

(1) whether be preplanned characteristic according to maintenance, maintenance can be divided into preventative maintenance activity and temporary repair movable, respectively its frequency is predicted below.

(1) preventative maintenance activity quantitative forecast

Preventative maintenance activity refers to that those are in the interior maintenance that plans sth. ahead, usually its number of times directly can be determined by the cycle of preventative maintenance, but for different device objects, the division of preventative maintenance cycle of activity has three kinds of foundations usually: take calendar time as foundation, being foundation with service time, take access times as foundation.For different demarcation foundation, the movable number of times account form of preventative maintenance is as follows:

For the preventative maintenance dividing the cycle according to calendar time, preventative maintenance number of times computing formula is:

n _PMSEi＝T/t _i

In formula:

-n _pMSEirepresent the number of times of preventative maintenance activity i;

-T represents the calendar time belonging to task;

-t _irepresent the preventative maintenance interval in units of calendar time.

For the preventative maintenance dividing the cycle according to time used, preventative maintenance number of times computing formula is:

n _PMSEi＝H/h _i

In formula:

-n _pMSEirepresent the number of times of preventative maintenance activity i;

-H represents the service time in task time;

-H _irepresent the preventative maintenance interval in units of service time.

For according to the periodic preventative maintenance of actual access times, preventative maintenance number of times computing formula is:

n _PMSEi＝K/k _i

In formula:

-n _pMSEirepresent the number of times of preventative maintenance activity i;

-K represents total access times in task time;

-k _irepresent the preventative maintenance interval in units of access times.

(2) provisional maintenance quantitative forecast

Provisional maintenance refers to that those are in unscheduled maintenance activity.Its occurrence frequency mainly affects by the factor such as fault characteristic, maintainability of equipment.Under normal circumstances, the failure rate of product determines the frequency of provisional maintenance; In addition, because localization of fault is forbidden the false-alarm that causes non-faulting product being torn open to situation by mistake, or cause current production generation misjudgement failure etc. due to other products fault, all can produce provisional maintenance.Therefore, the calculating of the frequency of provisional maintenance need be considered from three aspects, that is: fault, false-alarm, misjudgement failure.

The frequency that fault and false-alarm problem occur can quantize with failure rate and false alarm rate; And for misjudgement failure frequency, suppose SRU _g,ifor LRU _iin be numbered the sub-product of g, represent all sub-product set of product i, order represent SRU _m,isRU during fault _n,ithe probability broken down, λ _m,irepresent SRU _m,ifailure rate, then analyze the SRU that causes of misjudgement failure _n,ithe frequency d of temporary repair activity _cMScomputing method:

$d_{CMS}={\mathrm{\Σ}}_{m\∈I_i^s}{P}_r\left\{{\mathrm{SRU}}_{n,i}\right|{\mathrm{SRU}}_{m,i}\}\·{\mathrm{\λ}}_{m,i}$

In conjunction with failure rate, false alarm rate, misjudgement failure frequency three kinds of situations, LRU _iprovisional maintenance items frequency computing method be:

$d_{{\mathrm{CMS}}_i}=A_{OR}\×{\mathrm{\θ}}_i\×N\×n\×({\mathrm{\λ}}_i+{\mathrm{\μ}}_i+{\mathrm{\ΣP}}_r\{{\mathrm{LRU}}_i|{\mathrm{LRU}}_j\}\·{\mathrm{\λ}}_j)/8760$

In formula:

-A _oRrepresent task time, unit is hour;

-θ _irepresent the operating ratio between i-th equipment must in office, the navigation rate of such as boats and ships;

-N indication equipment total quantity;

-n represents that equipment of the same type installs number;

-λ _irepresent the _ithe failure rate of individual equipment;

-μ _irepresent the _ithe false alarm rate of individual equipment;

-P _r{ LRU _i| LRU _jrepresent LRU _jlRU during fault _ithe probability of fault;

-λ _jrepresent the failure rate of a jth equipment.

-LRU: LRU, can in working site from the unit that system or device are dismantled or changed after pointing out fault;

-SRU: internal field replaceable units, in workshop (Relay or Base Level), from the unit that LRU dismantles or changes, generally can not directly can change after pointing out fault at the scene.

(2) Maintenance Resources Prediction of multi-source maintenance

In maintenance implementation process, may need to arrange multinomial maintenance job simultaneously, and the difference of maintenance job sequential relationship, produce larger impact by the quantity required of Maintenance Resource.Following three kinds of relations may be there are in maintenance:

ordinal relation, namely multiple maintenance order is carried out, and completes the maintenance of multiple equipment as single;

concurrency relation, namely multiple maintenance is completed by many people simultaneously;

, namely there is multiple possible maintenance to certain equipment in trial relation, and each maintenance can occur with certain probability, namely may take different maintenance modes.

For different maintenance relations and different Maintenance Resource types, the method for corresponding Maintenance Resources Prediction is as follows:

(1) for the Maintenance Resources Prediction of ordinal relation

Take type resource: the man-hour of similar resource is added, and resource requirement maximal value is the maximal value in each maintenance.If there is the maintenance of n order, take type Maintenance Resource for jth class, the holding time in i-th maintenance is T _ij, the demand of the jth class Maintenance Resource in i-th maintenance is N _ij, then jth class takies the total holding time T of type Maintenance Resource _j, aggregate demand N _jfor:

$T_j=\underset{i}{\overset{n}{\Σ}}{T}_{ij}$

N _j＝max(N _1j，N _2j，......，N _nj)

Consumption-type resource: the quantity of similar resource is added.If there is the maintenance of n order, for kth class consumption-type resource, the demand of kth class consumption-type Maintenance Resource in i-th maintenance is N _ik, then the aggregate demand N of kth class consumption-type resource _kfor:

$N_k=\underset{i}{\overset{n}{\Σ}}{N}_{ik}$

(2) for the Maintenance Resources Prediction of concurrency relation

Take type resource: the man-hour taking type resource now constitutes ordinal relation, computing method are see a upper joint; If need to carry out n maintenance simultaneously, in i-th maintenance, jth class takies the holding time of type Maintenance Resource is T _ij, the jth class Maintenance Resource demand in i-th maintenance is N _ij, then jth class takies the total holding time T of type Maintenance Resource _j, maximum aggregate demand N _jmax, minimum aggregate demand N _jminfor:

$T_j=\underset{i}{\overset{n}{\Σ}}{T}_{ij}$

$N_{jmax}=\underset{i}{\overset{n}{\Σ}}{N}_{ij}$

N _jmin＝max(N ₁，N ₂，......，N _n)

Consumption-type resource: the quantity of similar Maintenance Resource is added.Namely for kth class consumption-type Maintenance Resource, if need to carry out n maintenance simultaneously, the demand of kth class consumption-type Maintenance Resource in i-th maintenance is N _ki, then N _ik, then the aggregate demand N of kth class consumption-type resource _kfor:

$N_k=\underset{i}{\overset{n}{\Σ}}{N}_{ik}$

(3) for the Maintenance Resources Prediction of the relation of trial

Trial relation multidimensional needs the probability by each maintenance occurs to take into account when repairing active resource prediction, is namely weighted.Can decimal place be produced in this process, wouldn't carry out rounding process, avoid the accuracy affecting resources.

Take type resource: if there is n maintenance in trial relation, the frequency of i-th maintenance generation is f _i, in i-th maintenance, jth class takies the holding time of type Maintenance Resource is T _ij, in i-th maintenance, the demand of jth class Maintenance Resource is N _ij, then jth class takies the total holding time T of type resource _j, aggregate demand N _jfor:

$T_j=\underset{i}{\overset{n}{\Σ}}{f}_i{T}_{ij}$

$N_j=\underset{i}{\overset{n}{\Σ}}{f}_i{N}_{ij}$

Consumption-type resource: the quantity of similar resource is added, namely for kth class consumption-type Maintenance Resource, if there is n the maintenance attempted, the frequency of i-th maintenance generation is f _i, the demand of kth class consumption-type Maintenance Resource in i-th maintenance is N _ik, then the aggregate demand N of kth class consumption-type resource _kfor:

$N_k=\underset{i}{\overset{n}{\Σ}}{f}_i{N}_{ik}$

(4) multidimensional repaiies active resource forecast value revision

In the process that calculates at multiple resource becomes, there is the maintenance of trial relation.Decimal may be produced by the method for weighting summation or not meet the situation of single maintenance resource requirement, so finally also need to revise above-mentioned situation, just can obtain predicting the outcome of Maintenance Resource comparatively accurately:

In formula:

-- represent the net result of the prediction of the i-th class Maintenance Resource;

--N _irepresent the tentative prediction result of the i-th class Maintenance Resource;

--n _ijrepresent the demand of the i-th class Maintenance Resource in a jth maintenance.

In sum, embodiments provide a kind of Maintenance Resources Prediction method towards boats and ships operational phase, by the maintenance mode that runs into for boats and ships operational phase and maintenance type, in conjunction with the mission requirements, maintenance attribute, Maintenance Resource attribute etc. of boats and ships, give a kind of Maintenance Resources Prediction method towards boats and ships operational phase, by this robotization account form of server terminal for the Maintenance Resources Prediction of boats and ships operational phase provides technical support, improve accuracy rate, add the matching degree of Maintenance Resource and demand.

Compared to the existing method based on experience and the method based on design and evaluation session information, the embodiment of the present invention is for the maintenance of boats and ships operational phase and spare part resources characteristic, give the Maintenance Resource predictor method under mission bit stream input, effectively can mate boats and ships operational phase for the consumption-type such as spare part, oil plant resource, and personnel, equipment etc. take the demand of estimating of the resources requirements such as type resource, and provide corresponding resource and estimate conclusion, instruct boats and ships to carry out the preliminary work of Maintenance Resource.

It will be understood by those skilled in the art that all or part of flow process realizing above-described embodiment method, the hardware that can carry out instruction relevant by computer program has come, and described program can be stored in computer-readable recording medium.Wherein, described computer-readable recording medium is disk, CD, read-only store-memory body or random store-memory body etc.

The above; be only the present invention's preferably embodiment, but protection scope of the present invention is not limited thereto, is anyly familiar with those skilled in the art in the technical scope that the present invention discloses; the change that can expect easily or replacement, all should be encompassed within protection scope of the present invention.

Claims (10)

1., towards a Maintenance Resources Prediction method for boats and ships operational phase, it is characterized in that, comprising:

The key input information compiled by terminal;

Terminal carries out the Maintenance Resources Prediction of the prediction of maintenance number of times and multi-source maintenance according to described key input information, obtains demand type and the quantity of consumption-type Maintenance Resource, and takies the demand of type Maintenance Resource occupied time;

To demand type and the quantity of the consumption-type Maintenance Resource obtained be predicted, and take the demand of type Maintenance Resource occupied time, and report server, and call the Maintenance Resource of corresponding demand accordingly.

2. method according to claim 1, is characterized in that, described key input information comprises: mission requirements, comprises task time and task intensity; Maintenance kind and frequency; Relation between maintenance and Maintenance Resource, the i.e. occupied quantity of consumption-type resource in a certain maintenance, and take the occupied time of type resource in certain maintenance; The attribute of Maintenance Resource self.

3. method according to claim 1 and 2, is characterized in that,

Whether is preplanned characteristic according to maintenance, described maintenance comprises: preventative maintenance activity and temporary repair movable.

4. method according to claim 3, is characterized in that, if described maintenance is preventative maintenance activity, then the forecasting process of preventative maintenance activity number of times specifically comprises:

For the preventative maintenance dividing the cycle according to calendar time, preventative maintenance number of times computing formula is:

n _PMSEi＝T/t _i

In formula: n _pMSEirepresent the number of times of preventative maintenance activity i; T represents the calendar time belonging to task; t _irepresent the preventative maintenance interval in units of calendar time;

For the preventative maintenance dividing the cycle according to time used, preventative maintenance number of times computing formula is:

n _PMSEi＝H/h _i

In formula: n _pMSEirepresent the number of times of preventative maintenance activity i; H represents the service time in task time; h _irepresent the preventative maintenance interval in units of service time;

For according to the periodic preventative maintenance of actual access times, preventative maintenance number of times computing formula is:

n _PMSEi＝K/k _i

In formula: n _pMSEirepresent the number of times of preventative maintenance activity i; K represents total access times in task time; k _irepresent the preventative maintenance interval in units of access times.

5. method according to claim 3, is characterized in that, if described maintenance is provisional maintenance, then the forecasting process of provisional maintenance number of times specifically comprises:

The frequency that fault and false-alarm problem occur can quantize with failure rate and false alarm rate; And for misjudgement failure frequency, suppose SRU _g,ifor LRU _iin be numbered the sub-product of g, represent all sub-product set of product i, order represent SRU _m,isRU during fault _n,ithe probability broken down, λ _m,irepresent SRU _m,ifailure rate, then analyze the SRU that causes of misjudgement failure _n,ithe frequency d of temporary repair activity _cMScomputing method:

$d_{CMS}={\mathrm{\Σ}}_{m\∈I_i^s}{P}_r\left\{{\mathrm{SRU}}_{n,i}\right|{\mathrm{SRU}}_{m,i}\}\·{\mathrm{\λ}}_{m,i}$

In conjunction with failure rate, false alarm rate, misjudgement failure frequency three kinds of situations, LRU _iprovisional maintenance items frequency computing method be:

$d_{{\mathrm{CMS}}_i}=A_{OR}\×{\mathrm{\θ}}_i\×N\×n\×({\mathrm{\λ}}_i+{\mathrm{\μ}}_i+{\mathrm{\ΣP}}_r\{{\mathrm{LRU}}_i\left|{\mathrm{LRU}}_j\right\}\·{\mathrm{\λ}}_j)/8760$

In formula: A _oRrepresent task time, unit is hour; θ _irepresent the operating ratio between i-th equipment must in office; N indication equipment total quantity; N represents that equipment of the same type installs number; λ _irepresent the failure rate of i-th equipment; μ _irepresent the false alarm rate of i-th equipment; P _r{ LRU _i| LRU _jrepresent LRU _jlRU during fault _ithe probability of fault; λ _jrepresent the failure rate of a jth equipment.

6. method according to claim 2, is characterized in that, described multi-source maintenance exists following three kinds of relations:

Ordinal relation, namely multiple maintenance order is carried out;

Concurrency relation, namely multiple maintenance is completed by many people simultaneously;

, namely there is multiple possible maintenance to certain equipment in trial relation, and each maintenance can occur with certain probability.

7. method according to claim 6, is characterized in that, if described multi-source maintenance is ordinal relation, then

Take type resource: the man-hour of similar resource is added, and resource requirement maximal value is the maximal value in each maintenance; If there is the maintenance of n order, take type Maintenance Resource for jth class, the holding time in i-th maintenance is T _ij, the demand of the jth class Maintenance Resource in i-th maintenance is N _ij, then jth class takies the total holding time T of type Maintenance Resource _j, aggregate demand N _jfor:

$T_j=\underset{i}{\overset{n}{\Σ}}{T}_{ij}$

N _j＝max(N _1j，N _2j，......，N _nj)

Consumption-type resource: the quantity of similar resource is added, if there is the maintenance of n order, for kth class consumption-type resource, the demand of kth class consumption-type Maintenance Resource in i-th maintenance is N _ik, then the aggregate demand N of kth class consumption-type resource _kfor:

$N_k=\underset{i}{\overset{n}{\Σ}}{N}_{ik}.$

8. method according to claim 6, is characterized in that, if described multi-source maintenance is concurrency relation, then

Take type resource: if need to carry out n maintenance simultaneously, in i-th maintenance, jth class takies the holding time of type Maintenance Resource is T _ij, the jth class Maintenance Resource demand in i-th maintenance is N _ij, then jth class takies the total holding time T of type Maintenance Resource _j, maximum aggregate demand N _jmax, minimum aggregate demand N _jminfor:

$T_j=\underset{i}{\overset{n}{\Σ}}{T}_{ij}$

$N_{jmax}=\underset{i}{\overset{n}{\Σ}}{N}_{ij}$

N _jmin＝max(N ₁，N ₂，......，N _n)

Consumption-type resource: the quantity of similar Maintenance Resource is added, and namely for kth class consumption-type Maintenance Resource, if need to carry out n maintenance simultaneously, the demand of kth class consumption-type Maintenance Resource in i-th maintenance is N _ik, then the aggregate demand N of kth class consumption-type resource _kfor:

$N_k=\underset{i}{\overset{n}{\Σ}}{N}_{ik}.$

9. method according to claim 6, is characterized in that, if described multi-source maintenance is trial relation, then

Take type resource: if there is n maintenance in trial relation, the frequency of i-th maintenance generation is f _i, in i-th maintenance, jth class takies the holding time of type Maintenance Resource is T _ij, in i-th maintenance, the demand of jth class Maintenance Resource is N _ij, then jth class takies the total holding time T of type resource _j, aggregate demand N _jfor:

$T_j=\underset{i}{\overset{n}{\Σ}}{f}_i{T}_{ij}$

$N_j=\underset{i}{\overset{n}{\Σ}}{f}_i{N}_{ij}$

Consumption-type resource: the quantity of similar resource is added, namely for kth class consumption-type Maintenance Resource, if there is n the maintenance attempted, the frequency of i-th maintenance generation is f _i, the demand of kth class consumption-type Maintenance Resource in i-th maintenance is N _ik, then the aggregate demand N of kth class consumption-type resource _kfor:

$N_k=\underset{i}{\overset{n}{\Σ}}{f}_i{N}_{ik}.$

10. method according to claim 1, is characterized in that, repaiies active resource prediction revise according to following formula to multidimensional:

In formula: represent the net result of the prediction of the i-th class Maintenance Resource; N _irepresent the tentative prediction result of the i-th class Maintenance Resource; n _ijrepresent the demand of the i-th class Maintenance Resource in a jth maintenance.