Predication and Optimization of Maintenance Resources for Weapon System

I.J. Intelligent Systes and Applications, 20, 5, -9 Published Online August 20 in MECS (http://www.ecs-press.org/) Predication and Optiization of Maintenance Resources for Weapon Syste Yabin Wang Departent of Equipent Coand and Manageent in Mechanical Engineering College, Shijiazhuang, P.R.China wangyabin23@63.co Abstract Maintenance resources are iportant part of the aintenance support syste. The whole efficiency of weapon syste is directly affected by the allocation of aintenance resources. Joint support for weapon syste of ulti-kinds of equipents is the ain fashion of aintenance support in the future. However, there is a lack of the efficiency tools and ethods for predication and optiization of weapon syste aintenance resources presently. For the prediction requireent of aintenance resources of weapon syste, the priary infection factors for the requireent of aintenance resources were analyzed. According to the different characteristics of aintenance resources and the analysis for the traditional classification ethods, a kind of classification for weapon syste s aintenance resources was given. A prediction flow for the aintenance resources requireent was designed. Four kinds of odels for predicting the aintenance resources requireent in a weapon syste were designed and described in detail. In this paper, approaches of the optial selection fro the siulation schees and reverse siulation for the resources allocation optiization were analyzed; soe optiization odels for aintenance resources such as spare parts and personnel were constructed. Further ore, an optiization and decision-aking syste was not only designed but also developed. At last, an exaple was presented, which proved the prediction and optiization ethods were applicability and feasibility, the decision-aking syste for the optiization of aintenance resources was a supportable and efficient tool. Index Ters-prediction, aintenance resources, odeling, optiization, decision-making, siulation, weapon syste I. INTRODUCTION Maintenance resources are ain assurance of equipent readiness and continuous battle effectiveness. United capaign is the ain odel under high technology conditions in the future. With the proinent characteristic, such as high technology, high speed and high consuption [], the traditional support odel is not adapted to the battle requireent in the future. Hence, Joint support for weapon syste of ulti-kinds of equipents is the ain fashion of aintenance support in ties to coe. However, the forecasting and optiization of aintenance resources deands for weapon syste has becoing ore and ore difficult, along with the iproveent of technology and coplexity of new type equipent, and with the augentation of training tie and intensity. Therefore, it has realistic significance to achieve the accurate forecasting and the optiu allocation of aintenance resources through introducing science technology, in order to iprove the battle effectiveness and decrease the aintenance support cost. Soe researchers have worked in the field of predicting and optiizing aintenance resources. Reference [2] has studied the optiization odels for spare parts and a ath odel for aintenance and a service odel was presented after analyzing the ipact factors for spare parts allocation. Reference [3] has studied the optiization for two level spare parts, and given soe odels for inventory decision. Reference [4] has studied personnel need for equipent aintenance based on queue theory. Reference [5] has studied the allocation odels for Manpower on wartie. Although there are any articles written about the prediction of aintenance resources requireents, ost of the took a single kind of equipent as the object or aied at a group of equipent of the sae kind [6, 7, 8, and 9]. In other words, few people took weapon syste as an object to study the requireent of aintenance resource for weapon syste is ade up of any types of equipents which have different configurations, with different tasks and different aintenance resources consuption. The prediction for its resource requireents is quite coplicated. How to synthetically predict all the ain resources and build an optiization and decision-aking syste has seldo entioned or studied. Hence, it is necessary to design and realize a universal optiization and decision-aking syste of aintenance resources for weapon syste. II. REQUIREMENT ANALYSIS A. Main influence factors for resources requireent Equipent aintenance resources is a general designation of anpower, aterial, outlay, inforation and tie, which are indispensable to equipent aintenance and will be consued or eployed in the aintenance support process [0]. The ain influence factors include the ipleent tie for ission, the replaceable unit s fault rate, the preventive aintenance interval period, the circustance infection factors, the personnel diathesis of equipent operation and aintenance. )The ipleent tie for ission. This factor eans the practice runtie for the weapon syste under a certain task, which could be the calendar tie, shooting nubers and so on. Generally, the ipleent tie is presented by

2 Predication and Optiization of Maintenance Resources for Weapon Syste the coander fro the capaign presupposition or training task. In order to calculate conveniently, its needs to converse the different unit tie to the sae unit tie before odeling. 2)The fault rate of replaceable unit. The fault rate of replaceable unit is the design characteristic of equipent itself. This characteristic has a direct influence to the aintenance resources consuing []. Currently, the life-span of electron products obeys exponent distribution, while enginery or achine electricity products obey weibull distribution. Hence, the fault rate of each replaceable unit can be calculated by the fault distribution. 3)The preventive aintenance interval period. This factor directly deterine the aintenance cycle of equipent preventive aintenance, which could be gained fro the RCM general outline or the distribution table of aintenance task. 4)The circustance infection factors. The consuing of aintenance resources will be different for the different circustance. Teperature, huidity, sand blown by wind, and libration have a biggish infection to electron product, next is the non-electron product, while the circustance have a least ipact to etal product [2]. 5)Repair influence factors. After repair, the fault unit can be the aintenance spares to be used. This factor is ainly considering the influence of aintenance resources consuing by the repairable ratio after the unit fault. 6 ) The diathesis of equipent operation and aintenance personnel. The personnel diathesis has a great influence to the resources consuing. If the equipent operation and aintenance personnel have a high diathesis, the equipent would be having a good care and the accident probability will be sall. Otherwise, if the equipent operation or aintenance personnel have a low diathesis, the equipent would be having a worse care and the accident probability will be big. B. Maintenance resources classification According to the characteristic of unit support, aintenance resources can be classed as currency resources and special resources. Currency resources are those resources which can support any kinds of equipent, such as tyre, oil plants, and standard parts of an apparatus. Special resources are those resources which can only used to a certain kind of equipent, such as xx kind of special charger. Otherwise, according to the resources being consued or being engaged, the resources can be classified as consued resources and engaged resources. Engaged resources eans aintenance resources are engaged in the aintenance support process all along. When the corresponding activity closed, the support resources will in idle state, such as support facility, tools, establishent, anpower, and technology datu. Consued resources eans the aintenance resources are dissipative gradually along with the tie in aintenance support process. Coonly, the resources such as oil, clean aterial belong to consued aterial. For the repairable parts, although they are rehabilitated to be use tie after tie, the repair nuber is restricted. Hence, we can regard the as consued resources. Synthesized the two kinds of classification ethods above, and cobined with the support requireent of weapon syste, we plot aintenance resources as the follow four parts. They are consued special resources, consued current resources, engaged special resources, and engaged current resources, which can be shown as Fig.. Figure. Maintenance resources classification of weapon syste Thereinto, the Ⅰ and Ⅱ resources are all consued aintenance resources, which need deployed periodically. These resources are difficult to predict for its strong rando city. The Ⅲ and Ⅳ resources are all engaged aintenance resources, which are coonly equipped while the support syste being built. These resources needed not to be deployed periodical for the requireent of the are relatively fixed up. C. The prediction process for resources requireent Figure 2. Prediction process for aintenance resources requireent The scientific predication of aintenance resources requireent is the precondition of aintenance resources deployent. According to the training tasks in peacetie, we can confir the type and nuber of the training weapon syste. Moreover, basis on the configuration inforation of each equipent, we could ake the ain replaceable units certain, which are concerned with the training task. The following step is to predict the fault and

Predication and Optiization of Maintenance Resources for Weapon Syste 3 aintenance requireents for the key parts. This prediction is very difficult and iportant and we should use the reliability paraeters and equipent fault ode. At last, according to the aintenance process inforation and the prediction odels, the requireent nuber of each resource could be predicted. The concrete process is shown as Fig. 2. III. PREDICTION MODELS A. Hypothesis and sybol explain In this study, we hypothesis that all kinds of equipents have the sae equipping tie, and the repair style are all replace unit repair. What s ore, we suppose that all kinds of resources are abundance, and there is no conflict proble about resources. In this paper, the sybols signification can be explained as follows: L i eans the quantity of equipent i. f Cij eans the reparability aintenance frequency of replaceable unit j in equipent i. f pij eans the prevent aintenance frequency of replaceable unit j in equipent i. f ij (t) eans fault density function of replaceable unit j in equipent i. T eans the task tie of the weapon syste. represents the ite nuber of the training task. α i is the proportion between the training ties of task k for equipent i and the total training tie. X kij represents the consued quantity of spare parts, while equipent i unit j being repaired under the training task k. P kij is the probability of spare parts being consued when equipent i unit j being repaired under the training task.if this probability is, that eans this repair ust be replaceable repair. If this probability is less than, that eans it ust be original unit repair. H ij is the circustance influence genes. In generally, the equipent operation circustance can be classified as good, iddle and bad three kinds. The circustance influence genes are,.05, and.5 correspondingly. W ij is the diathesis of equipent operation and aintenance personnel. According to the personnel status in our ary, the diathesis can be divided into excellence, all right, pass and fail, which with the influence genes are,.05,.5,.25 correspondingly. B. Prediction for theⅠresource In a period of tie, the average requireent S ij for the equipent i unit j can be denoted as follows:, 0 < Nij < S ij = () Nij +, Nij > fij(t) N ij = int[ Li α ikt ( + fpij) X kijpkijhkijwkij ] (2) k= f (t)d t ij t )if the life-span of replaceable unit obey exponent fij(t) distribution, then = λ = λ ( t), fij(t) dt t Therefore, N ij can be denoted as follows: N ij = int[ Li α ikt ( λij + f Pij) X kij Pkij H kijwkij ] (3) k= 2)if the life-span of replaceable unit obey weibull distribution, then t t ( ) exp[ ( ) ] fij( t) η η η t = = ( ) t f t j(t d u i ) t η η exp[ ( ) du] 0 η η ( t 0, η 0, > 0 ) Therefore, N ij can be denoted as follows: N ij = int[ L i k= ij t ij αikt( ( ) + fpij ) X ηij ηij (t 0, η 0, > 0) ij ij P kij kij Coonly, the frequency of preventive aintenance support active is directly confired by the preventive aintenance general outline or aintenance task distribution table. We should pay attention to the frequency unit in the calculate process. That is the frequency of preventive aintenance support active and the fault ratio of the replaceable unit ust be unified with the task tie T. C. Prediction for the Ⅱ resource The Ⅱ resource eans consued and current aintenance resources, we assue that there are n kinds of equipents need consue resources j, then the total requireent quantity of this resource can be denoted as S j. n, 0 < Nij < S = i= j n n + > Nij, Nij i= i= Engaged aintenances eans there are engaged by fault equipent and not consued in the support aintenance process, such as aintenance establishent, facility, and personnel. The requireent quantity is related to the frequency of aintenance task, aintenance type, aintenance process inforation, and its working tie in a unit tie. Take aintenance personnel as an exaple, each person can work 8 hours in one day. If we have calculated that the total workload for one kind of aintenance personnel is 20 hours, this personnel requireent nuber is 2.5. In the requireent prediction for this type resource, we suppose the equipent i participate in training task k, and unit j was supported. Therefore, aintenance resource q was engaged. The engaged tie is T ikjq, while the engaged quantity is R ikjq. The working tie for this resource is in one day. Then in this aintenance support process, the average requireent quantity for this resource is S iq H kij W, kij ] (4) (5), 0 < Niq S i q = (6) Niq +, Niq >

4 Predication and Optiization of Maintenance Resources for Weapon Syste Rs fij( t) Li αikt ( + f Pij) RikjqTikjqPk ihkijwkij j= k= = f j( t) dt t i N iq int (7) Tq D. Prediction for the Ⅳ resource These resources was engaged any ties in the aintenance support process, such as underpan repairan can repair not only arored equipent, but also ordnance equipent. We suppose that the equipent quantity is n and the unit j was supported. Then, the average requireent quantity for resource q can be expressed as S q., 0 < N q S q = (8) N q +, N q > n i Nq = int R i = j= k= Liα ikt( t fij( t) + f fij( t) dt T q Pij ) R T P H ikjq ikjq ki ikj W ikj (9) Personnel are the ain body of using and servicing equipent [3]. The nuber and the technology level of aintenance personnel is directly affect the aintenance efficiency and availability of the equipents. It is vital to ake the best use of all kinds of anpower and enhance the optiization for personnel outfit. 2) Optiization for spare parts Spare parts anageent is an iportant part of aintenance activity. Only have we deposit and provide spare parts scientifically, the aintenance task can be econoical and efficient. As any people know, Operation research has ade a sufficient effect in the optiization of spare parts [4]. However, dynaic prograing and Lagrange ethods are difficult to solve great odels and coplex probles, for the any leash conditions and rando factors. At the sae tie, the optiization for spare parts should consider the liitation of funds, The nuber and the technology level of aintenance personnel is directly affect the aintenance efficiency and availability of the equipents. It is vital to ake the best use of all kinds of anpower and enhance the optiization for personnel outfit. B. Principles for decision-aking ) Least cost principle IV. METHODS FOR DECISION-MAKING OF MAINTENANCE On condition of achieving certain availability, we RESOURCES should choose a aintenance allocation concept which cost is the least. A. Contents of aintenance resources optiization ) Optiization for anpower resource n α i C bi inc S = ( ) + C piα i + C α i + S Ui + S Li α itli + C ditli C jt j i= S U i- S Li + α T 2 (0) i Li j = Tb s.t. AS = A0 Tb + M + D C S Total aintenance cost for the equipent C P Price of spare parts C a Cost for once order C b Cost for spares stock in every hour C j Maintenance personnel cost for every an-hour S U The upper liit for spares stock S L The lower liit for spares stock T L Delay tie for ordering T j Man-hour for personnel j Tb ax AS = Tb + M + D n αi Cbi s.t. CS = Cpiα i + Cαi + S i= SU i-s Li + αitli 2 C. Process of decision-aking According to aintenance ethods for the failure parts, we disport the into three kinds (irreparable parts, repairable parts and need changing subsyste parts). For each kind, we have built the optiization odels for personnel and spare parts. Then we can ake an optiization decision process as follows. A S The syste s availability T b Mean tie between aintenances M Mean tie for aintenances D Mean delay tie 2) Biggest availability principle On condition of certain aintenance cost, we should ake the availability biggest. ( + S α T ) Ui () Li i Li + CdiTLi + C jtj C0 j = Firstly, we ust input aintenance support inforation, training plan, equipent organization and all units inforation Secondly, we ust ake a cost restriction for spare parts or personnel clearly, and then run the siulation syste, which can give us a lots of useful inforation about the resource requireent.

Predication and Optiization of Maintenance Resources for Weapon Syste 5 Thirdly, according to the restriction conditions, we can use Genetic Algorith optiization ethods to bring out an optiu concept about spares and personnel. Lastly, we can escalate the result and choose a proper aintenance allocation concept. We can see the whole process as Fig. 3. Figure 3. Process of decision-aking V. DESIGNS AND REALIZATION OF THE SOFTWARE SYSTEM A. The Main Frae of the Syste The Optiization and Decision-aking syste of Maintenance Resources is coposed of equipent inforation anageent syste, prediction of aintenance resources requireent by siulation syste and optiization allocation for resources syste. The ain frae of the syste is shown as Fig. 4. User Intercourse syste for Man & Machine Manageent syste for equipent inforation Prediction syste for requireent siulation Optiization syste for aintenance allocation Support Syste analysis Equipent odeling Support requireen t analysis Modeling and siulation Siulation data analysis Out put the Spares siulation optiizatio result n odeling Personnel optiizatio n odeling GA optiization and calculation Maintenance queue siulation odeling Figure 4. Main frae of the optiization and decision-aking syste B. Functional Design of Modules ) Manageent syste for equipent inforation. This syste ainly coplete support syste analysis, equipent syste odeling and requireent analysis for equipent support. What is ore, all the relation inforation and odels will be saved into database and odel bases, which can provide useful inforation for the prediction and optiization of resources. 2) Prediction syste for requireent siulation. In this syste, one function is odeling for the process of aintenance support, and records all kinds of useful data; an other function is to provide restriction inforation for spares and personnel optiization by the analysis of siulation data. The last function is that the syste can output the requireent inforation through graphs and tables and bring out availability inforation which are very useful for the decision-aker to ake a correctly and efficiency allocation. 3) Optiization syste for resources allocation. The ain function in this syste is to optiization spares and personnel according to spare optiization odeling and personnel optiization odeling. The optiization integrates with Genetic Algorith and aintenance queue siulation odels. C. Database Design According to the syste s requireent analysis and the ain Frae above, this paper have established the

6 Predication and Optiization of Maintenance Resources for Weapon Syste syste s database fraework, analyzed the relationship by using the latest database, designed the data table and defined the data types in each table, the aterial databases and data table are narrated as follows. ) Ite Manage Database Ite Integer Inforation Table. This table is ainly anage integer inforation of the siulation syste, which includes establish units, establish date, establish person, nae of the siulated units, equipent s type and nae. 2 Ite Manage Inforation Table. This table includes the aintenance levels, the nubers of units which subordinate to the siulated unit, the subordinate equipent s outfit nubers and training proportion of the equipent. 3 User Inforation Table. This table includes user s nae, password and type. 2)Equipent inforation database Equipent Structure Tree Inforation Table. This table ainly records the structure relationship between each subsyste and each repairable unit. 2 Repairable Unit s Inforation Table. This table ainly records all utuality inforation of repairable units, which involve unit nae, failure distribute type, aintenance level, aintenance strategy, aintenance interval tie, aintenance tie, aintenance personnel type and quantity. 3 Distribute Paraeter Table. This table records the distribute type and paraeters of all unit s life tie and aintenance tie. 4 Maintenance Personnel Inforation Table. The ID ark and nuber of the deanded aintenance personnel are recorded in this table. 5 Spare Parts and Cost Inforation Table. This table records spare parts nae and price which are needed in aintenance. 6 Preventive Maintenance Inforation Table. This table records all the inforation related to preventive aintenance. 7 Training Plan Inforation Table. This table records the inforation related to the training, such as training tie and training topic etc. 3)Siulate and Optiization Operation Dynaic Database Tie Inforation Record Table. This table records all repairable units rando fault tie, rando aintenance tie and rando delay tie. What s ore, it records the accuulated aintenance tie for different type aintenance personnel in each aintenance level. 2 Quantity Inforation Table. This table records each unit s accuulated fault ties, all spare part s type and reaining nuber in real tie for every depot. 3 Optiizations Restriction Inforation Table. This table records the restriction conditions for different users. 4)Siulate Results Database OR Inforation Table. This table ainly records the equipent s OR inforation and syste s availability inforation. 2 Spare Parts Consue Inforation Table. This table ainly records all s consuing and stocking state in each stock level. 3 Maintenance Personnel Deand Inforation Table. This table records the aintenance an-hour of all personnel type in each aintenance level. 4 Maintenance Cost Inforation Table. The aintenance costs deanded in each aintenance level are recorded in this table. 5 Maintenance Tie and Delay Tie Inforation Table. This table records the aintenance and delay tie in each aintenance level. 6 Fault Ties Inforation Table. This table records the fault ties for each unit in every year. 5)Optiization Results Database spare parts Inforation Table. This table ainly records the nuber of every kind of spares in each aintenance level. 2 Maintenance Personnel allocation Inforation Table. This table records the nuber of every personnel type in each aintenance level. 3 Maintenance Cost Inforation Table. According to each optiization concept, the aintenance costs deanded in each aintenance level are recorded in this table. 4 Syste availability Inforation Table. According to each optiization concept, the syste availability will be recorded in this table. VI. CASE STUDY For one weapon syste has been joined in a training task, while two type equipents took a join operation. The equipent nae are called A and B respectively. The equipent quantities are 8 and 24 for A and B. The training task was divided into two topics, which are underpan training and jacket training. In underpan training, the training tie for equipent A is 50h while for equipent B is 60h. In jacket training, the training tie for equipent A is 5h while for equipent B is 20h. The ain replaceable unit is a, b of jacket part in equipent A, while c, d, and e in underpan part. While the ain replaceable unit is a, f and g in jacket part, d, e, h in underpan part of equipent B. The work tie for aintenance personnel is 8 h every day. The circustance influence genes are. The diathesis of equipent operation and aintenance personnel are too. The replaceable units of the two kinds of equipent are all obey exponent distribution. The other paraeters are shown as table in detail. We take spare parts optiization as exaple, supposing there are 8 kinds of key repairable units selectively and assue the aintenance cost is 280000 Yuan each year, unit s inforation are shown as table 2.

Predication and Optiization of Maintenance Resources for Weapon Syste 7 Serial nuber Unit nae λ i (/h) f p (/h) TABLE. THE MAIN PARAMETERS OF EACH REPLACEABLE UNIT Repair tie(h) X kij P kij Person A Person B Person C Facility (h) Facility2 (h) A 0.003 0.2 0.60 2 0.05 0. 2 B 0.002 0.004 0.5 0.85 3 0.2 0. 3 C 0.004 0.006 0.5 0.92 3 0.3 0. 4 D 0.00 0.003 0.6 0.65 2 3 0.2 0.3 5 E 0.005 0.002 0.4 0.60 2 0. 0.2 6 F 0.002 0.005 0.5 0.75 2 0.3 0. 7 G 0.003 0.002 0.3 0.95 3 0. 0. 8 H 0.005 0.00 0.5 0.85 3 0.2 0.2 Serial nuber Unit Nae Failure Distributing Kinds TABLE 2 PARTS OF INFORMATION OF EQUIPMENT TRAINING AND UNIT Distributing Paraeter Distributing Paraeter 2 Nuber In Each Equipent Aiing (300h) Training Plan driving (300h) Unit s Price (Yuan) A weibull η=600 β=. 300 2 B weibull η=000 β=.2 500 3 C weibull η=500 β=.08 600 4 D weibull η=800 β=. 400 5 E weibull η=400 β=2.3 000 6 F weibull η=200 β=2-800 7 G weibull η=800 β=2.5-550 8 H weibull η=000 β=2 850 A. Analysis According to the aintenance resources classification entioned above, spare parts a, d, e and aintenance personnel A, B and facility are all current resources. Spare parts b, c, f, g, h, aintenance personnel C and facility 2 are all special resources. Therefore, spare parts b, c, f, and g, h belong to the Ⅰ kind aintenance resources. Spare parts a, d, e belong to the Ⅱ kind aintenance resources. A aintenance personnel C belongs to the Ⅲ kind aintenance resources. Maintenance personnel A, B, facility and facility 2 belong to the Ⅳ kind aintenance resources. B. Calculation ) The requireent prediction for the Ⅰ kind aintenance resources Followed by (), (2) and (3), the requireent quantity of spare part b is: 8 5 (0.04+0.02 ) 0.85=.377 The result is 2 after integer calculation. In the sae ethod, we can calculate that the quantity of spare c, f, g and h are 2, 3, 6, and 3. 2 ) The requireent prediction for the Ⅱ kind aintenance resources Followed by (5), the requireent quantity of spare part a is : [8 5 0.003 0.60+24 20 0.003 0.60]=4. In the sae ethod, we can calculate that the quantity of spare d, e and h are7 and 0. 3 ) The requireent prediction for the Ⅲ kind aintenance resources Followed by (6) and (7), the requireent quantity of Personnel C is: [{8 50 (0.004+0.006) 3 0.5 0.92+8 50 (0.00+0.003) 3 0.6 0.65+8 50 (0.005+0.002) 2 0.4 0.6}/8]=2 4 ) The requireent prediction for the Ⅳ kind aintenance resources Followed by (8) and (9), the requireent quantity of Personnel A is: [{8 50 (0.004+0.006) 0.5 0.92+ 8 50 (0.00+0.003) 2 0.6 0.65+8 50 0.4 0.6 (0.005+0.002) +24 60 (0.005+0.00) 3 0.5 0.95}/8] =2 In the sae ethod, the requireent quantity of Personnel B is 3; the requireent quantity of facility and 2 are both. C. Optiization We siulate all the equipents for 0 year s using. The siulation last 688 seconds for 0 ties, and we can get the relationship between Spares support availability and the ost optial individual for each group. The supportability curve in spares optiization is agnified as Fig. 5.

8 Predication and Optiization of Maintenance Resources for Weapon Syste Spares Support Availability 0.98 0.96 0.94 0.92 0.9 0.88 0.86 0.84 0 50 00 50 200 250 300 Nuber of Heredity Era Figure5. Supportability curve in spares optiization Fig.5 indicates that when the inherit era reach above 220, the Spares support availability will reach to a stabilization level. Hence, we can sure that we have fond an optiu allocation concept, and parts of the optiu result are displayed as table 3. The aintenance cost in this concept is 27980 Yuan and the total Spares support availability is 0.9976, which are satisfied with the beginning restriction condition. Fro the result, we can see clearly that soe valuable and less needed spare parts should to be increase the deposit nuber in interediate repertory, and reduce it in basic repertory. On the contrary, for those less cost and ore needed spare parts, we should increase the deposit nuber in the basic repertory, and reduce the deposit nuber in interediate repertory. More iportantly, the optiization result is accord with the fact, which is an ebodient of the availability of the odels and optiization ethods in this paper. Serial nuber Unit Nae Require Nuber in Basic Repertory TABLE 3 PARTS OF OPTIMUM RESULT Optiu Result in Basic Repertory Optiu Result in Interediate Repertory Apply Nuber fro Repertory Support Availability for Single Parts a 9. 24 4 0.09 0.9993 2 b.8 5 8 0.007 0.9995 3 c 8.2 9 8 0.046 0.9989 4 d 4.5 7 4 0.0022 0.9985 5 e.2 2 0 0.9997 6 f.02 0 0 0.9999 7 g.02 0 2 0.0035 0.9996 8 h 6.8 8 4 0.0654 0.999 VII. CONCLUSIONS According to the requireent analysis of weapon syste aintenance resources, a detailed classification ethod was presented fro resources being consued/engaged and current/special angle. A prediction flow of aintenance resources requireent was abstracted by the practice support process. The prediction odels for four kinds of aintenance resource requireent were designed and presented. It is an ephasis of our study and the odels calculation are all nuerical value calculation. Lastly, a case study was given, which have proved the practicability of the predication ethod. Our study can provide an effective theoretic sustentation for aintenance support decision-aker. In the aftertie study, we should lucubrate on different equipping tie and resources confliction issues. Scientifically predict the aintenance resources and optiize the allocation in each level is the precondition to bring the precision support into effect. After researched on the ethods for decision-aking of aintenance resources, this study established the process of decision-aking, designed and developed a corresponding siulation software syste, and applied a case to the software at last, which validate that the siulation syste can relative exactly siulate the aintenance resources deand and can provide a optiu result for resources. It is a crucial and realistic significance not only for aking a scientific aintenance support decision, but also for optiizing the deployent of aintenance resources. ACKNOWLEDGEMENT This paper was sponsored by Mechanical Engineering College funds ite (YJJXM09037) REFERENCES [] AI Baoli, WU Chang, Modeling and Siulation of Counication Equipents Spare Parts Support Syste Based on Arena [J].Journal of Air Force Engineering University, 200, (5):8-85. [2] ZHAO Gang, Research on optiization allocation odel for spare parts, Telecounications Technology. 2005, 6(0), 3-34. [3] YI Fa, Research on the optiization of two level spare parts, Military Operations Research and Systes Engineering. 2002,6(4), 2-7. [4] YANG Guanghui, A odel of personnel need for equipent aintenance based on queue theory, Coand control and siulation. 2007,2(2). [5] ZHANG Fangyu, Research on allocation odels for anpower on wartie, Military Operations Research and Systes Engineering. 2005,9(2), 23-26.

Predication and Optiization of Maintenance Resources for Weapon Syste 9 [6] WANG Ya-bin, Research on Siulation of Maintenance Resource Requireents of Typical General Purpose Equipent, Shijiazhuang: Ordnance Engineering College, 2005. [7] FAN Hao, Study of Requireent Siulation and Allocation Optiization of Maintenance Resources for Representative Currency Weapons, Shijiazhuang: Ordnance Engineering College, 2007. [8] ZHAN Tao, GUO Bo, TAN Yuejin, Research on a Mission Oriented Maintenance Resources Deployent Decision Support Syste, ACTA ARMAMENTAR, 2005, (5):76-720 [9] ZHOU Xuelin, Optiization Configuration of Maintenance resources Distribution for Maintenance Manageent, National university of defense technology, 2005 [0] GUO Ji-zhou, ZHAO Chao-xian, GUO Bo, Spare Optiization Modeling of Phased-Mission Syste for Air-Defense Cobat Unit, Matheatics in Practice and Theory, 2009,(2):64-69 [] Derek T. Dwyer, Heuristic Algorith for U.S. Naval Mission Resource Allocation, ADA488672, 2008.09 [2] Scott Wells, Coordinated Resource Allocation aong Multiple Agents with Application to Autonoous Refueling and Servicing of Satellite Constellations. ADA479643, March 2008 [3] GAN Maozhi, KANG Jianshe, GAO Qi, Maintenance Engineering Science for Military Equipent Use, Beijing: national defense industry publishing copany. 2005 [4] Ruhul Sarker, Aanul Haque, Optiization of Maintenance and Spare Provisioning Policy Using Siulation, Applied Matheatical Modeling, 2000, (24),75-760. BIOGRAPHY Ya-Bin WANG (975.09- ), Male, Hebei Province of P.R. China, Doctor graduate student in Ordnance Engineering College, Be engaged in equipent support theory and application.