Production Cost Optimization Model Based on CODP in Mass Customization

Transcription

1 IJCSI International Journal of Computer Siene Issues, Vol. 0, Issue, No, January Prodution Cost Optimization Model Based on CODP in Mass Customization Yanhong Qin, Yuanfang Geng Shool of Management, Chongqing Jiaotong University Chongqing, , China Shool of Management, Chongqing Jiaotong University Chongqing, , China Abstrat The ey for enterprises to implement the postponement strategy is the right deision on the loation of Customer Order Deoupling Point (CODP) so as to ahieve the sope eonomis of mass ustomization and sale eonomis of mass prodution fully. To deal with prodution ost optimization problem of postponement system based on various situation of CODP, a basi model of prodution ost and its M/M/ extended model are proposed and ompared so as to optimize the overall prodution ost of the postponement system. The prodution modes an be lassified as MTS (mae to sto), ATO (assemble to order), MTO (mae to order) and ETO (engineering to order) aording to the inventory loation, and the postponed prodution system onsidered here inludes manufaturing ost, semi-finished inventory ost and ustomer waiting ost aused by delaying delivery. By Matlab simulation, we an ompute the optimal loation of CODP in eah prodution mode, whih an provide some management insight for the manufaturer to deide the right prodution mode and utilize the resoures effiiently. Keywords: Mass ustomization, Postponed prodution, Prodution ost, Customer order deoupling point. Introdution With the maret hanging frequently, more and more ompanies are starting to adopt mass ustomization (MC) to provide a larger degree of produt ustomization to fulfill the various demands of inreasingly differentiated maret segments. The advaned information tehnique an also provide more ompanies with more possibility to interat with ustomers and obtain individual ustomer requirements effetively (Huang, 008). Postponement strategies allow a ompany to be flexible in developing different versions of the produt as needed, to meet hanging ustomer needs, and to differentiate a produt or to modify a demand funtion. As many researhers pointed out, the ustomer order deoupling point (CODP) tehnology as a tehnique of postponement is an effetive way to ahieve MC, and many firms made out the different loation of CODP to revise their supply hain so as to meet various requirements of different ustomized extents, by doing this it an meet exat requirement and lessen the often-painful effets of upstream order magnifiation, i.e. bullwhip effet (Alessandro, 009). CODP means ustomer order deoupling point, that is to say, the plae in the supply hain where the ustomer requirements are permitted to penetrate up the value hain of supply before differentiation of the produt is started (Riardo, 00). The manufaturing strategy planned based on the foreast started to ustomized prodution driven by ustomer order at CODP, i.e. CODP is related to manufaturing strategy with a distintion is neessary between pre-codp and post-codp operations, sine these have fundamentally different harateristis. The post CODP means the produt is lined to a speifi ustomer order. Before CODP, the mass prodution an be implemented to ahieve the high prodution effiieny and sale eonomy, and post CODP, the flexible manufature proess should be adopted to route greater volumes of ompatible produts through a fixed asset (Lee, 996 and Lee, 997). So in postponed prodution ondition, there are two prodution stages, i.e. mass prodution before CODP and ustomized prodution after CODP, and the loation of CODP is very important for the enterprise in terms of prodution ost. Italian lothing ompany Benetton adopted the postponement strategy to delay the CODP in the prodution proess until to the end prodution proess, and thus to redue the ris of unertainty demand. There have been many theories and literatures on postponement strategy. The postponed prodution is applied by retailer to inrease the profit, but the manufature is ignored (Yang et al., 009). The inventory managing strategy model under the entralized and deentralized deision mode is set in supply hain applying postponed strategy, but the total prodution ost was not onsidered (Shao and Ji, 004). Jin et al. (0) proposed the method of Kanban to ahieve ustomization, but they didn t analyze whether the Kanban system an redue the ost of manufature in the quantitative way. Sun (00) implemented the postponed prodution by restruture the produt portfolio and set an simple model by ombing the profit, ost and produt Copyright () 03 International Journal of Computer Siene Issues. All Rights Reserved.

2 IJCSI International Journal of Computer Siene Issues, Vol. 0, Issue, No, January strategy, and the model was an general postponed prodution model to ahieve ustomization, but in their model, they thought the manufature need different proesses to obtain the ustomization after the CODP (Customer Order Deoupling Point). Hua (007) optimized the flexible prodution system by queue theory. Van (998), Krajewsi (005) and Rao (007) researh the postponed prodution in terms of simple ustomization and mass ustomization, but the ey to their problem is whether the manufature an redue ost by ustomized postponement. Huang et al. (008) ompared the ost hange before and after the CODP, but they ignored the payment of ustomer waiting ost to eep the ustomer purhasing the produt. Dan (009) set the ost optimization model for the two-stage supply hain made up of retailer and manufature applying postponed prodution, and Li (00) set the similar model and CODP orientation model, but both of them didn t onsider the ost hange before and after the CODP only for the manufature, i.e. they didn t ompare the ost hange in different ondition in applying postponed prodution or not applying the postponed strategy. Garg (997) studied the postponed prodution model with many potential CODPs. Swaminathan (998) found out that the general omponents and modules an redue the inventory ost of the postponed prodution system, but when the ost of design and manufature is too high, it is uneonomi to implement the postponed prodution. Ma (00) studied the multi-assembly postponed prodution problem under assemble to order mode, and he analyzed the relation between the general omponents /modules and prodution ost. Tibben and Basso (005) found out the postponed prodution an redue the total prodution ost based on the inventory model when the postponed prodution was applied. Su (005) set the model of time postponement and form postponement, and analyzed the implementation ondition of these two postponement strategies. Dan (009) studied the ost optimization model under mass ustomization for manufature and supplier, and analyzed the influene of CODP on the systemati prodution ost and the ey fators on the CODP loation. Yang (00) studied the ost evaluating model of mass ustomization based on CODP loating, and set the ost model refleting the influene of multi-codp on the assemble produts. Most of these researhes foused on the postponed prodution system with fixing CODP loation and without onsidering the prodution leading time or fixing the leading time, few referred to the multi-codp loation problem. Based on these researhes, this paper will onsider the manufaturing ost, semi-finished inventory ost and ustomer waiting ost aused by delaying delivery to set the ost optimization model of basi model its M/M/ extended model so as to optimize the overall prodution ost of the postponement system. The prodution modes an be lassified as MTS (mae to sto), ATO (assemble to order), MTO (mae to order) and ETO (engineering to order) aording to the inventory loation, and the postponed prodution system onsidered here inludes manufaturing ost, semi-finished inventory ost and ustomer waiting ost aused by delaying delivery. By Matlab simulation, we an ompute the optimal loation of CODP in eah prodution mode, whih an provide some management insight for the manufaturer to deide the right prodution mode and utilize the resoures effiiently.. The prodution modes under mass ustomization The ey to arry out postponement strategy in mass ustomization is CODP. Before CODP, enterprise mainly adopt push supply hain whih mainly foreast maret demand and implement large-sale prodution, and the goal is to improve supply hain effiieny and redue the ost of the supply hain. After CODP, enterprise an mainly adopt pull supply hain whih depend on ustomer orders and implement small-sale proessing, and the goal is to improve the response speed of the supply hain as well as the ability to provide ustomers with ustomized produts and servie. In general, supply hain ativities inlude supply, design, manufature, assembly and retail. The position of CODP is hangeable. The more upstream of CODP in the supply hain, the more obvious pull supply hain, and the higher the degree of ustomer partiipation. The more downstream of CODP in the supply hain, the more obvious push supply hain, the lower the degree of ustomer partiipation. The different position of CODP lead to different modes of prodution, this is a new understanding of these four prodution modes based on ost and ustomization. As shown in Figure, the vertial axis represents the ost, and the horizontal axis represents ustomization level. When other onditions are same, sale advantage plays a very important role in reduing the prodution ost, but it also redues ustomization level. At this point, the ost and ustomization level are in a low level, enterprises will adjust the position of CODP aording to produt harateristi and maret demand harateristi, every points will result in orresponding hanges about the osts and ustomization level. As shown in Figure, from MTS (Mae to sto) to ETO (Engineer to order), the osts and ustomization level inrease or improve gradually. Copyright () 03 International Journal of Computer Siene Issues. All Rights Reserved.

3 IJCSI International Journal of Computer Siene Issues, Vol. 0, Issue, No, January high retai l assembly push push manufatur e MTO ETO desig n pull suppl y pull greatest degree. Under this prodution mode, prodution osts and ustomization level are highest. Suh enterprises generally have a high degree of produt design management apabilities, and most produts are about omplex struture, suh as speial test equipment, generator sets, et (Qin and Geng, 0). ost push push MTS ATO pull pull 3. The basi model under postponed prodution mode low 3. Problem desription low ustomization level Fig. Four prodution mode based on different positioning of CODP Under MTS, CODP is positioned in retail ativity. Enterprises foreast produts fully depend on maret demand and arrange prodution aording to their own inventory. In the supply hain, there is not the partiipation of ustomers from the supply to the retail, ustomers selet their favorites in the final produt, the entire supply hain an quily and timely response to ustomer demands, and the osts is low, but the available hoie of ustomers is very limited. Under this prodution mode, ustomization level is very low, and most of the produts are popular onsumable. Under ATO, CODP is positioned in assembly, enterprises produe large-sale standardized omponents and assemble existing standardized omponents and modules to meet ustomer order requirements after reeiving ustomer orders, ustomers partiipate in assembly aspets. Under this prodution mode, prodution yle is redued and the response time to ustomers is prolonged, osts and ustomization level are both improved relatively. Enterprises an avoid oversto or out of sto, and they an also meet ustomers demand quily. Most produts are about eletroni equipment, automobiles, et. Under MTO, CODP is positioned in manufature ativity, enterprises arrange prodution plans with purhased omponents and modules to meet the needs of ustomers, ustomers partiipate in manufature aspets. Under this prodution mode, advantages of sale eonomy is gradually weaen, the response time to ustomers are longer, ost and ustomization level are relatively higher. Enterprises will arrange prodution only reeiving ustomer orders, not to mae any inventory. Most produts are about airraft, ships, et. Under ETO, CODP is positioned in design ativity, enterprise entirely design produt aording to ustomer order, and then proeed to the prourement, prodution and other ativities, and ustomers partiipate in design aspets from the beginning, enterprises meet the demand of ustomer servie at the high The manufature will fae the unertain maret demand and produe N inds of ustomized produts belonged to the same produt family by postponed prodution with the same total prodution time S. Eah final produt will go through two prodution stage, i.e. mass prodution and ustomized prodution, and the first stage is the modular semi-finished prodution pushed by foreast information, and the seond stage is the ustomized prodution pulled by order. r denote the ustomer order penetration point, i.e. CODP, whih is ey to implement postponed prodution and it will lin the two prodution stages. r ( 0r ) an stand for the ratio of prodution time in stage to total prodution time, and r =0 an indiate the manufature to hoose the ETO prodution mode, and all the prodution ativities are driven by orders, but r = indiate the MTS should be applied, and all the produts are produed aording to the foreasting information and stored as inventory. The bigger value of r denotes the longer mass prodution time and shorter ustomized prodution time. 3. Assumption () Whether to implement the postponed prodution will not influene the transportation time, so we will not onsider the transportation ost. The loation of CODP an be denoted as the ratio of prodution time of standard produt to the total prodution time, i.e. r ( 0 r ). () The ustomer demand of the K th ustomized produt is a random variable observing Poisson distribution whose average value is, and the variant value is. means the average demand quantity of ustomized produt K in unit time. (3) The manufature will produe some produt and eep the inventory aording to the foreast information of the maret demand, and the produe intension will be bigger than the reahing ratio of ustomer demand, so there will be no shortage ost. Copyright () 03 International Journal of Computer Siene Issues. All Rights Reserved.

4 IJCSI International Journal of Computer Siene Issues, Vol. 0, Issue, No, January (4) For the CODP divide the prodution into two stages and in the seond stage, the final produt will delivered to ustomer diretly one it is finished driven by order, so the there is no inventory in the seond stage, and we only onsider the buffer inventory at CODP. 3.3 Denotation and model To better study the influene of CODP loation on the prodution ost quantitatively, the prodution ost inludes only the manufature ost Mr (), inventory ost Hr () and ustomer waiting ost Wr (). For the order delivery needs some lead time, and the longer the lead time is, the longer the waiting time is, leading to the more waiting ost, so time is the measure standard of the waiting ost. For the prodution ost an be divided as two parts: the manufaturing ost M () r in the stage of mass prodution and the manufaturing ost M () r in stage of ustomized prodution. So we an denote the prodution ost in postponed prodution as: Z( r) M ( r) M ( r) H( r) W( r) () In the formula, the relative denotation in Mr () is as following:, is the unit demand reahing ratio of the K th ustomized produt, () r is the unit average prodution ost in stage when the CODP loation is at r is the unit average prodution ost of r and, () the K th produt in stage when the CODP loation is at r. The relative denotation in Hr () is: h() r average inventory ost of semi-finished inventory in stage, E[ I ]( r ) is the expeted inventory amount of semifinished inventory. So the ost optimization model an be transformed as: N min Z( r) ( r) ( r),,, h ( r) E[ I ]( r) w ET ( r),,, N N st.. 0r (3) Eah term in formula () is orresponding to the ost item in formula (), and it means the total prodution ost in postponed prodution system. The first item in () is the manufature ost in stage, the seond item is the ustomization ost in stage, the third term is inventory ost of semi-finished produt at CODP, and the forth item is the ustomer waiting ost in stage. Constraint (3) denotes the loation of CODP an be at random stage in the whole prodution proess. () 4. The M/M/extended model of postponed prodution 4. Assumption () The prodution proess is a value inreasing proess, so () r is simple inreasing funtion of r, and it will inrease with delaying CODP to the downstream of prodution proess, i.e. M ( r) M ( r ) M ( r) 0. Besides, the inventory ost is inreasing in the prodution proess, so h () r is all simple inreasing funtion of r, H( r) H( r ) H( r) 0. () The ustomized produts of produt family are not the high additional-value produt, and the inremental proess is a ontinuous and even proess of prodution time and, () r is the simple dereasing funtions of r, i.e. M ( r) M ( r ) M ( r) 0. (3) Not all the ustomer would lie to wait some time for the ustomized produt, and the longer the waiting time, the bigger the lost order, so w, is dereasing funtions of r, i.e. W ( r) W( r ) W( r) 0. (4) All the ustomized produts are belonged to the same produt family, and thus eah ustomized produts are similar and have the same prodution time, so we an assume that,,,, () r, w,, ET, () r an be equal, () r, w and ET () r respetively. to (5) In the random time zone, the probability of ustomer demand for the ertain ustomized produt is dependent on the length of time zone, but it independent of the terminal of time zone, and if the time zone is small enough, the probability that the number of ustomer demand for the ertain ustomized produt is more than twie an be ignored. Besides, in eah independent time zone, the demand of produt is independent. (6) The prodution proess in stage and stage is smoothly, and the prodution time and ustomer order is independent. (7) The manufature will adopt the first ome first servie rule to finish the order, so the prodution system an be seen as an M/M/ queuing system. The better your paper loos, the better the Journal loos. Thans for your ooperation and ontribution. Copyright () 03 International Journal of Computer Siene Issues. All Rights Reserved.

5 IJCSI International Journal of Computer Siene Issues, Vol. 0, Issue, No, January Denotation and model h is the basi inventory in stage, D is the average total demand and, N D, () r proessing produt, and, () r is the amount of is the amount of proessing produt of the th final produt. We an obtain the effiieny index before and after CODP aording to the researh of Buzaott and Shanthiumar (993). Aording to the assumption of extended model, the manufature intension of standard semi-finished produt is ( r) before CODP, and the prodution intension of ustomized produt is, () r. So we an get the expeted inventory in stage and expeted prodution time in stage as following: ; rds r DS ; ( ) h [ ] h ( )( ) E I h [ rds ( rds) ]( rds) h ( ) ( ) [ ( ) ]. ET N r S D r S So the prodution ost model an be transformed as h rds ( rds) NwD( r) S min Z( r) D ( r) D ( r) h ( r)[ h rds ] D( r) S (4) st.. 0r (5) 0DS (6) ( r) h( r) 0; 0 r r (7) () r 0 r (8) h Z (9) The formula (4) denotes the total prodution ost of postponed prodution in mass ustomization. In formula (4), the first item denotes the manufaturing ost in mass prodution of stage, the seond item denotes the manufaturing ost in ustomized prodution of stage, the third item denotes the inventory ost in stage, and the forth item denotes the ustomer waiting ost. Constraint (5) denotes the loation of CODP an be at random stage in the whole prodution proess. Constraint (6) means that the oversto ondition will not be appeared, beause the prodution intension of manufature is bigger than the reahing ratio of ustomer demand. In onstraint (7) an be obtained easily by assumption (), i.e. () r is simple inreasing funtion of r and h () r is all simple inreasing funtion of r. Constraint (7) means that the produt value is inreasing with prodution time in stage, and the inventory ost of standard semi-finished produt is inreasing with its value. Similarly, onstraint (8) means the produt value in stage is inreasing with prodution time, when the prodution time in stage is shortening, the produt value inrement will derease. Finally, onstraint (9) indiates the safety sto is an integer. 5. Simulation and omputation For further researh, we will apply MATLAB software to simulate the influene of four prodution modes on the prodution ost and the optimal CODP loation in eah prodution mode. Aording to the ase data in researh of Rietze (006), the value of eah parameter is as following: h 3, h ( r) 0.6r S and N 0, D 000,. For the data in this researh, the unit inventory ost and ustomer waiting ost has little influene on the total prodution ost, so we only onsider the effet of unit manufaturing ost on the optimal CODP loation. In the following simulation figures, the horizontal axis denote the CODP loation, and with the CODP moving to the end of prodution proess, the loation on the axis is inlined to moving toward the right side. The vertial axis denotes the manufaturing ost. 5. The optimal CODP loation in MTS The produts under MTS are about a large lass of low omplex standardized produts, osts and delivery time are ey fators in delivery proess, whih requires enterprises to produe and store large amounts of standardized produts, suh as the largest food and beverage manufaturer Wahaha, the speies has been involved in the drining water, arbonated drins, tea drins, mil drins and other beverages industries to meet the diverse needs of ustomer. In the MTS, ( r) r, ( r) 3 4 r r[0.9 r (0.9 r) ] 4.5( r) Z( r) 000( r ) 000(3 4 r).8r 0.9r 0.9( r) The simulation result is shown in fig. From fig, the manufaturing ost is dereasing with CODP moving to the end, and the optimal CODP loation with the minimum ost is r =, i.e. all the prodution proess is mass prodution with sale eonomis. For easy deision on the CODP loation, the sensitive analysis of () r and () r is shown in table. Copyright () 03 International Journal of Computer Siene Issues. All Rights Reserved.

6 IJCSI International Journal of Computer Siene Issues, Vol. 0, Issue, No, January Fig. The trend of prodution ost hanging under MTS From table, the prodution proess in stage is an value inreasing proess, i.e. () r is an inreasing funtion, its value will inrease with CODP moving to the end proess, and the manufaturing ost M () r will inrease too. () r is a dereasing funtion, its value will derease with CODP moving to the end proess, and the manufaturing ost M () r will derease too. When r, will inrease with CODP moving to the end proess, but will derease. For all the prodution proess is mass prodution, there exits obvious sale eonomis, so Mr () is dereasing, and Zr () is dereasing. 5. The optimal CODP loation in ATO When ATO is adopted, ustomization level is relatively low and the ost is relatively high. Under ATO, enterprises ombine different standardized modules into a limited variety of produts to meet ustomer demand, although hoie of ustomers is limited, but it allows enterprises to produe mass standard parts and omponents to get the advantage of eonomies of sale, and it also allows enterprises to get omponents by outsouring to provide a reasonable prie to the ustomer, suh as omputer industry, enterprises use the advantages of manufaturing resoures around the world to produe parts and to assemble in plaes lose to the sale of land, For example, Dell put their main fous on o-operation with suppliers in order to share information with suppliers, purhase and organize prodution after reeiving ustomer orders. Under ( r) r and ( r) 3.4r. Z( r) 000( r ) 000(3.4 r ) ATO, r[0.9 r (0.9 r) ] 4.5( r).8r 0.9r 0.9( r) The simulation result is shown in fig 3. Fig. 3 The trend of prodution ost hanging under ATO In figure 3, the ost urve is onave in CODP loation, and the optimal CODP loation with minimum ost is r =0.6. For the CODP is at the downstream of prodution proess, so the mass prodution will tae more ratio before CODP, and the sensitive analysis of () r and () r is shown in table. From table, when r 0.6, will inrease with CODP moving to the end proess, but will derease with CODP moving to the end proess. For the mass prodution proess is longer than the ustomization proess, there exits some sale eonomis, so Mr () is dereasing, and Zr () is dereasing. So for the eletroni produts, the optimal CODP loation is r = The optimal CODP loation in MTO When MTO is adopted, ustomization level is relatively high, the ost is relatively low. Enterprises store a lot of raw materials and parts in order to obtain sale advantages, and the rest of the ativities will be delayed until the ustomer orders. Amaretto is the ream liqueur produed in Italy, it an tae different ustomer strategies aording to different maret demand. In the fae of international maret, the enterprise delay paaging and labeling, but in the loal maret, timely delivery does not allow the enterprise postpone any lin. Proter & Gamble has adopted Networ order management online system to omplete the order request of the end retail lin, whenever and wherever retail ustomers an be diretly onneted to the P & G. Under ATO, ( r) r ( r) 3.r. Z( r) 000( r ) 000(3. r).8r r[0.9 r (0.9 r) ] 4.5( r) 0.9r 0.9( r) and Copyright () 03 International Journal of Computer Siene Issues. All Rights Reserved.

7 IJCSI International Journal of Computer Siene Issues, Vol. 0, Issue, No, January The simulation result is shown in fig Fig. 4 The trend of prodution ost hanging under MTO In figure 4, the ost urve is onave in CODP loation, and the optimal CODP loation with minimum ost is 0.3. For the CODP is at the upstream of prodution proess, so the mass prodution will tae less ratio of the total prodution proess, and the sensitive analysis of () r and () r is shown in table 3. From table 3, when r 0.3, will inrease with CODP moving to the end proess, but will derease. For the mass prodution proess is shorter than the ustomization proess, there exits few sale eonomis, so Mr () is dereasing, and Zr () is dereasing. So for Furniture produts, the optimal CODP loation is r = The optimal CODP loation in ETO When ETO is adopted, ustomization level and osts are very high. The omponents have standard interfaes, so enterprise would assemble timely aording to ustomer needs, and they have their own suppliers and distributors, and tae flexible supply hain strutures based on the expetations of the ustomer strategy. Toyota s prodution aounts for a substantial advantage in the automotive maret driven by ustomer orders, and Trainer airraft manufaturer Mahi airraft an produe a variety of airraft for speial training aording to the speial needs. Under ETO, r r and r r. ( ) ( ) Z( r) 000( r ) 000(3 0.5 r) r[0.9 r (0.9 r) ] 4.5( r).8r 0.9r 0.9( r) The simulation result is shown in fig 5. Fig. 5 The trend of prodution ost hanging under ETO In figure 5, the ost urve is inreasing funtion of CODP loation, and the optimal CODP loation with minimum ost is 0. For the CODP is at the threshold of prodution proess, so the whole prodution proess is driven by ustomer order, and the sensitive analysis of () r and () r is shown in table 4. For the mass prodution proess is shorter than the ustomization proess, there exits few sale eonomis, so Mr () is dereasing, and Zr () is dereasing. For more tehnial, more omplex struture of the produt, the optimal CODP loation is r =0. From table 3, will derease with CODP moving to the end proess. For the whole prodution proess is, there is no sale eonomy, so Mr () is inreasing, and Zr () is inreasing in the whole prodution proess. 6. Conlusion This paper studied the ost optimization problem under onsidering manufaturing ost, inventory ost of semifinished produt and ustomer waiting ost, and analyzed the optimal CODP under four prodution modes, i.e. MTS, ATO, MTO and ETO. The Matlab was applied to analyze the ost optimization under eah prodution mode. When the produts are a large lass of low omplex standardized produts, suh as Swiss offee and the largest food and beverage Wahaha, the MTS will be hosen and the optimal CODP is r =. When the produts are eletroni produts of high ustomization level and low ustomization ost, e.g. Dell and GOME, the ATO will be hosen and the optimal CODP loation is r =0.6.When the produts are Furniture produts, the optimal CODP loation is r=0.3 and the MTO will be applied. When the produts are more tehnial, more omplex struture of the produt, e.g. airraft and mahine, ETO will be applied and the optimal CODP loation is r =0.So manufature an hoose the right Copyright () 03 International Journal of Computer Siene Issues. All Rights Reserved.

8 IJCSI International Journal of Computer Siene Issues, Vol. 0, Issue, No, January prodution mode and mae right deision on the optimal CODP aording to its own harateristis and maret demand harateristis. Besides, the shortness in this paper is that the basi ost model and its M/M/extended model did not onsider the other ost fators, suh as holding ost of proessing produt, investment ost aused by redesign for the postponed prodution, and so on, whih an be future researh diretion. Table : The influene of unit manufaturing ost on the optimal CODP loation under MTS r r 0.6r 0.8r r.r.4r.6r.7r.8r.9r r 3 0.3r r 3 0.6r 3 r 3.4r 3 r 3.5r 3 3r 3 3.5r 3 4r M Z Table The influene of unit manufaturing ost on the optimal CODP loation under ATO r r 0.6r 0.8r. r.4r.7r r r r r r 3 0.3r r 3 0.6r 3.r 3.7r 3.4r 3.8r 3 3.r 3 3.6r 3 4r M Z Table 3 The influene of unit manufaturing ost on the optimal CODP loation under MTO r r.5r.8r r r r r r r r r 3 0.3r 3 0.r 3 0.7r 3.r 3.6r 3 r 3.4r 3.8r 3 3.r 3 3.6r 3 4r M Z Table 4 The influene of unit manufaturing ost on the optimal CODP loation under ETO r r r r r r r r r r r r 3 0.5r 3 0.3r 3 0.7r 3.r 3.6r 3 r 3.4r 3.8r 3 3.r3 3.6r 3 4r M Z Copyright () 03 International Journal of Computer Siene Issues. All Rights Reserved.

9 IJCSI International Journal of Computer Siene Issues, Vol. 0, Issue, No, January Referenes [] Y. Y. Huang, S. L. Li, Suitable appliation situations of different postponements approahes: Standardization vs. modularization, Journal of Manufaturing Systems, Vol.7, No., 008, pp.-. [] B. Alessandro, Marta Z, Evaluation of produt ustomization strategies through modularization and postponement, International Journal of Prodution Eonomis, Vol. 0, No. 3, 009, pp [3] E. Riardo, K. Bardia, Evaluation of Supply Chain Strutures through Modularization and Postponement, European Journal of Operational Researh, Vol.4, No. 3, 00, pp [4] H. Lee, Effetive inventory and servie management through produt and proess redesign, Operations Researh, Vol.44, No., 996, pp [5] H. Lee, C. Tang, Modeling the osts and benefits of delayed produt differentiation, Management Siene, Vol. 43, No., 997, pp [6] Z. L. Yang, Y. M. Tian, A study of partial baorder poliy under random demand, Journal of Systems & Management, Vol. 8, No.6, 009, pp [7] X. F. Shao, J. H. Ji, Researh on impat of postponement strategies on inventory ost in mass ustomization, System Engineering Theory Methodology & Appliation, Vol. 3, No. 5, 00, pp [8] J. Qing, Z. Zhong. A visualized e-anban system for small bath JIT prodution, Industrial Engineering Journal, vol. 4, No. 3, 0, pp [9] S. W. Sun, The disussion about push-pull supply hain based on delay tatis, Storage Transportation & Preservation of Commodities, vol. 3, no. 9, 00, pp [0] Z. S. Hua. Flexible manufaturing systems and flexible supply hain: Modeling optimization. Beijing, Siene Press, 007. [] Van Hoe R I. Logistis and virtual integration: postponement, outsouring and the fow of information, International Journa of Physial Distribution & Logistis Management, vol. 8, no. 7, l998, pp [] Krajewsi L, Wei J C, Tang L L. Responding to shedule hanges in build-to-order supply hains, Journal of Operations Management, vol. 3, no.5, 005, pp [3] R. Kai, D. Bin, L. Yu. Researh on ost optimization model of manufaturer implementation postponement strategy in mass ustomization, Computer Integrated Manufaturing Systems, vol. 3, no. 9, 007, pp [4] R. Kai, D. Bin, L. Yu. Researh on ost optimization model of manufaturer implementation postponement strategy in mass ustomization, Computer Integrated Manufaturing Systems, vol. 3, no. 9, 007, pp [5] D. Bin, R. Kai, Li H. Cost optimization model of supply hain implementation postponement strategy in mass ustomization, Computer Integrated Manufaturing Systems, vol. 5, no., 009, pp [6] D Li., J. X. Wang. Customer order deoupling point position for mass ustomization, Journal of Qingdao University (Natural Siene Edition), vol. 3, no., 00, pp [7] Garg A, Tang C. On postponement strategies for produt families with multiple points of differentiation, IIE Transations, vol. 9, no.8, 997, pp [8] S. Ma, W. Wang, L. Liu Commonality and postponement in multistage assembly systems, European Journal of Operational Researh, vol.4, no.3, 00, pp [9] Tibben-Lembe R S, Basso Y. An inventory model for delayed ustomization: a hybrid approah, European Journal of Operational Researh, vol. 65, no.3, 005, pp [0] C.P. Su, Y. Chang, M. Ferguson. Evaluation of postponement struture to aommodate mass ustomization, Journal of Operations Management, vol. 3, no.3, 005, pp [] S. L. Yang, S. F. Zhou T. F., Li. Researh on the Estimation of Mass Customization Prodution Cost Based on CODP, Foreasting, vol.3, no.6, 00, pp [] S. L. Yang, S. F. Zhou T. F., Li. Researh on the Effets of Multi-CODP on Prodution Cost of Proessing and Assembling Produts-Perspetive of Assemble to Order, Operations Researh and Management Siene,vol.8, no.3, 00, pp [3] Y. H.Qin, Y. F. Geng. Mathing Model Analysis of Supply Chain Strutures and Prodution Mode Under Mass Customization, International Journal of Eletronis Communiation and Computer Engineering, vol. 3, no.3, 0, pp [4] Mohamed Ramzi Bouzid, Naoufel Kraiem, An Empirial Evaluation of a Reuse Based Approah for ERP Customization, International Journal of Computer Siene Issues, Vol. 9, No. 3, 0, pp [5] Kompan Chomsamutr, Somiat Jongprasithporn, Optimization Parameters of tool life Model Using the Taguhi Approah and Response Surfae Methodology, International Journal of Computer Siene Issues, Vol. 9, No., 0, pp Yanhong Qin Chongqing Provine, China. Wor as professor in Management Shool of Chongqing Jiaotong University, and researh interests on mass ustomization and supply hain management. Yuanfang Geng Jiangxi Provine, China. Graduate student in Management Shool of Chongqing Jiaotong University, and researh interests on mass ustomization and postponement strategy. Copyright () 03 International Journal of Computer Siene Issues. All Rights Reserved.