Yugoslav Journal of Operations Research 25 (25), Number 3, 425-443 DOI:.2298/YJOR3689S EPQ MODEL FOR IMPERFEC PRODUCION PROCESSES WIH REWORK AND RANDOM PREVENIVE MACHINE IME FOR DEERIORAING IEMS AND RENDED DEMAND Nita H. SHAH Department of Mathematics, Gujarat University, India nitahshah@gmail.com Dushyantkumar G. PAEL Department of Mathematics, Govt. Poly.for Girls, India dushyantpatel_98@yahoo.co.in Digeshkumar B. SHAH Department of Mathematics, L. D. College of Engg., India digeshshah23@yahoo.co.in Received: July 23 / Accepted: July 24 Abstract: Economic production quantity (EPQ) model is analyzed for trended demand and the units which are subject to constant rate of deterioration. he system allows rework of imperfect units and preventive maintenance time is random. he proposed methodology, a search method used to study the model, is validated by a numerical example. Sensitivity analysis is carried out to determine the critical model parameters. It is observed that the rate of change of demand and the deterioration rate have a significant impact on the decision variables and the total cost of an inventory system. he model is highly sensitive to the production and demand rate. Keywords: EPQ, Deterioration, ime-dependent Demand, Rework, Preventive Maintenance, Lost Sales. MSC: 9B5.. INRODUCION Due to out-of-control of a machine, the produced items do not satisfy the codes set by the manufacturer, but can be recovered for the sale in the market after reprocessing. his
426 N.H.Shah, D.G.Patel, D.B.Shah / EPQ Model For Imperfect Production Proces phenomenon is known as rework, Schrady(967). At manufacturer s end, the rework is advantageous because this will reduce the production cost. Khouja (2) modeled an optimum procurement and shipment schedule when direct rework is carried out for defective items. Kohet al. (22) and Dobos and Richter (24) discussed two optional production models in which either opt to order new items externally or recover existing product. Chiu et al. (24) studied an imperfect production processes with repairable and scrapped items. Jamal et al. (24), and later Cardenas Barron (29) analyzed the policies of rework for defective items in the same cycle and the rework after N cycles. eunter (24), and Widyadana and Wee (2) modeled an optimal production and a rework lot-size inventory models for two lot-sizing policies. Chiu (27), and Chiu et al. (27) incorporated backlogging and service level constraint in EPQ model with imperfect production processes. Yoo et al. (29) studied an EPQ model with imperfect production quality, imperfect inspection, and rework. he rework and deterioration phenomena are dual of each other. In other words, the rework processes is useful for the products subject to deterioration such as pharmaceuticals, fertilizers, chemicals, foods etc., that lose their effectivity with time due to decay. Flapper and eunter (24), and Inderfuthet al. (25) discussed a logistic planning model with a deteriorating recoverable product. When the waiting time of rework process of deteriorating items exceeds, the items are to be scrapped because of irreversible process. Wee and Chung (29) analyzed an integrated supplier-buyer deteriorating production inventory by allowing rework and just-in-time deliveries. Yang et al. (2) modeled a closed-loop supply chain comprising of multi-manufacturing and multi-rework cycles for deteriorating items. Some more studies on production inventory model with preventive maintenance are by Meller and Kim (996), Sheu and Chen (24), and sou and Chen (28). Abboudet al (2) formulated an economic lot-size model when machine is under repair resulting shortages. Chung et al. (2), Wee and Widyadana (22) developed an economic production quantity model for deteriorating items with stochastic machine unavailability time and shortages. In the above cited survey, the researchers assumed demand rate to be constant. However, the market survey suggests that the demand hardly remains constant. In this paper, we considered demand rate to be increasing function of time. he items are inspected immediately on production. he defective items are stored and reworked immediately at the end of the production up time. hese items will be labeled as recoverable items. After rework, some recoverable items are declared as good and some of them are scrapped. Preventive maintenance is performed at the end of the rework process and the maintenance time is considered to be random. Here, shortages are considered as lost sales. wo different preventive maintenance time distributions are explored viz. the uniform distribution and the exponential distribution. he paper is organized as follows. In section 2, notations and assumptions are given. he mathematical model is developed in section 3. An example and the sensitivity analysis are given in section 4. Section 5 concludes the study.
N.H.Shah, D.G.Patel, D.B.Shah / EPQ Model For Imperfect Production Proces 427 2..Assumptions 2. ASSUMIONS AND NOAIONS. Single item inventory system is considered. 2. Good quality items must be greater than the demand. 3. he production and rework rates are constant. 4. he demand rate, (say) R(t ) a( bt ) is function of time where a is scale demand and bdenotes the rate of change of demand. 5. he units in inventory deteriorate at a constant rate ;. 6. Set-up cost for rework process is negligible or zero. 7. Recoverable items are obtained during the production up time and scrapped items are generated during the rework up time. 2.2 Notations I : serviceable inventory level in a production up time I 2a : serviceable inventory level in a production down time I 3a : serviceable inventory level in a rework up time I : serviceable inventory level from rework up time I 4r : serviceable inventory level from rework process in rework down time I r : recoverable inventory level in a production up time I r3 : recoverable inventory level in a rework up time I : total serviceable inventory in a production up time I 2a : total serviceable inventory in a production down time I 3a : total serviceable inventory in a rework up time I : total serviceable inventory from a rework up time I 4r : total serviceable inventory from rework process in a rework down time I r : total recoverable inventory level in a production up time I r3 : total recoverable inventory level in a rework up time : production up time 2a : production down time : rework up time 4r : rework down time sb : total production down time ub : production up time when the total production down time is equal to the upper bound of uniform distribution parameter
428 N.H.Shah, D.G.Patel, D.B.Shah / EPQ Model For Imperfect Production Proces I : inventory level of serviceable items at the end of production up time m I : maximum inventory level of recoverable items in a production up time mr I : total recoverable inventory w P : production rate P : rework process rate R Rt : demand rate; x : product defect rate x : product scrap rate a bt, a, b : deteriorate at a constant rate ;. A : production setup cost h : serviceable items holding cost h : recoverable items holding cost S : scrap cost C S L : lost sales cost C d : Cost of deteriorated units C : total inventory cost : cycle time C : total inventory cost per unit time for lost sales model C : total inventory cost per unit time for without lost sales model NL C : total inventory cost per unit time for lost sales model with uniform U distribution preventive maintenance time C : total inventory cost per unit time for lost sales model with exponential E distribution preventive maintenance time
N.H.Shah, D.G.Patel, D.B.Shah / EPQ Model For Imperfect Production Proces 429 3. MAHEMAICAL MODEL he rate of change of inventory is depicted in Figure.During production period, a, x defective items per unit time are to be reworked. he rework process starts at the end of time. he rework time ends at time period. he production rates of good items and defective items are different. During the rework process, some recoverable and some scrapped items are obtained. LIFO policy is considered for the production system. So, serviceable items during the rework up time are utilized before the fresh (new) items from the production up time. he new production cycle starts when the inventory level reaches zero at the end of 2a time period. Because machine is under maintenance, which is randomly distributed with probability density function f t,the new production cycle may not start at time 2a. he production down time may result in shortage 3 - time period. he production will start after the 3 time period. Inventory level I m 4r 2a 2 3 ime Figure : Inventory status of serviceable items with lost sales Under above mentioned assumptions, the inventory level during production up time can be described by the differential equation d I t dt P R t x I t, t () he inventory level during rework up time is governed by the differential equation d I dt t P R t x I t, t (2) he rate of change of inventory level during production down time is
43 N.H.Shah, D.G.Patel, D.B.Shah / EPQ Model For Imperfect Production Proces d I t 2a 2a dt 2a R t I t, t and during rework down time is d I t 4r 4r dt 4r 2a 2a 2a 2a 2a R t I t, t 4r 4r 4r 4r 4r Under the assumption of LIFO production system, the rate of change of inventory of good items during rework up time and down time is governed by d I dt (5) t 3a 3a 3a I t, t 3a 3a 3a 4r Using I a, the inventory level in a production up time is t ab t 2 I t P a x e e t he total inventory in a production up time is a I I t dt Using, Using I, solution of (2) is t ab t 2 I t P a x e e t (8) and total inventory in a rework up time is 3 r I I t dt (9) I4r t 4r, solution of (4) is a (4 r t 4r ) ab (4 4 4 4 r t r ) ab ( r t r ) I4r t4r e e 2 4re () And hence the total inventory of serviceable items during rework down time is 4 r 4r 4r 4r 4r I I t dt () Similarly, using I the total inventory during production down time is 2a 2a, (3) (4) (6) (7)
N.H.Shah, D.G.Patel, D.B.Shah / EPQ Model For Imperfect Production Proces 43 2 a 2a 2a 2a 2a I I t dt (2) Now, the maximum inventory level is ab 2 Im I a a P a x e e a Hence, the total inventory in a rework up time is (3) I 2 3a Im 3 r 4r 3 r 4 r 2 (4) Next, we analyze the inventory level of recoverable items. (Figure I Mr x Figure 2: Inventory status of recoverable items ime Using up time is he rate of change of recoverable items in a production up time is d I t r r dt r x I t, t r r r (5) Ir, the inventory level of the recoverable items during the production x t r I t e, t r r r hence, total recoverable items in a production up time is (6) a I I ( t ) dt (7) r r r r
432 N.H.Shah, D.G.Patel, D.B.Shah / EPQ Model For Imperfect Production Proces Initially, the recoverable inventory is x a I I e 2 x a 2 Mr r he rate of change of inventory level of recoverable item during the rework up time is governed by differential equation d I t r3 r3 dt r3 Using, P I t, t r3 r3 r3 r3 I t, the solution of equation (9) is (8) (9) P r3 tr3 I t e (2) r3 r3 he total inventory of recoverable item during rework up time is 3 r I I ( t ) dt (2) r3 r3 r3 r3 he number of recoverable items is P 3 r I Mr Ir3 e (22) Since and using aylor's series approximation, equation (22) gives I P Mr (23) Substituting I Mr from equation (8) in equation (23), we get 2 x a P 2 otal recoverable items (24) I I I (25) w r r3 otal number of units deteriorated is
N.H.Shah, D.G.Patel, D.B.Shah / EPQ Model For Imperfect Production Proces 433 a 3 r 2 a 4r DU P Rtdt P Rtdt Rtdt x 3 r (26) Since the inventory level at the beginning of the production down time is equal to the inventory level at the end of the production up time minus the deteriorated units at, using Misra(975), the approximation concept, we have 4r ab 2 2 2a P a x a a 3 r 4 r 3 r 4 r a 2 2 (27) he inventoryfor serviceable item in rework process is I I 4r by simple calculations P a x a 2 4 r 3 r 3 r (28) Using equations (24) and (28), 2a given in equation (27) is only a function of. he total production cost of inventory system is sum of production set up cost, holding cost of serviceable inventory, deteriorating cost of recoverable inventory cost, and scrap cost. herefore, C A h I I I I I h I C DU S x total replenishment time is 2a 4r 3a w d C (29) (3) 2a 4r he total cost per unit time without lost sales is given by C NL C (3) he optimal production up time for the EPQ model without lost sales is the solution of dc NL d (32) Lost sales will occur when maintenance time of machine is greater than the production down-time period. So the total inventory cost in this case is
434 N.H.Shah, D.G.Patel, D.B.Shah / EPQ Model For Imperfect Production Proces 2 4 E C C S R t t f t dt (33) L a r t2a4r the total cycle time for lost sales scenario is 2a 4r E t f t dt (34) t2a4r Using equations (33) and (34), the total cost per unit time for lost sales scenario is E C 3.. Uniform distribution Case E C (35) E Define the probability distribution function time t follows uniform distribution as follows. f t substituting, t, otherwise f t, when the preventive maintenance f t in equation (35) gives total cost per unit time for uniform distribution as SL 2a 4r 3a w d C ( ) 2a 4r A h I I I I I h I C DU S x a bt t dt CU t dt 2a 4r 2a 4r (36) he optimal production up time for lost sales case is solution of dc U d (37) o decide whether manufacturer should allow lost sales or not, we propose following steps (Wee and Widyadana (2)): Step : Calculate from equation (32). Hence calculate 2a from equation (27) and from equation (28). Set sb 2a 4r. 4r Step 2: If sb, then non lost sales case is not feasible, and go to step 3; otherwise the optimal solution is obtained.
N.H.Shah, D.G.Patel, D.B.Shah / EPQ Model For Imperfect Production Proces 435 Step 3: Set. Find ub using equations (27) and (28). Calculate NL sb ub C using equation (3). Step 4: Calculate from equation (37), hence 2a from equation (27) and 4r from equation (28), and set. 2 4 Step 5: If sb NL C If sb ub sb a r Step 6: If C C is then optimal production up time is ub NL ub U 3.2. Exponential distribution case Define the probability distribution function, then, calculate C using equation (36). time t follows exponential distribution with mean as,. f t e t U and, then optimal production up time ub ; otherwise it Here, the total cost per unit time for lost sales scenario is f t, when the preventive maintenance C E t C SL Rtt 2a 4r e dt t 2a4r e 2a4r he optimal can be obtained by setting (38) dc E d he convexity of (39) C NL, C U and/or suitable values of inventory parameters. CE has been established graphically with 4. NUMERICAL EXAMPLE AND SENSIIVIY ANALYSIS In this section, we validate the proposed model by numerical example. First, we consider uniform distribution case. ake A $2 per production cycle, P, units per unit time, P 4 units per unit time, a 5 units per unit time, b %, x 5 units per unit time, x 4 units per unit time, h $5 per unit per
436 N.H.Shah, D.G.Patel, D.B.Shah / EPQ Model For Imperfect Production Proces unit time. h $3 per unit per unit time, SL $ per unit, SC $2 per unit, Cd $. per unit, % and the preventive maintenance time is uniformly distributed over the interval,.. Following algorithm with Maple 4, the optimal production up time a.9 years and the corresponding optimal total cost per unit time is CU $4448. he convexity of CU is exhibited in Figure 3. Figure 3: Convexity of otal Optimal Cost with Uniform Distribution he sensitivity analysis is carried out by changing one parameter at a time by 4%, 2%, 2% and 4%. he optimal production up time and the total cost per unit time for different inventory parameters are exhibited in able. able Sensitivity analysis of and total cost when preventive maintenance time for uniform and exponential distribution.
N.H.Shah, D.G.Patel, D.B.Shah / EPQ Model For Imperfect Production Proces 437 Parameter Percentage change Uniform Distribution Exponential Distribution λ = 2 C C -4%.779969 478.52832.395745 53.72373-2%.86 4263.88422.398498 55.7946 A P P A B X.9477 4447.96835.448682 56.4344 2%.23455 463.6699.428994 57.776849 4%.8878 48.99858.453765 59.8693-4% Not Feasible Not Feasible.833372 4497.76988-2%.993 44.2884.232542 482.9679.9477 4447.96835.448682 56.4344 2%.7688684 4787.228599.6448 5282.346729 4%.59274 586.9393.83233 5389.345959-4%.8683393 47.523848.4635758 556.829-2%.26929 4526.77856.423237 5258.883.9477 4447.96835.448682 56.4344 2%.7362559 442.35848.3858965 523.8886 4%.598946 44.92947.37554578 4958.73854-4% Not Feasible Not Feasible.6585422 379.2559-2%.724647 496.53895.972695 4449.53627.9477 4447.96833.448682 56.4344 2%.6785454 4733.262382.24924 578.55356 4%.273755232 58.486552.3435664 6269.66484-4%.95725 4445.37723.395577 54.42662-2%.92883 4446.642683.3979946 5.4343.9477 4447.96833.448682 56.4344 2%.953349 4449.69487.4299393 522.423958 4%.9659774 445.4364.455295 528.4696-4%.465638 438.549344.3576995 4949.25556-2%.667342 4382.428699.3786425 532.59567.9477 4447.96833.448682 56.4344 2%.227566 455.978.4232828 52.8244 4%.528823 4584.23734.4478828 5286.537699
438 N.H.Shah, D.G.Patel, D.B.Shah / EPQ Model For Imperfect Production Proces Parameter Percentage change Uniform Distribution Exponential Distribution λ = 2 C C -4%.99354 4386.374.39884967 554.344838-2%.93267 446.94324.39966795 585.37346.9477 4447.96833.448682 56.4344 2%.954249 4478.94682.43627 547.5222 4%.96254 459.936823.42263 578.646666-4%.84445 3929.6876.559236 4453.22532-2%.5979 49.9873.44782689 479.825835 h h S L S c Θ.9477 4447.96833.448682 56.4344 2%.8243755 472.88287.3582679 543.36776 4%.75962 4954.945599.322882 5736.7556-4%.9492258 4429.38983.4379577 593.62-2%.9449696 4438.645749.423774 54.73522.9477 4447.96833.448682 56.4344 2%.9364678 4457.6425.39884294 528.5837 4%.932222 4466.4799.397265 539.78676-4%.6222274 4429.33489.22394 47.2285-2%.857269 444.6694.398443 493.3235.9477 4447.96833.448682 56.4344 2%.2885 4452.9983.4683526 5273.7982 4%.926483 4456.59729.5275659 548.88796-4%.94866 4327.54245.43436 4997.9337-2%.94292 4387.724673.4943 557.8223.9477 4447.96833.448682 56.4344 2%.9446 458.88927.45888 575.677688 4%.939563 4568.27952.399635 5234.923957-4%.9485646 4454.42558.395745 53.72378-2%.946895 445.5998.398498 55.79422.9477 4447.96833.448682 56.4344 2%.924698 4444.69274.428994 57.776842 4%.985698 444.58265.453765 59.8694
N.H.Shah, D.G.Patel, D.B.Shah / EPQ Model For Imperfect Production Proces 439 Figure 4: Sensitivity analysis of production up time for uniform distribution Figure 5: Sensitivity analysis of total cost for uniform distribution
44 N.H.Shah, D.G.Patel, D.B.Shah / EPQ Model For Imperfect Production Proces Figure 6: Sensitivity analysis of production up time for exponential distribution Figure: 7 Sensitivity analysis of total cost for exponential distribution It is observed from figure 5 that the optimal production up time is slightly sensitive to changes in P, and a, moderately sensitive to changes in and b, and insensitive to
N.H.Shah, D.G.Patel, D.B.Shah / EPQ Model For Imperfect Production Proces 44 changes in other parameters. is negative related to P and and positively related to a and. Figure 6 exhibits variations in the optimal total cost per unit time with uniform distribution. he optimal total cost is slightly sensitive to changes in a, P, x, Cd and h ; moderately sensitive to changes in A,, Sc,, x and SL and insensitive to changes in other parameters. ake mean of exponential distribution as 2. he optimum total cost is $ 56 when the optimal production up time is.4 years. he convexity of the total cost is shown in Figure 8. Figure 8: Convexity of otal Optimal Cost with Exponential Distribution From Figure6, for lost sales with exponential distribution, it is observed that the optimal production up time is slightly sensitive to changes in P and a, moderately sensitive to changes in the parameter and, and insensitive to changes in other parameters. he optimal production up time is negatively related to P, b and, and positively related to the value of a. In Figure7, variations in the optimal total cost is studied. Observations are similar tothe uniform distribution case. 5. CONCLUSIONS In this research, the economic production quantity model for deteriorating items is studied when demand is time dependent. he rework of the items is allowed and random preventive maintenance time is incorporated. he model considers lost sales. he probability of machine preventive maintenance time is assumed to be uniformly and exponentially distributed. It is observed that the production up time is sensitive to demand rate and deterioration. It suggests that the manufacturer should control deterioration of units in inventory by using proper storage facilities. he optimal total cost per unit time is sensitive to changes in the holding cost, the product defect rate, and the production rate in both the distributions. his suggests that the manufacture should
442 N.H.Shah, D.G.Patel, D.B.Shah / EPQ Model For Imperfect Production Proces depute an efficient technician to reduce preventive maintenance time. his model has wide applications in manufacturing sector. Because of using machines for a long period of time,manufacturer facesimproper production, some customers are not satisfied with the quality of the production so, manufacturer has to adopt rework policy.future research by considering constraints on the machine s output, machine s life time will be worthy. Acknowledgements: Authors would like to thank all the anonymous reviewers for their constructive suggestions. REFERENCES [] Abboud, N. E., Jaber, M. Y., and Noueihed, N. A., Economic Lot Sizing with the Consideration of Random Machine Unavailability ime, Computers & Operations Research, 27 (4) (2) 335-35. [2] Cardenas-Barron, L. E., On optimal batch sizing in a multi-stage production system with rework consideration, European Journal of Operational Research, 96(3) (29) 238-244. [3] Chiu, S. W., Optimal replenishment policy for imperfect quality EMQ model with rework and backlogging, Applied Stochastic Models in Business and Industry, 23 (2) (27) 65-78. [4] Chiu, S. W., Gong, D. C., and Wee, H.M., Effect of random defective rate and imperfect rework process on economic production quantity model, Japan Journal of Industrial and Applied Mathematics, 2 (3) (24) 375-389. [5] Chiu, S.W., ing, C. K., and Chiu, Y. S. P., Optimal production lot sizing with rework, scrap rate, and service level constraint, Mathematical and Computer Modeling, 46 (3) (27) 535-549. [6] Chung, C. J., Widyadana, G. A., and Wee, H. M., Economic production quantity model for deteriorating inventory with random machine unavailability and shortage, International Journal of Production Research, 49 (3) (2) 883-92. [7] Dobos, I., and Richter, K., An extended production/recycling model with stationary demand and return rates, International Journal of Production Economics, 9(3)(24), 3-323. [8] Flapper, S. D. P., and eunter, R. H., Logistic planning of rework with deteriorating work-inprocess, International Journal of Production Economics, 88 () (24) 5-59. [9] Inderfuth, K., Lindner, G., and Rachaniotis, N. P., Lot sizing in a production system with rework and product deterioration, International Journal of Production Research, 43 (7) (25) 355-374. [] Jamal, A. M. M., Sarker, B. R., and Mondal, S., Optimal manufacturing batch size with rework process at a single-stage production system, Computer & Industrial Engineering, 47 () (24) 77-89. [] Khouja, M., he economic lot and delivery scheduling problem: common cycle, rework, and variable production rate, IIE ransactions, 32 (8) (2) 75-725. [2] Koh, S. G., Hwang, H., Sohn, K. I., and Ko, C. S., An optimal ordering and recovery policy for reusable items, Computers & Industrial Engineering, 43 (-2) (22) 59-73. [3] Meller, R. D., and Kim, D. S., he impact of preventive maintenance on system cost and buffer size, European Journal of Operational Research, 95 (3) (2) 577-59. [4] Misra, R. B., Optimum production lot-size model for a system with deteriorating inventory, International Journal of Production Research, 3 (5) (975) 495-55. [5] Schrady, D. A., A deterministic inventory model for repairable items, Naval Research Logistics,4 (3) (967) 39-398. [6] Sheu, S. H., and Chen, J. A., Optimal lot-sizing problem with imperfect maintenance and imperfect production, International Journal of Systems Science, 35() (24) 69-77.
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