DEVELOPMENT OF THE INVENTORY SYSTEM OF RAW MATERIALS IN PHARMACEUTICAL INDUSTRY USING EOQ METHOD

Transcription

1 DEVELOPMENT OF THE INVENTORY SYSTEM OF RAW MATERIALS IN PHARMACEUTICAL INDUSTRY USING EOQ METHOD Sisca Dianawati 1) and Bobby O. P. Soepangkat Master s Program in Management of Technology, Institut Teknologi Sepuluh Nopember Jl. Cokroaminoto 12A, Surabaya, 60264, Indonesia 1) sisca.nawa@gmail.com ABSTRACT PT. X is a pharmaceutical industry founded in 1970 and producing medicinal (pharma) and nutrition products for export (in the Southeast Asia region) and local. Production planning created by the Department of PPIC quite often has to be adjusted in accordance with the company condition. Inventory system of raw materials in PT.X is conducted based on the warehouse stock data, wherein the policy was established by the Department of PPIC. This inventory system of raw materials has not been reviewed and updated in order to be able to keep up with the current condition of the company. Therefore, it is necessary to develop a new structured inventory system to maintain an effective and efficient production process. The first step in developing the inventory system is to select the appropriate forecasting model to predict the required raw material, based on the demand of medicinal products and raw material consumption. The second step is to collect lead time and demand of raw materials during lead time data. The third step is to calculate ordering cost, holding costs and expected stock out of materials required to determine when and how many economic order of quantity (EOQ), the reorder point and the size of the safety stock for obtaining the minimum total inventory cost. Keywords: economic order of quantity (EOQ), forecasting, inventory system. INTRODUCTION PT. X is one of pharmaceutical industries which distributing the products for export (in the Southeast Asia region) and local. There are two types of products, medicinal (pharma) and nutrition products. Medicinal products are multivitamins, antibiotics, pain reliever syrup and pedialite solution. In its operations, inventory system of raw material prepare material stock for a certain period (make to order) with purchase order (PO) three months earlier. For local products produced by having stock, because the demand smaller than production capacity. Production Planning and Inventory Control (PPIC) Department create production planning based on approved demand statement (ADS) for local and export demand. Inventory system does not consider uncertainty lead time of arrival raw materials while prepare safety stock for fluctuating demand. If previous planning can not realized, lead time for producing can be longer. This condition can delay or cancel distribution products to customers. A-1-1

2 Picture 1. Demand versus actual production for multivitamin export Picture 2. Demand versus actual production for multivitamin local Picture 1 and Picture 2 show unfilled demand demand during seven month period caused by uncertainty, production process must be updated by the current condition of the company. In this paper, forecasting and EOQ method are used to obtain effective production process with minimal inventory costs. METHODOLOGY Forecast Forecasting is collecting data from past events to predict future events. There are two basic steps to get accurate forecasting (Hanke et al., 2001). The first step is to collect data which have purpose of forecasting and information to get accurate forecasting. The second step is to choose the right forecasting method which will be used for processing data. Steps for forecasting of raw materials shown in Picture 3. A-1-2

3 Start A Data the needs of the raw material from multivitamin in the past Calculate forecasting error Stationerity process data variance and mean Compare with the other model Identification ARIMA model based on ACF and PACF graph Choose the correct forecasting model Is lag significant? Check the other model End Statistic test parameter model Is parameter significant? Independent test residual model Is residual independent? Distribution test of model Is normal distribution? A Picture 3. Steps for forecasting A-1-3

4 Development of The Inventory System Management try to determine the optimum inventory of raw material policies which can ensure a effective production process and get minimal cost. For this purpose, economic order quantity (EOQ) method can be used to determine: a. Optimum order quantity of raw material. b. Minimum inventory costs of raw material. c. Reorder point of raw material. d. Optimum safety stock of raw material. Development of the inventory system of the company consists of five steps, which can be described as follows: 1. Calculate the average demand of raw materials during lead time (M ) and the average of lead time (D ). 2. Test the distribution for the required raw material during lead time and lead time data, whether the data have normal distribution or not. 3. Calculate optimum order quantity (Q opt ) using iteration methods and follow this steps: a. The first iteration process to find Q 1 value using deterministic model with this equation (Tersine, 1994): with Q = order quantity C = ordering cost per order R = average annual demand H = holding cost Then, determine the size of reorder point (B 1 ) and E (M > B 1 ) with the following equation: B = M + S = M + Z α. σ (2) with B = reorder point M = average lead time demand S = safety stock Z α = standard normal deviate σ = standard deviation of lead time demand (1) with E (M > B) = expected stockout during lead time (3) = probability density function in normal distribution = cumulative distribution function in normal distribution b. The second iteration process to find Q 2 value using probabilistic models, and B 2 for finding E (M > B 2 ) value. (4) with A = backordering cost A-1-4

5 c. The next iteration process using probabilistic model as well as at second iteration to obtain E ( M > B i ) value which is equal to E (M> B i-1 ). In other words, the iteration process stops if optimum point has been reached. 4. Calculate safety stock by the equation below: 5. Calculate total inventory costs with the following equation: with TC = total cost P = purchase cost (5) (6) RESULTS AND DISCUSSION In this paper, forecasting determination by using ARIMA. The smallest value of forecasting error used to determine forecasting model (Makridakis, 1999). Minitab 16 is used to obtain forecasting of each raw material for 12 next periods (see picture 4). (a) (b) (c) (d) A-1-5

6 (e) (f) (g) (h) (i) (j) Picture 4. For raw material : (a) OMP, (b) AAC, (c) RBV, (d) PVF, (e) AFO, (f) PRN, (g) THN, (h) CLM, (i) NCN, (j) OOY Forecasting result using ARIMA model have the upper limit and lower limit, iit can be used to estimate how much influence the raw material requirement are changing. Figure 4 shows that the actual demand is still in upper limit and lower limit. Therefore, forecasting result from ARIMA model can be used to determine inventory system. Forecasting results of raw materials for next 12 periods are used to determine optimal order quantity (EOQ), the size of reorder point (ROP), and the size of safety stock (SS). The A-1-6

7 calculating results of EOQ, ROP, SS are shown in Table 1. Then, next step is calculating minimum total inventory cost of each raw material, it is shown in Table 2. Table 1. Parameter inventory system management of raw material Raw material EOQ (kg) P (M>B) ROP (kg) SS (kg) OMP AAC RBV PVF AFO PRN THN CLM NCN OOY Forecast 70, , , ,98683 Upper 106, , , ,33464 Lower 46, , , ,56247 Forecast 197, , , ,25663 Upper 258, , , ,17306 Lower 107, , , ,74586 Forecast 18, , , , Upper 24, , , , Lower 13, , , ,54479 Forecast 41, , , , Upper 62, , , , Lower 27, , , , Forecast 6, , , , Upper 9, , , , Lower 4, , , , Forecast 15, , , , Upper 20, , , , Lower 11, , , , Forecast 18, , , , Upper 28, , , , Lower 12, , , , Forecast 24, , , , Upper 33, , , , Lower 18, , , , Forecast 37, , , ,12832 Upper 56, , , , Lower 24, , , , Forecast 16, , , , Upper 22, , , , Lower 12, , , , A-1-7

8 Table 2. Total inventory cost of raw material Raw material OMP AAC RBV PVF AFO PRN THN CLM NCN OOY Ordering Cost (OC) Holding Cost (HC) Purchasing Cost (PC) Stockout Cost (SC) Total Cost (TC) Forecast Rp ,41 Rp ,62 Rp ,38 Rp ,41 Rp ,82 Upper Rp ,19 Rp ,57 Rp ,98 Rp ,66 Rp ,40 Lower Rp ,21 Rp ,57 Rp ,84 Rp ,23 Rp ,85 Forecast Rp ,28 Rp ,90 Rp ,84 Rp ,40 Rp ,41 Upper Rp ,24 Rp ,39 Rp ,49 Rp ,98 Rp ,10 Lower Rp ,74 Rp ,81 Rp ,19 Rp ,88 Rp ,61 Forecast Rp ,36 Rp ,24 Rp ,12 Rp ,16 Rp ,88 Upper Rp ,52 Rp ,37 Rp ,15 Rp ,52 Rp ,57 Lower Rp ,33 Rp ,98 Rp ,26 Rp ,06 Rp ,62 Forecast Rp ,84 Rp ,91 Rp ,98 Rp ,66 Rp ,40 Upper Rp ,34 Rp ,96 Rp ,66 Rp ,04 Rp ,00 Lower Rp ,18 Rp ,15 Rp ,14 Rp ,74 Rp ,22 Forecast Rp ,60 Rp ,08 Rp ,01 Rp ,77 Rp ,47 Upper Rp ,41 Rp ,12 Rp ,64 Rp ,14 Rp ,31 Lower Rp ,31 Rp ,90 Rp ,10 Rp ,22 Rp ,52 Forecast Rp ,86 Rp ,10 Rp ,87 Rp ,14 Rp ,96 Upper Rp ,12 Rp ,45 Rp ,85 Rp ,64 Rp ,06 Lower Rp ,68 Rp ,17 Rp ,65 Rp ,82 Rp ,32 Forecast Rp ,12 Rp ,90 Rp ,99 Rp ,60 Rp ,62 Upper Rp ,01 Rp ,97 Rp ,16 Rp ,35 Rp ,50 Lower Rp ,88 Rp ,13 Rp ,24 Rp ,25 Rp ,51 Forecast Rp ,37 Rp ,93 Rp ,26 Rp ,71 Rp ,27 Upper Rp ,45 Rp ,45 Rp ,28 Rp ,90 Rp ,08 Lower Rp ,22 Rp ,99 Rp ,44 Rp ,75 Rp ,40 Forecast Rp ,56 Rp ,52 Rp ,00 Rp ,01 Rp ,09 Upper Rp ,36 Rp ,18 Rp ,25 Rp ,36 Rp ,16 Lower Rp ,61 Rp ,68 Rp ,12 Rp ,41 Rp ,81 Forecast Rp ,60 Rp ,36 Rp ,71 Rp ,22 Rp ,90 Upper Rp ,73 Rp ,60 Rp ,50 Rp ,67 Rp ,50 Lower Rp ,11 Rp ,69 Rp ,50 Rp ,31 Rp ,61 The management of PT. X made policies for the size of safety stock of raw materials for two weeks until one month, however, the policy has not been reviewed to be adjusted to current conditions. So, the inventory system management more structure will be needed for determining optimal the size of safety stock with minimum cost. Based on EOQ method, the comparison of costs between the current policies and calculation results are shown in Table 3.. A-1-8

9 Table 3. Comparison safety stock (SS) and total cost (TC) No. Raw material SS policy (kg) SS research (kg) TC policy TC research Decreasing cost (%) 1 OMP 5,69 418,99 Rp ,91 Rp ,82-1,74 2 AAC 183,00 404,26 Rp ,69 Rp ,41 60,52 3 RBV 2,37 26,93 Rp ,52 Rp ,88-27,20 4 PVF 29,60 43,42 Rp ,65 Rp ,40 24,79 5 AFO 2,06 1,98 Rp ,22 Rp ,47-44,94 6 PRN 6,17 7,32 Rp ,41 Rp ,96-30,94 7 THN 4,23 23,95 Rp ,89 Rp ,62 12,56 8 CLM 24,29 14,78 Rp ,06 Rp ,27 22,22 9 NCN 15,03 24,13 Rp ,76 Rp ,09 41,69 10 OOY 0,76 41,99 Rp ,11 Rp ,90 5,36 Total Rp ,21 Rp ,82 Rp ,39 CONCLUSIONS AND RECOMMENDATIONS Forecasting demand using ARIMA models with upper and lower limits can be used to supply raw materials for uncertainty demand. Inventory policies in company must be reviewed with order lead time and lifetime of raw materials. Inventory system with EOQ method can saving total inventory cost Rp ,39. REFERENCES Hanke, J. E. dan Arthur, G. R. (2001), Business Forecasting, Sixth Edition, Prentice Hall, Upper Saddle River, New Jersey. Makridakis, S., Wheelwright, S.C. dan McGee, V.E. (1999), Metode dan Aplikasi Peramalan, Edisi Kedua, Terjemahan Binarupa Aksara, Jakarta. Tersine, R.J. (1994), Principles of Inventory and Materials Managements, Fourth Edition, Prentice-Hall, New Jersey. A-1-9