“ ” SENIOR DESIGN PROJECT: IMPROVING THE DEMAND FORECAST AND RAW MATERIAL ORDER POLICY TO MINIMIZE STOCK COSTS IN GÜL PRES DÖKÜM SANAYİ A.Ş ADVISOR : A.

... konulu sunumlar: "“ ” SENIOR DESIGN PROJECT: IMPROVING THE DEMAND FORECAST AND RAW MATERIAL ORDER POLICY TO MINIMIZE STOCK COSTS IN GÜL PRES DÖKÜM SANAYİ A.Ş ADVISOR : A."— Sunum transkripti:

1 “ ” SENIOR DESIGN PROJECT: IMPROVING THE DEMAND FORECAST AND RAW MATERIAL ORDER POLICY TO MINIMIZE STOCK COSTS IN GÜL PRES DÖKÜM SANAYİ A.Ş ADVISOR : A SSOCıATE P ROF. C EMAL D ENIZ YENIGÜN YILDIRAY YILDIRIM LORİ POLAT NAZ FATOŞ MERZİFONLU AYŞEGÜL TEKİN

2 OUTLINE 1. INFORMATION ABOUT THE COMPANY 2. PROBLEM DEFINITION 3. FORECASTING 4. NEW ORDER POLICY 5. COMPARISON WITH EXISTING POLICY 6. Q&A

3 1) INFORMATION ABOUT THE COMPANY Established in 1978 Manufactures water and gas valves and faucets, radiator valves and bath & kitchen taps Manufactures all it’s products in its own building in Beylikduzu It has 2 different manufacturing styles; pressing and casting.

4 In the GPD company, raw material is brass. Brass includes %58 copper %40 zinc and %2 lead. These metals kilogram price change according to exchange rates at the London Metal Exchange. Brass producers purchase these raw materials and turn them into brass sticks which can have different diameters. 58% Copper + 40% Zinc + 2% Lead = Brass

5 2) PROBLEM DEFINITION o Making a good forecast to create a raw material order policy! How much to order brass? When to order brass ? How much should be produced?

6 Forecasted Brass Amount vs. Observed Brass Amount Brass forecasts are made judgmentally and for whole year!

7

8  Raw Material Orders;  are not made according to forecast.  are made by employees when they need it or there are raw metarials more than they need o Hence, production distruptions are observed. o Stock cost is increased.

9 Based on the company’s problem we worked on; DEMAND FORECAST RAW MATERIAL DETERMINATION FOR PRODUCTION CREATING RAW MATERIAL ORDER POLICY

10 Why we worked on 2017;

11 3) FORECASTING METHODS  Exponential Smoothing 1. Simple Exponential Smoothing: Technique for data with no trend or seasonality. Simple Exponential Smoothing 2. Holt’s Method: Technique for data with trend but no seasonality. Holt’s Method 3. Holt-Winters Method: Technique for data with trend and seasonality. 3.a. Multiplicative Model the components multiply together to make the time series. If you have an increasing trend, the amplitude of seasonal activity increases. 3.b. Additive Model the components add together to make the time series. If you have an increasing trend, you still see roughly the same size peaks and troughs throughout the time series

12 What is Holt-Winters Seasonal Method  To make predictions using data with a trend and seasonality, we turn to the Holt- Winters Seasonal Method. This method can be implemented with an “Additive” structure or a “Multiplicative” structure, where the choice of method depends on the data set. The Additive model is best used when the seasonal trend is of the same magnitude throughout the data set, while the Multiplicative Model is preferred when the magnitude of seasonality changes as time increases.  Our data includes trend and seasonality so it is suitable for this method  All computations are held in R Studio

13 We can see the trend and seasonality!

14 Dynamic Forecast Model Fit Update 3-Step Forecast 6-Step Forecast 12-Step Forecast

15 12*12 holt winter tablosu gelicek

16 Mse hata hesaplamaları koyulacak  Biz hatalarını hesapladık en düşük 6month çıktı ama yine de ww hepsine uyguladık vs.

17 With the Multiplicative Model updating every 6 months;

18 OFFERED POLICY : WAGNER WITHIN ALGORITHM To prevent the interrupts on production line, companies often keep on hand stock that is ready to use. Inventory models answers two main questions. These are “when to order?” and “how much to order?” Objective; to minimize order(setup costs and inventory holding cost) Dynamic programming A and h do not have to be constant through the planning horizon. In this Project, 3 different Wagner-Within methods were examined. The lowest-cost method was selected. 3-Step Wagner Within Algorithm 6-Step Wagner Within Algorithm 12-Step Wagner Within Algorithm

19  Ordering and Setup Cost (A) Ordering costs are essentially costs incurred every time you place an order. These costs include all the paper work cost, transportation cost, finding supplier cost and receiving costs. In the company, transportation cost of 5 tons loaded trucks are 500TL (which is equal to 0.04TL per kilogram).  Holding and Carrying Cost (h) Holding costs are those associated with storing inventory that is not used for production. The Company has enough space and does not pay for holding brass in their inventory. However, money has opportunity cost. The Company can invest their money to bank and generate revenue.

20  3-Step Wagner Within Algorithm Quantity of Brass(Forecast) Quantity of Shavings F*Ordering CostHolding Cost Holding cost/tonne January (D1) 3.881.23.88A1500h193.12 24 February (D2) 3.781.13.78A2500h290.72 24 March (D3) 3.671.13.67A3500h388.08 24 April (D4) 7.132.17.13A41000h4171.12 24 May (D5) 7.452.27.45A51000h5178.8 24 June (D6) 7.762.37.76A61000h6186.24 24 July (D7) 16.715.06.6A71000h7158.616 24 August (D8) 16.825.016.82A82000h8403.68 24 September (D9) 17.935.47.9A91000h9188.904 24 October (D10) 8.32.58.3A101000h10199.2 24 November (D11) 6.642.06.64A111000h11159.36 24 December (D12) 6.72.06.7A121000h12160.8 24 (tonne) (tl) Year 2017

21 Total Cost: 11000

22  6-Step Wagner Within Algorithm Quantity of Brass(Forecast) Quantity of Shavings F*Ordering CostHolding Cost Holding cost/tonne 9.322.89.32A11000h1223.68 24 7.892.47.89A21000h2189.36 24 7.132.17.1A31000h3171.12 24 3.281.03.28A4500h478.72 24 5.91.82.8A5500h566.648 24 15.74.75.6A61000h6135.456 24 9.122.79.1A71000h7218.88 24 7.392.27.39A81000h8177.36 24 4.31.34.3A91000h9103.2 24 5.861.81.2A10500h1027.6 24 6.131.81.2A11500h1128.248 24 8.542.63.7A12500h1287.672 24 (tonne) (tl) Year 2017

23 Total Cost: 8278.609

24  12-Step Wagner Within Algorithm Months123456789101112 12500.07584.319210.960604.485764.7160659.5190617.4253829.6330839.7335149.8443331.1499411.4 2 10084.316183.445136.064934.2127796.3153988.8210835.0281532.3285551.8387702.7441191.7 3 17683.424362.230451.552202.861870.083725.2111682.3113304.9155196.3177406.0 4 27362.234588.669006.086214.7127713.1183009.2186310.3273309.9320167.0 5 31951.539796.545026.559215.179381.680635.7114630.8133321.7 6 42796.549023.871549.1107566.9109956.1177418.3215569.4 7 46026.549780.857784.758382.076371.986969.5 8 51780.859018.759738.984141.499474.7 9 59784.760168.677510.589769.4 10 58882.059313.459719.9 11 61813.466405.6 12 60719.9 Total cost: 19231

25  Şirketin kendi order policy costları

26 Buraya da 3 aylık 2019 ww konulacak 2019 da şu an dolar yükseliyor onun için 3 aylık ww uyguladık. Belki iyi çıkar. Eğer iyi çıkarsa diyeceğiz ki, stabil durumlarda örneğin 2017 yılı gibi yıllarda 6 aylık ww. Uygulanır ama 2018 ve 2019 gibi borsa dalgalanmasının sıkıntılı olduğu yıllarda 3aylık ww kullanılmasını önerdik.

27