HIZLI FOURIER DÖNÜŞÜMÜ ALGORİTMASI İLE DÜZENSİZ TALEP ALTINDA İŞ YÜKÜ ÖNGÖRÜSÜ

Year 2020, Volume: 38 Issue: 1, 97 - 114, 31.03.2020

Onur Koyuncu , Erdem Turfan

https://doi.org/10.17065/huniibf.463143

Abstract

Düzensiz talep altında öngörüde bulunma oldukça zahmetli bir süreç olup, klasik öngörü yöntemlerinden verim almak oldukça zordur. Bu çalışmada incelenen firmanın üretim talep yapısı da düzensiz seyretmektedir ve firma vazgeçilmez süreç geliştirme faaliyetlerini planlayabilmek için iş yükü öngörüsüne ihtiyaç duymaktadır. Öngörülecek iki parametre toplam üretim hacmi ve fason üretim miktarının toplam üretime oranı şeklinde belirlenmiştir. Göreceli daha düzenli bir yapı sergileyen fason üretim oranı öngörüleri durağan öngörü yöntemiyle gerçekleştirilmiştir. Daha kritik olan düzensiz toplam üretim miktarı ise Hızlı Fourier Dönüşüm algoritmasıyla hesaplanmıştır. Toplam üretim parametresi ayrıca tahmin güvenilirliği ölçümü amacıyla bir yıl boyunca gözlenmiştir. Gözlenen Ortalama Mutlak Hata Yüzdeleri %11 (fason üretim oranı) ve %14-%22 (toplam üretim miktarı) olarak hesaplanmış ve düzensiz talep göz önüne alındığında kabul edilebilir olarak değerlendirilmiştir. 

Keywords

Öngörü, düzensiz talep, kesikli fourier dönüşümü

WORKLOAD FORECASTING UNDER ERRATIC DEMAND USING FAST FOURIER TRANSFORM ALGORITHM

Abstract

Forecasting process may become cumbersome under erratic demand structures where no conventional methodology seems to provide plausible outcomes. The company investigated in this paper is subject to this condition and needs to forecast the workload in order to plan the indispensable process enhancement activities. Two parameters to be forecasted are the total production volume and the ratio of in-house production ratio with respect to the total production. The required forecasts for relatively regular structured in-house production to total production ratio were computed via static forecasting. The more important erratic structured total production volume forecasts were computed using FFT (Fast Fourier Transform) algorithm. Total production was further observed during the next year to check the reliability of the forecasts. The resulting respective MAPEs (Mean Absolute Percentage Errors) of approximately 11% (in-house ratio) and 14-22% (total production) were considered acceptable under the erratic demand structure.

Keywords

Forecasting, erratic demand, discrete fourier transform

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