Yıl: 2021 Cilt: 32 Sayı: 3 Sayfa Aralığı: 396 - 413 Metin Dili: İngilizce İndeks Tarihi: 05-09-2022

APPLYING FORECASTING METHODS TO REDUCE THE COST OF SPARE PARTS INVENTORY IN A COMPANY

Öz:
Any improvement on inventory cost provides financial benefits to companies and also increases customer satisfaction. In this study, it was aimed to reduce the cost of inventory of a construction equipment vendor with spare parts stock of ten thousand available out of almost fifty thousand registered items and increase in spare parts availability. The vendor company prepares spare part orders by using 12-month moving average of variable demand data. The research question was whether or not moving average method used by the company provides minimum cost and minimum lost sales. 36-month spare parts sales data were analyzed by using various forecasting methods. A sample group that best represents thousands of spare parts was selected for the analysis. A test period was picked out of 36-month time period and various forecasting methods were used for demand forecasting of this sample group. Stock on hand amount and lost sales amount were calculated for each demand forecast method and the method which provides minimum cost was determined.
Anahtar Kelime:

YEDEK PARÇA ENVANTER MALİYETİNİ DÜŞÜRMEK İÇİN TAHMİN YÖNTEMLERİNİN BİR ŞİRKETTE UYGULANMASI

Öz:
Envanter maliyetinde yapılacak herhangi bir iyileştirme, firmalara mali açıdan fayda sağlayacak ve ayrıca müşteri memnuniyetini arttıracaktır. Bu çalışmada, on bin kalemi stoklu yaklaşık elli bin kalem yedek parça envanter kaydına sahip bir iş makinesi satıcı firmasının stok maliyetinin azaltılması ve yedek parça bulunabilirliğinin arttırılması amaçlanmıştır. Satıcı firma, hâlihazırda yedek parça stok siparişlerini değişken talep verisinin 12 aylık hareketli ortalamasını kullanarak hazırlamaktadır. Araştırma sorusu, şirketin kullandığı hareketli ortalama yönteminin en az maliyet ve en az kayıp satışa neden olup olmadığıydı.36 aylık yedek parça satış rakamları farklı istatistiksel talep tahmin yöntemleriyle analiz edilmiştir. Binlerce yedek parça kalemini en iyi temsil eden bir örnek grubu seçilmiştir. 36 aylık periyot içinden bir test periyodu belirlenmiş ve farklı talep tahminleri yöntemleri bu örnek yedek parça grubunun talep tahminleri için kullanılmıştır. Her bir tahmin yönteminin yol açtığı stok tutma maliyeti ve kayıp satış maliyeti hesaplanmış ve mevcut talep tahmin yönteminden daha az maliyet sağlayan yöntem tespit edilmiştir.
Anahtar Kelime:

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
  • Boylan, J. E., Syntetos, A. A. & Karakostas, G. C. (2008). Classification for forecasting and stock control: a case study. Journal of the Operational Research Society, 59, 473–481. Doi: https://doi.org/10.1057/palgrave.jors.2602312
  • Box, G. E. P. & Jenkins, G. M., (1968). Some recent advances in forecasting and control. Journal of the Royal Statistical Society. Series C (Applied Statistics), 17(2), 91-109. Doi: https://doi.org/ 10.2307/2985674
  • Businger, M. & Read, R. R. (1999). Identification of demand patterns for selective processing: a case study. Omega International Journal Management Science, 27, 189-200. Doi: https://doi.org/10.1016/S0305-0483(98)00039-5
  • Cavalieri, S., Garetti, M., Macchi, M. & Pinto, R. (2008). A decision-making framework for managing maintenance spare parts. Production Planning & Control, 19(4), 379-396. Doi: https://doi.org/ 10.1080/09537280802034471
  • Chen, Y., Liu, P. & Yu, L. (2010). Aftermarket demands forecasting with a Regression-Bayesian-BPNN model. IEEE International Conference on Intelligent Systems and Knowledge Engineering. Doi: https://doi.org/10.1109/ISKE.2010.5680793
  • Chitale, A. K. & Gupta, R. C. (2014). Materials management a supply chain perspective: text and cases. Third Edition, PHI Learning Private Limited. Retrieved from https://books.google.com.tr/ books?id=oYdHBQAAQBAJ
  • Croston, J. D. (1972). Forecasting and stock control for intermittent demands. Journal of the Operational Research Society, 23, 289–304. Doi: https://doi.org/10.1057/jors.1972.50
  • Hyndman, R. J. & Athanasopoulos, G. (2018). Forecasting: principles and practice, 2nd edition. Retrieved from https://otexts.com/fpp2/
  • Jiafu, R., Zongfang, Z. & Fang, Z. (2009). The forecasting models for spare parts based on ARMA. WRI World Congress on Computer Science and Information Engineering. Doi: https://doi.org/10.1109/ CSIE.2009.315
  • Kim, T. Y., Dekker, R. & Heij, C. (2017). Spare part demand forecasting for consumer goods using installed base information. Computers & Industrial Engineering, 103, 201-215. Doi: https://doi.org/10.1016/j.cie.2016.11.014
  • Makridakis, S., Wheelwright S. C. & Hyndman, R. J. (1998). Forecasting: methods and applications, Third edition. New Jersey, USA: Wiley.
  • McKinsey&Company Inc. (2017). The changing aftermarket game and how automotive suppliers can benefit from arising opportunities. Retrieved from https://www.mckinsey.com/~/media/ McKinsey/Industries/Automotive%20and%20Asse mbly/Our%20Insights/The%20changing%20after market%20game%20and%20how%20automotive %20suppliers%20can%20benefit%20from%20aris ing%20opportunities/The-changing-aftermarket game.ashx
  • Nawzar, R. & Sheik, S. K. (2016). Improving forecasting for the aftermarket through big data: A case study at Volvo Group (M.Sc thesis). Department of Technology Management and Economics, Chalmers University of Technology, Gothenburg, Sweden. Retrieved from https://hdl.handle.net/ 20.500.12380/238852
  • Ozcift, B. (2018). Fuzzy clustering model proposal for forecasting automotive spare part demands (Ph.D. Thesis). Kocaeli University The Pure and Applied Sciences Institute, Kocaeli.
  • Porras, E. & Dekker, R. (2008). An inventory control system for spare parts at a refinery: an empirical comparison of different re-order point methods. European Journal of Operational Research, 184, 101– 132. Doi: https://doi.org/10.1016/ j.ejor.2006.11.008
  • Regon, J. R. & Mesquita, M. A. (2014). Demand forecasting and inventory control: A simulation study on automotive spare parts. International Journal of Production Economics, 161, 1-16. Doi: https://doi.org/10.1016/j.ijpe.2014.11.009
  • Saravanan, A. M., Anbuudayasank, S. P., David, A. W. & Narassima, M. S. (2019). Forecasting techniques for sales of spare parts. International Journal of Recent Technology and Engineering (IJRTE),ISSN: 2277- 3878, 8(3). Retrieved from https://www.ijrte.org/download/volume-8-issue-3/
  • Schaffer, A. L., Dobbins, T. A., & Pearson, S. A. (2021). Interrupted time series analysis using autoregressive integrated moving average (ARIMA) models: a guide for evaluating large-scale health interventions. BMC medical research methodology, 21(1), 1-12. Doi : https://doi.org/10.1186/s12874- 021-01235-8
  • Suyunova, M. (2018). The use of demand forecasting techniques for the improvement of spare part management. Proceedings of the World Congress on Engineering Vol I, London, U.K.
  • TUIK, (2021). Gross domestic product at current prices by income approach (value, share, percentage change). Retrieved from https://data.tuik.gov.tr/ Kategori/GetKategori?p=ulusal-hesaplar-113&dil=1
  • Vargas, G.C.A. & Cortes E.M. (2017). Automobile spare parts forecasting: A comparative study of time series methods. Journal of Automotive and Mechanical Engineering, 14, 3898-3912. Doi: https://doi.org/10.15282/ijame.14.1.2017.7.0317
  • Webby, R. & O'Connor, M. (1996). Judgemental and statistical time series forecasting: a review of the literature. International Journal of Forecasting 12,91-118. Doi : https://doi.org/10.1016/0169- 2070(95)00644-3
  • Winters, P. (1960). Forecasting Sales by Exponentially Weighted Moving Averages. Management Science, 6(3), 324-342. Doi : https://doi.org/10.1287/ mnsc.6.3.324
APA T A, Sennaroglu B (2021). APPLYING FORECASTING METHODS TO REDUCE THE COST OF SPARE PARTS INVENTORY IN A COMPANY. , 396 - 413.
Chicago T ALPER,Sennaroglu Bahar APPLYING FORECASTING METHODS TO REDUCE THE COST OF SPARE PARTS INVENTORY IN A COMPANY. (2021): 396 - 413.
MLA T ALPER,Sennaroglu Bahar APPLYING FORECASTING METHODS TO REDUCE THE COST OF SPARE PARTS INVENTORY IN A COMPANY. , 2021, ss.396 - 413.
AMA T A,Sennaroglu B APPLYING FORECASTING METHODS TO REDUCE THE COST OF SPARE PARTS INVENTORY IN A COMPANY. . 2021; 396 - 413.
Vancouver T A,Sennaroglu B APPLYING FORECASTING METHODS TO REDUCE THE COST OF SPARE PARTS INVENTORY IN A COMPANY. . 2021; 396 - 413.
IEEE T A,Sennaroglu B "APPLYING FORECASTING METHODS TO REDUCE THE COST OF SPARE PARTS INVENTORY IN A COMPANY." , ss.396 - 413, 2021.
ISNAD T, ALPER - Sennaroglu, Bahar. "APPLYING FORECASTING METHODS TO REDUCE THE COST OF SPARE PARTS INVENTORY IN A COMPANY". (2021), 396-413.
APA T A, Sennaroglu B (2021). APPLYING FORECASTING METHODS TO REDUCE THE COST OF SPARE PARTS INVENTORY IN A COMPANY. Endüstri Mühendisliği, 32(3), 396 - 413.
Chicago T ALPER,Sennaroglu Bahar APPLYING FORECASTING METHODS TO REDUCE THE COST OF SPARE PARTS INVENTORY IN A COMPANY. Endüstri Mühendisliği 32, no.3 (2021): 396 - 413.
MLA T ALPER,Sennaroglu Bahar APPLYING FORECASTING METHODS TO REDUCE THE COST OF SPARE PARTS INVENTORY IN A COMPANY. Endüstri Mühendisliği, vol.32, no.3, 2021, ss.396 - 413.
AMA T A,Sennaroglu B APPLYING FORECASTING METHODS TO REDUCE THE COST OF SPARE PARTS INVENTORY IN A COMPANY. Endüstri Mühendisliği. 2021; 32(3): 396 - 413.
Vancouver T A,Sennaroglu B APPLYING FORECASTING METHODS TO REDUCE THE COST OF SPARE PARTS INVENTORY IN A COMPANY. Endüstri Mühendisliği. 2021; 32(3): 396 - 413.
IEEE T A,Sennaroglu B "APPLYING FORECASTING METHODS TO REDUCE THE COST OF SPARE PARTS INVENTORY IN A COMPANY." Endüstri Mühendisliği, 32, ss.396 - 413, 2021.
ISNAD T, ALPER - Sennaroglu, Bahar. "APPLYING FORECASTING METHODS TO REDUCE THE COST OF SPARE PARTS INVENTORY IN A COMPANY". Endüstri Mühendisliği 32/3 (2021), 396-413.