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Joint effect of forecasting and lot-sizing method on cost minimization objective of a manufacturer: a case study

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Forecasting and lot-sizing problems are key for a variety of products manufactured in a plant of finite capacity. The plant manager needs to put special emphasis on the way of selecting the right forecasting methods with a higher level of accuracy and to conduct procurement planning based on specific lot-sizing methods and associated rolling horizon. The study is con-ducted using real case data form the Fibertex Personal Care, and has evalu-ated the joint influence of forecasting procedures such as ARIMA, exponen-tial smoothing methods; and deterministic lot-sizing methods such as the Wagner-Whitin method, modified Silver-Meal heuristic to draw insights on the effect of the appropriate method selection on minimization of operational cost. The objective is to explore their joint effect on the cost minimization goal. It is found that a proficient selection process has a considerable impact on performance. The proposed method can help a manager to save substantial operational costs.
Rocznik
Strony
21--36
Opis fizyczny
Bibliogr. 41 poz., fig., tab.
Twórcy
autor
  • Aalborg University, Department of Materials and Production, DK 9220, Aalborg East, Denmark
  • Aalborg University, Department of Materials and Production, DK 9220, Aalborg East, Denmark
autor
  • Aalborg University, Department of Materials and Production, DK 9220, Aalborg East, Denmark
  • Aalborg University, Department of Materials and Production, DK 9220, Aalborg East, Denmark
autor
  • Production Manager, Fibertex Personal Care Group, Aalborg, Denmark
  • Aalborg University, Department of Materials and Production, DK 9220, Aalborg East, Denmark
autor
  • Aalborg University, Department of Materials and Production, DK 9220, Aalborg East, Denmark
Bibliografia
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  • [27] Patalas-Maliszewska, J. (2012). Assessing the Impact of Erp Implementation in the small Enterprises. Foundations of management, 4(2), 51-62. https://doi.org/10.2478/fman-2013-0010
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  • [35] Syntetos, A. A., Boylan, J. E., & Disney, S. M. (2009). Forecasting for inventory planning: a 50-year review. Journal of the Operational Research Society, 60, 149–S160. https://doi.org/10.1057/jors.2008.173
  • [36] Syntetos, A. A., Nikolopoulos, K., & Boylan, J. E. (2010). Judging the judges through accuracy-implication metrics: The case of inventory forecasting. International Journal of Forecasting, 26(1), 134-143. https://doi.org/10.1016/j.ijforecast.2009.05.016
  • [37] Taneja, K., Ahmad, S., Ahmad, K., & Attri, S. D. (2016). Time series analysis of aerosol optical depth over New Delhi using Box–Jenkins ARIMA modeling approach. Atmospheric Pollution Research, 7(4), 585596. https://doi.org/10.1016/j.apr.2016.02.004
  • [38] Van Den Heuvel, W., & Wagelmans, A. P. (2005). A comparison of methods for lot-sizing in a rolling horizon environment. Operations Research Letters, 33(5), 486–496. https://doi.org/10.1016/j.orl.2004.10.001
  • [39] Wagner, H. M., & Whitin, T. M. (1958). Dynamic version of the economic lot size model. Management science, 5(1), 89-96. https://doi.org/10.1287/mnsc.5.1.89
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-fd2d0e96-a4aa-402a-8756-8b4daecd5abf
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