Endüstri Mühendisliği (İngilizce) Bölümü Koleksiyonu

Permanent URI for this collection

https://dspace.mudanya.edu.tr/handle/20.500.14362/77
Bu bölüme ait yayınları içerir

Browse

Browsing Endüstri Mühendisliği (İngilizce) Bölümü Koleksiyonu by Publisher "Sage"

Now showing 1 - 2 of 2
  • No Thumbnail Available
    Publication
    Mathematical model to upcycle end-of-roll leftover fabrics in apparel manufacturing
    (Sage, 2024-06) İşeri, Ali; Kızılaslan, Recep; 135066
    This study addresses the problem of end-of-roll leftover fabrics originating after the production of baby/child apparel. The ineffective management of these leftovers results in excess inventory, occupies storage space, and imposes economic and environmental loads. To address this challenge, a novel mathematical modeling approach is proposed. The model maximizes the upcycling of leftovers by incorporating these into the manufacturing of garments while adhering to marketing, production, and ordering constraints. This model also introduces the feasibility of ordering new fabrics with a penalty, as defined by the decision makers, to increase utilization. The model was tested using actual end-of-roll leftover data. The upcycling utilization of leftovers was calculated to be between 57% and 87%. Notably, at an upcycling rate of 58%, 96% of the utilized fabrics were sourced from leftovers. The case study results validate the model efficacy and provide insights into leftover-fabric management.
  • No Thumbnail Available
    Item
    Testing the Forecasting Power of Statistical Models for Intercity Rail Passenger Flows in Turkey
    (Sage, 2024-11) Ekici, Üsame; Tüydeş Yaman, Hediye; Şendil, Nuri
    While going through a major rail transformation, it is important to develop reliable estimation models for rail passenger flows (RPFs) in Turkey. There are two main approaches in RPF estimation, regressions and autoregressive integrated moving-average (ARIMA) models, both of which were in this study developed using the daily RPF data for the period 2011–2015. The ARIMA models (with some variations) were used to forecast first the daily flows in 2016, during which travel restrictions for summer resulted in reduced volumes, successfully captured in the updated ARIMA model. The regression models predicted the expected demand during the restrictions, enabling evaluation of the impact of restrictions, which also showed the models’ power over the longer term. The forecasts were extended to 2017, 2018, and 2019 data. The regression results produced more reliable forecasts over the long term, whereas more accurate predictions were obtained by ARIMA-Sliding (FA-Sld) for short-term planning purposes.