Determining Order Delivery Date by Revenue Approach: A Case Study with Non-Woven Textile Manufacturers in TRC1 Region


AKTÜRK C., Gulsecen S.

TEKSTIL VE KONFEKSIYON, cilt.29, sa.2, ss.133-141, 2019 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 29 Sayı: 2
  • Basım Tarihi: 2019
  • Doi Numarası: 10.32710/tekstilvekonfeksiyon.428328
  • Dergi Adı: TEKSTIL VE KONFEKSIYON
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.133-141
  • İstanbul Üniversitesi Adresli: Evet

Özet

Non-woven textile materials are used as intermediate raw materials in various sectors such as cleaning, healthcare and automotive. These products are produced based on demand because they are requested in different compositions, colors, and weights. To ensure that the company achieves its objectives, it is necessary to use the capacity efficiently in the non-woven textile technology since it has high investment costs and high production capacity. In this study, a decision support system has been developed for non-woven textile firms so that they can obtain more order revenue. This software application was developed to sort the orders in 7 different ways based on the Moora and linear functions. The total order revenues to be obtained from each ranking and the delivery dates of sorted jobs are calculated and presented to the user to help him/her in the decision-making process. In addition, this software can also record the operator's planned maintenance data. In the present study, the decision support system was run with 27 different production scenarios. In the scenarios, the Moora method and linear function methods put forward more total order revenues than FCFS (First Come First Served) and EDD (Earliest Due Date) methods. As a product that can be used by decision-makers, the present decision support system provides a different point of view to the literature -which generally consists of theoretical studies-on delivery date and order ranking.