KaydedilenlerDerginizi ekleyin

Dergiler / Tekstil ve Konfeksiyon / 2019 / Cilt: 29 - Sayı: 2

DETERMINING ORDER DELIVERY DATE BY REVENUE APPROACH: A CASE STUDY WITH NONWOVEN TEXTILE MANUFACTURERS IN TRC1 REGION

Cemal AKTÜRK
Sevinç GÜLSEÇEN
Sayfa
133–141
Yayın Tarihi
2019-06-30
DOI
—
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The present decision support system as a product that can be used by decision makers gives a different point of view to delivery date and order ranking literature which is generally composed of theoretical studies.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Nonwoven textile materials are used as intermediate raw materials in various sectors such as cleaning, healthcare and automotive.
📊
Temel Bulgular & Veri:In this software application developed, orders are sorted in 7 different ways based on Moora and linear function.
💡
Sonuç & Katkı:The present decision support system as a product that can be used by decision makers gives a different point of view to delivery date and order ranking literature which is generally composed of theoretical studies.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Nonwoven Textile · Order Ranking · Decision Support System

Abstract

Nonwoven textile materials are used as intermediate raw materials in various sectors such as cleaning, healthcare and automotive. These products are produced according to the demand because they are requested in different compositions, colors and weights. It is necessary to use the capacity efficiently in the nonwoven textile technology which has high investment costs and high production capacity in order to attain company objectives. In this study, a decision support system for nonwoven textile firms was developed so that they obtain more order revenue fromcustomer orders. In this software application developed, orders are sorted in 7 different ways based on Moora and linear function. The total order revenues to be obtained from each ranking and the delivery dates of sorted jobsare calculated and presented to the user for decision support purposes. 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 running scenarios, Moora and linear function methods have introduced more total order revenues than FCFS and EDD methods. The present decision support system as a product that can be used by decision makers gives a different point of view to delivery date and order ranking literature which is generally composed of theoretical studies.

🔖

Bu Makaleye Atıf Yap

AKTÜRK, C., GÜLSEÇEN, S. (2019). DETERMINING ORDER DELIVERY DATE BY REVENUE APPROACH: A CASE STUDY WITH NONWOVEN TEXTILE MANUFACTURERS IN TRC1 REGION. Tekstil ve Konfeksiyon, Cilt: 29 - Sayı: 2, 133–141. https://ajindex.com/articles/45982

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (12)

  1. Guhlich, H., Fleischmann, M., & Stolletz, R., 2015, “Revenue management approach to due date quoting and scheduling in an assemble-to-order production system”, OR Spectrum, 37(4), 951-982
  2. Ilić, A., 2015, “On the variable common due date, minimal tardy jobs bicriteria two-machine flow shop problem with ordered machines”, Theoretical Computer Science, 582, 70-73
  3. Jagan, D., Senthilvel, A. N., Prabhakar, R., & Maheswari, S. U., 2015, “Analysis for Maximal Optimized Penalty for the Scheduling of Jobs with Specific Due Date on a Single Machine with Idle Time”, Procedia Computer Science, 47, 247-254
  4. Demir, H. I., Uygun, O., Cil, I., Ipek, M., & Sari, M., 2015, “Process Planning and Scheduling with SLK Due-Date Assignment where Earliness, Tardiness and Due-Dates are Punished”, Journal of Industrial and Intelligent Information, 3(3)
  5. Low, C., Li, R. K., Wu, G. H., & Huang, C. L., 2015, “Minimizing The Sum Of Absolute Deviations Under A Common Due Date For A Single-Machine Scheduling Problem With Availability Constraints”, Journal Of Industrial And Production Engineering, 32(3), 204-217
  6. Canıyılmaz, E., Benli, B., & Ilkay, M. S., 2015, “An Artificial Bee Colony Algorithm Approach For Unrelated Parallel Machine Scheduling With Processing Set Restrictions, Job Sequence-Dependent Setup Times, And Due Date”, The International Journal Of Advanced Manufacturing Technology, 77(9-12), 2105-2115
  7. Çakar, T., Köker, R., & Canay, O., 2015, “A New Neuro-Dominance Rule For Single-Machine Tardiness Problem With Double Due Date”, Neural Computing And Applications, 26(6), 1439-1450
  8. Baker, K. R. and Trietsch, D., 2015, “Trading off due-date tightness and job tardiness in a basic scheduling model”, Journal of Scheduling, 18(3), 305-309
  9. Assarzadegan, P. and Rasti-Barzoki, M., 2016, “Minimizing sum of the due date assignment costs, maximum tardiness and distribution costs in a supply chain scheduling problem”, Applied Soft Computing, 47, 343-356
  10. Shabtay, D., Steiner, G., & Zhang, R., 2016, “Optimal Coordination Of Resource Allocation, Due Date Assignment And Scheduling Decisions”, Omega, 65, 41-54
  11. Schäfer, R., Chankov, S., & Bendul, J., 2016, “What is Really “On-Time”? A Comparison of Due Date Performance Indicators in Production”, Procedia CIRP, 52, 124-129
  12. Demir, H. I., Cil, I., Uygun, O., Simsir, F., & Kokcam, A. H., 2016, “Process Planning And Weighted Scheduling With Wnoppt Weighted Due-Date Assignment Using Hybrid Search For Weighted