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

Yıl 2019, Cilt: 29 Sayı: 2, 133 - 141, 30.06.2019

Cemal Aktürk , Sevinç Gülseçen

https://doi.org/10.32710/tekstilvekonfeksiyon.428328

Cited By: 1

Öz

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.

Anahtar Kelimeler

Nonwoven Textile, Order Ranking, Decision Support System, Moora, Delivery Date

Kaynakça

• 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 Customers”, International Journal Of Science And Technology, 2(1).
• 13. Demir, H. İ. and Erden, C., 2017, “Solving process planning and weighted scheduling with WNOPPT weighted due-date assignment problem using some pure and hybrid meta-heuristics”, Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 21(2), 210-222.
• 14. Samarghandi, H. and Behroozi, M., 2016, “An Enumeration Algorithm for the No-Wait Flow Shop Problem with Due Date Constraints”, IFAC-PapersOnLine, 49(12), 1803-1808.
• 15. Kuroda, M., 2016, “Integration of product design and manufacturing through real-time due-date estimation and scheduling systems”, Journal of Advanced Mechanical Design, Systems, and Manufacturing, 10(3).
• 16. Low, C., Li, R. K., & Wu, G. H., 2016, “Minimizing Total Earliness and Tardiness for Common Due Date Single-Machine Scheduling with an Unavailability Interval”, Mathematical Problems in Engineering, 2016, Article ID 6124734, 12 pages, doi:10.1155/2016/6124734
• 17. Li, S. S. and Chen, R. X., 2017, “Common due date assignment and cumulative deterioration scheduling on a single machine”, Engineering Optimization, 49(6), 976-989.
• 18. Nurainun, T., Fudholi, A., Hartati, M., Yendra, R., & Kusumanto, I., 2016, “A Multi Due Date Batch Scheduling Model on Dynamic Flow Shop to Minimize Total Production Cost”, Contemporary Engineering Sciences, 9(7), 315 – 324.
• 19. Zahedi, Z., Samadhi, T., Suprayogi, S., & Halim, A., 2016, “Integrated batch production and maintenance scheduling for multiple items processed on a deteriorating machine to minimize total production and maintenance costs with due date constraint”, International Journal of Industrial Engineering Computations, 7(2), 229-244.
• 20. Zhao, C., 2016, “Common due date assignment and single-machine scheduling with release times to minimize the weighted number of tardy jobs”, Japan Journal of Industrial and Applied Mathematics, 33(1), 239-249.
• 21. Lin, Y. K. and Huang, D. H., 2017, “Reliability analysis for a hybrid flow shop with due date consideration”, Reliability Engineering & System Safety.
• 22. Drwal, M., 2017, “Robust Scheduling To Minimize The Weighted Number Of Late Jobs With Interval Due-Date Uncertainty”, Arxiv Preprint Arxiv, 1708.03252.
• 23. Lödding, H. and Piontek, A., 2017, “The surprising effectiveness of earliest operation due-date sequencing”, Production Planning & Control, 28(5), 459-471.
• 24. Carr, S. and Duenyas, I., 2000, “Optimal admission control and sequencing in a make-to-stock/make-to-order production system”, Operations research, 48(5), 709-720.
• 25. Lewis, H. F., & Slotnick, S. A., 2002, “Multi-period job selection: planning work loads to maximize profit”, Computers & Operations Research, 29(8), 1081-1098.
• 26. Keskinocak, P., Ravi, R., & Tayur, S., 2001, “Scheduling and reliable lead-time quotation for orders with availability intervals and lead-time sensitive revenues”, Management Science, 47(2), 264-279.
• 27. Slotnick, S. A. and Morton, T. E., 2007, “Order acceptance with weighted tardiness”, Computers & Operations Research, 34(10), 3029-3042.
• 28. Deng, H., Wang, Q., Leong, G. K., & Sun, S. X., 2008, “The usage of opportunity cost to maximize performance in revenue management”, Decision Sciences, 39(4), 737-758.
• 29. Oğuz C., Salman, F. S., & Yalçın, Z. B., 2010, “Order acceptance and scheduling decisions in make-to-order systems”, International Journal of Production Economics, 125(1), 200-211.