Due date quotation in make-to-order systems with lead time sensitive customers

Aydın, Ayhan (2006) Due date quotation in make-to-order systems with lead time sensitive customers. [Thesis]

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Abstract

Due date management is a central issue when production is triggered by customer orders. In a wide range of industries, especially if either craftsmanship is necessary or small scale project management is employed, quoting short but still attainable due dates and sustaining the highest return for the company in the long run provides an important competitive edge. In this study, we consider a single stage make-toorder manufacturing system, where customers are quoted hundred percent reliable due dates, immediately after they arrive. Lead time sensitive customers are offered price discounts in return for due dates further out. Still, quoted lead times cannot be arbitrarily long, and strict upper bounds are imposed on these depending on the type of the customer order. The scheduler does not have any information about the future arrivals in terms of their type and timing, and s/he needs to make decisions in an online setting without prior information about the arrival process or the attributes. In this thesis, a framework which evaluates the potential decisions for each order in conjunction with the current temporary production schedule is introduced. Using this framework, a group of algorithms is developed which aim to maximize the long term profit per unit time by estimating the future implications of accepting an order with a certain due date. Computational results demonstrate that under mild congestion and relatively frequent arrival of high-margin orders, this group of algorithms outperform first-come-first-served (FCFS) order selection and sequencing approach which is typical in many contexts.
Item Type: Thesis
Uncontrolled Keywords: Scheduling. -- Due date quotation. -- Make-to-order. -- Simulation. -- Online algorithms
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Engineering and Natural Sciences
Faculty of Engineering and Natural Sciences > Academic programs > Manufacturing Systems Eng.
Depositing User: IC-Cataloging
Date Deposited: 15 Apr 2008 09:24
Last Modified: 26 Apr 2022 09:47
URI: https://research.sabanciuniv.edu/id/eprint/8365

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