598
Views
11
CrossRef citations to date
0
Altmetric
Original Articles

Use of advance demand information in multi-stage production-inventory systems with multiple demand classes

&
Pages 57-68 | Received 16 Mar 2011, Accepted 02 Dec 2011, Published online: 16 Jan 2012
 

Abstract

This paper considers three-stage production-inventory systems serving two customer classes, where only one class provides advance demand information and early order fulfilment is acceptable. We propose a new approach for production replenishment and order fulfilment in such systems that uses advance demand information for performance improvement. The approach combines the benefits of early fulfilment and Kanban-based pull systems. Simulation is used to establish the performance of the resulting policy vs. two existing policies, for a variety of production scenarios and cost structures. A lower bound on total cost is also established using a simulation-based procedure. In general, early fulfilment with one-for-one replenishment is shown to provide greater benefit than making items to order. Neither of the existing policies, however, was found to use advance demand information as effectively as the proposed approach, which outperformed the existing policies in every case considered. Additionally, the proposed policy has the advantage of both retaining its benefit at high levels of system utilisation and increasing benefit up to the maximum level of advance demand information provided.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 973.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.