334
Views
8
CrossRef citations to date
0
Altmetric
Articles

Production-inventory analysis of single-station parallel machine make-to-stock/make-to-order system with random demands and lead times

, , &
Pages 33-44 | Received 06 Oct 2014, Accepted 24 Oct 2015, Published online: 02 Feb 2016
 

Abstract

Hybrid Make-To-Stock (MTS)/ Make-To-Order (MTO) production systems have captivated the attention of academic and practical societies due to their high levels of flexibility and profits of stock-based systems. This paper addresses a single-station production system including two parallel machines with two production modes; one of machines is allowed to process MTO (specific) products, whilst both machines might process these products in the other mode. In the considered system, it is assumed that demands and lead times follow Poisson and exponential density functions, respectively. In this regard, a queueing model is developed upon which extensive numerical analyses are conducted with respect to the exclusive performance measures for MTS and MTO products. The defined measures comprise fill rate, average number of finished products, and average number of orders for MTS products, and average number of specific orders in the system, expected response time, and on-time delivery rate for MTO products. Additionally, sensitivity analyses are performed.

Jel Classification:

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 289.00 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.