Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Towards responsive vehicle supply: a simulation-based investigation into automotive scheduling systems

Holweg, Matthias, Disney, Stephen Michael, Hines, Peter Arthur and Naim, Mohamed Mohamed 2005. Towards responsive vehicle supply: a simulation-based investigation into automotive scheduling systems. Journal of Operations Management 23 (5) , pp. 507-530. 10.1016/j.jom.2004.10.009

Full text not available from this repository.

Abstract

Vehicle supply has traditionally been based on forecast-driven production, and a large fraction of cars has been sold from stock—a practice which incurs considerable cost in terms of stock holding and sales incentives. Derived from successes in other industries, the benefits of responsive supply systems capable of providing customized vehicles in short lead-times have been pointed out. While the theoretical discussion of such ‘build-to-order’ (BTO) strategies is well advanced, the dynamic feasibility of implementing these concepts is far from understood. Using a simulation of a multi-tier supply chain-system, this paper investigates the impact of altering key aspects of the scheduling activities with the objective of determining the scope for potential improvements in responsiveness of the supply chain. The simulation results show that current vehicle supply systems are not capable of supporting BTO due to insufficient feedback between supply and demand, as well as due to the strong reliance on forecasting in the scheduling process. The paper concludes with a set of recommendations on how to improve current scheduling systems towards increasing the content of vehicles built to customer order.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC)
Uncontrolled Keywords: Build-to-order; Scheduling; Taguchi method; Systems modeling
ISSN: 0272-6963
Last Modified: 04 Jun 2017 01:48
URI: http://orca.cf.ac.uk/id/eprint/2775

Citation Data

Cited 89 times in Google Scholar. View in Google Scholar

Cited 59 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item