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

The dynamics of aggregate planning

Dejonckheere, J., Disney, Stephen Michael, Lambrecht, M. and Towill, Denis Royston 2003. The dynamics of aggregate planning. Production Planning & Control 14 (6) , pp. 497-516. 10.1080/09537280310001621967

[img]
Preview
PDF - Accepted Post-Print Version
Download (362kB) | Preview

Abstract

Recent software developments in system modelling via transfer function analysis now enables a much broader understanding of the dynamics of aggregate planning to be gained. In particular it opens up the possibility of exploiting filter theory as a focal point during algorithm design. This is particularly attractive in view of the fact that we have established, via transfer function models, that there is commonality between HMMS and the order-up-to replenishment rules used extensively within both local and global supply chains. Filter theory allows us to relate these dynamics directly to present-day production planning strategy as observed in much industrial practice. It covers the spectrum of production strategies recently identified as preferred industrial practice. These strategies range from 'level scheduling' (i.e. lean production) right through to 'pure chase' (i.e. agile manufacture) with appropriate simple algorithmic control support via APIOBPCS software.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC)
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HD Industries. Land use. Labor
H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Uncontrolled Keywords: Aggregate planning; Holt; Modigliani; Muth and Simon (HMMS) algorithm; transfer functions; system dynamics; filter theory
Publisher: Taylor & Francis
ISSN: 0953-7287
Date of First Compliant Deposit: 30 March 2016
Last Modified: 04 Jun 2017 11:09
URI: http://orca.cf.ac.uk/id/eprint/39441

Citation Data

Cited 29 times in Google Scholar. View in Google Scholar

Cited 26 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics