Visualisation and statistical modelling techniques for the management of inventory stock levels

Winston L. Sweatman, James McGree, C. Jacobien Carstens, Kylie J. Foster, Shen Liu, Nicholas Tierney, Eloise Tredenick, Ayham Zaitouny

Research output: Chapter in Book/Report/Conference proceedingConference PaperOtherpeer-review

Abstract

This paper describes the investigations conducted in a Mathematics-in-Industry Study Group project from the Australian meeting at Queensland University of Technology in 2015. This concerned the management of stock levels of raw materials used to construct aortic stents. The approaches used included network visualisation, classification and regression trees, and time series modelling. This work will be of general interest to those who are managing stock levels in a highly volatile context. The methods applied show that there is potential value in taking a statistical approach to understand and make decisions within such volatility. The work provides a basis for developing more advanced statistical approaches for specific inventory problems.
Original languageEnglish
Title of host publicationProceedings of the 2015 Mathematics in Industry Study Group
EditorsTroy Farrell, Tony Roberts
Place of PublicationCambridge UK
PublisherCambridge University Press
PagesM130-M162
Number of pages33
DOIs
Publication statusPublished - 2016
Externally publishedYes

Publication series

NameANZIAM Journal
PublisherCambridge University Press
Volume57
ISSN (Print)1446-1811
ISSN (Electronic)1446-8735

Cite this

Sweatman, W. L., McGree, J., Carstens, C. J., Foster, K. J., Liu, S., Tierney, N., Tredenick, E., & Zaitouny, A. (2016). Visualisation and statistical modelling techniques for the management of inventory stock levels. In T. Farrell, & T. Roberts (Eds.), Proceedings of the 2015 Mathematics in Industry Study Group (pp. M130-M162). (ANZIAM Journal; Vol. 57). Cambridge University Press. https://doi.org/10.21914/anziamj.v57i0.10225