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

Authors

  • Winston LeMay Sweatman Massey University
  • James McGree Queensland University of Technology
  • Corrie Jacobien Carstens RMIT University
  • Kylie J. Foster University of South Australia
  • Shen Liu Queensland University of Technology
  • Nicholas Tierney Queensland University of Technology
  • Eloise Tredenick Queensland University of Technology
  • Ayham Zaitouny University of Western Australia

DOI:

https://doi.org/10.21914/anziamj.v57i0.10225

Keywords:

mathematics-in-industry, networks, CARTS

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. References
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Author Biography

Winston LeMay Sweatman, Massey University

Associate Professor , Institute of Natural and Mathematical Sciences, Massey University

Published

2016-08-28

Issue

Section

Proceedings of the Mathematics in Industry Study Group