Adapting Modern Portfolio Theory For Prioritising Asset Care Planning In Industry

Authors

  • Andrew Francis van den Honert Stellenbosch University
  • Pieter-Jan Vlok Stellenbosch University

DOI:

https://doi.org/10.7166/25-1-673

Keywords:

optimisation, Modern portfolio theory, Physical asset management, asset care planning, productivity, risk, maintenance

Abstract

Productivity improvement within any organisation can lead to increased turnover. This study focuses on developing a maintenance productivity improvement model that is based upon an established financial investment portfolio technique known as the Modern Portfolio Theory (MPT). The model can be used as a tool to minimise and diversify the long term risk associated with variances or fluctuations in the increase in productivity in multiple maintenance service centres. This is achieved by optimising the most efficient way of splitting resources, such as time and money, between these multiple service centres, resulting in increased productivity and a more constant maintenance work load. This model is verified through the use of an efficient frontier, resulting in a graphical method to determine the link between the expected increase in productivity and the standard deviation of the increase in productivity. Ultimately this model can be adapted for use in many sectors within an organisation, over and above the application in maintenance prioritisation. This study concludes that the model offers a simple tool to aid decision-making among various combinations of assets within a maintenance context; and this model, adapted from MPT, was successfully validated with the use of an efficient frontier.

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Author Biographies

Andrew Francis van den Honert, Stellenbosch University

Industrial Engineering department, Masters student

Pieter-Jan Vlok, Stellenbosch University

Industrial Engineering department, Proffessor

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Published

2014-05-13

How to Cite

van den Honert, A. F., & Vlok, P.-J. (2014). Adapting Modern Portfolio Theory For Prioritising Asset Care Planning In Industry. The South African Journal of Industrial Engineering, 25(1), 107–116. https://doi.org/10.7166/25-1-673

Issue

Section

General Articles