Exploring incomplete information in maintenance materials inventory optimization
| DOI | https://doi.org/10.1108/IMDS-01-2013-0025 |
| Pages | 144-158 |
| Published date | 28 January 2014 |
| Date | 28 January 2014 |
| Author | Antti Puurunen,Jukka Majava,Pekka Kess |
| Subject Matter | Information & knowledge management,Information systems,Data management systems |
Exploring incomplete information
in maintenance materials
inventory optimization
Antti Puurunen, Jukka Majava and Pekka Kess
Industrial Engineering and Management, University of Oulu,
Oulu, Finland
Abstract
Purpose – Ensuring the sufficient service level is essential for critical materials in industrial
maintenance. This study aims to evaluate the use of statistically imperfect data in a stochastic
simulation-based inventory optimization where items’ failure characteristics are derived from
historical consumption data, which represents a real-life situation in the implementation of such an
optimization model.
Design/methodology/approach – The risks of undesired shortages were evaluated through a
service-level sensitivity analysis. The service levels were simulated within the error of margin of the
key input variables by using StockOptim optimization software and real data from a Finnish steel mill.
A random sample of 100 inventory items was selected.
Findings – Service-level sensitivity is item specific, but, for many items, statistical imprecision in the
input data causes significant uncertainty in the service level. On the other hand, some items seem to be
more resistant to variations in the input data than others.
Research limitations/implications – The case approach, with one simulation model, limits the
generalization of the results. The possibility that the simulation model is not totally realistic exists, due
to the model’s normality assumptions.
Practical implications – Margin of error in input data estimation causes a significant risk of not
achieving the required service level. It is proposed that managers work to improve the preciseness of
the data, while the sensitivity analysis against statistical uncertainty, and a correction mechanism if
necessary, should be integrated into optimization models.
Originality/value – The output limitations in the optimization, i.e. service level, are typically stated
precisely, but the capabilities of the input data have not been addressed adequately. This study
provides valuable insights into ensuring the availability of critical materials.
Keywords Inventory optimization, Maintenancematerials, Service-level sensitivity, Spare parts,
StockOptim
Paper type Research paper
1. Introduction
Intensifying competition and modern management philosophies drive companies to
find ways to reduce working capital tied to business operations, including maintenanc e
materials inventories (Eroglu and Hofer, 2010). The maintenance fun ction is
developing rapidly, and the progress of maintenance concepts over the years can
described as follows (Ahuja, 2009):
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/0263-5577.htm
The authors are grateful to Mr Joel Turpela as well as to the personnel of the case company for
the excellent cooperation.
Received 14 January 2013
Revised 11 March 2013
14 August 2013
3 September 2013
Accepted 5 September 2013
Industrial Management & Data
Systems
Vol. 114 No. 1, 2014
pp. 144-158
qEmerald Group Publishing Limited
0263-5577
DOI 10.1108/IMDS-01-2013-0025
IMDS
114,1
144
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