Logistics management is a critical component in supply chain management (SCM), in which
one of the goals is to improve inventory management (Ripanti and Tjahjono, 2019). Inventory
management is particularly important since it impacts logistical operations (Konur et al.,
2017), mainly in the highly competitive environment faced by the mining companies. Beyond
that, the mineral sector is of great importance to the emerging Brazilian economy. In 2018, the
estimated production value in this sector was US$ 34 billion which accounted for 13.0% of
Brazil’s exports, particularly iron ore, which accounted for 62% of the sector’s exports
besides provided 2 million direct and indirect jobs in this sector (IBRAM, 2018).
Regarding the costs of industrial plants, Hu et al. (2015) state that operational and
maintenance costs account for more than 60% of the overall costs, while the spare parts
related costs alone represent about 25–30%. In Brazil, a research conducted by ABRAMAN
(2013) points out that the maintenance costs of Brazilian companies were 4.69% of the
country’s GDP in 2013–21.96% of this value was spent in materials used for maintenance
while the financial value of the inventories represented 13.41% of total maintenance costs.
This clearly indicates that better operations management of spare parts ensures plant
availability at an adequate cost.
The ability of inventory management is critical to maintaining competitiveness in the
SCM (Tatham et al., 2017). Inventory of spare parts allows for greater availability of
production equipment (Teixeira et al., 2018) while balancing spending with the stock of spare
parts and level of service to internal customers. In many organisations, spare parts inventory
costs are extremely high because several items are strategic for operation and a stock
shortage can directly affect production (Conceica
˛oet al., 2015;Zhang and Zeng, 2017). Owing
to this, many large companies keep thousands of spare parts in stock (Kennedy et al., 2002).
Hence, the decision of which parts to stock in each location and in what quantities are as
important as the management of these materials (Driessen et al., 2015).
One of the ways to deal with spare parts management is to group them into specific
categories, making it possible to establish specific policies for each group (Roda et al., 2014;
Hu et al., 2017). There are several methodologies for inventory classification in the literature
(see, for example, Botter and Fortuin, 2000;Suryadi, 2003;Braglia et al., 2004;Bosnjakovic,
2010;Roda et al., 2014;Stoll et al., 2015;Hu et al., 2017); most of them focus on the classification
of existing stocks and not on the initial provisioning when new equipment is introduced.
Despite this, the most common spare parts classification approach is the traditional ABC
method (Bacchetti and Saccani, 2012;Stoll et al., 2015), making it still necessary to develop
improved methods for spare parts management.
Regarding the mineral industry, specifically, Roda et al. (2014) present an extensive survey
and two case studies in spare parts management in the copper mining sector of Chile. They
found that 70% of the companies had implemented classification approaches and 31% of
these companies had adopted a quantitative ABC analysis based on a single criterion.
According to Hu et al. (2018), there are two main options to meet the maintenance demand
in the initial provisioning: wait until either the demand occurs or storage initial spare parts. In
the initial provisioning, time series forecasting methods cannot be used due to the lack of an
adequate length of demand history precludes the use of extrapolative time series methods
(Boylan and Syntetos, 2008). The forecast based on explanatory or judgment variables is used
in the initial phase and is based on qualitative information (Boylan and Syntetos, 2008;Hu
et al., 2018). It is also used to adjust the forecasting results when qualitative information is
available and is not considered by the quantitative model (Hu et al., 2018). However, acting
only in inventory management maybe not enough since the provisioning may be performed
After initial provisioning and classification of spare parts, the supply department is
responsible to meet maintenance needs based on consumption data. Hu et al. (2018) point out