Abstract
Due to the main peculiarities of spare parts, i.e. intermittent demands, long procurement lead times and high downtime costs when the parts are not available on time, it is often difficult to find the optimal inventory level. Recently, Additive Manufacturing (AM) has emerged as a promising technique to improve spare parts inventory management thanks to a ‘print on demand’ approach.So far, however, the impact of AM on spare parts inventory management has been little considered, and it is not yet clear when the use of AM for spare parts inventory management would provide benefits over Conventional Manufacturing (CM) techniques.With this paper we thus aim to contribute to the field of AM spare parts inventory management by developing decision trees that can be of support to managers and practitioners.To this aim, we considered a Poisson-based inventory management system and we carried out a parametrical analysis considering different part sizes and complexity, backorder costs and part consumption. Moreover, we evaluated scenarios where the order-up-to level is limited to resemble applications with a limited storage capacity.For the first time, the analysis was not limited to just one AM and one CM technique, but several AM and CM techniques were considered, also combined with different post-process treatments, for a total of nine different sourcing alternatives. In addition, the economic and technical performance of the different sourcing options were obtained thanks to an interdisciplinary approach, where experts from production economics and material science were brought together.
Highlights
Spare parts management is central for maintaining a high availability of production systems and is crucial when considering both economic and technical aspects
Our paper proposes a periodic review inventory management system for spare parts to establish the most economically profitable option among Conven tional Manufacturing (CM) and additive manufacturing (AM) technologies when coupled with post-process treatments
The mechanical properties are expressed in terms of mean time to failure (MTTF), which is provided by accelerated tests, representing nowadays the only viable alternative to testing parts at their usage conditions in order to achieve the said reliability data for parts produced via AM
Summary
Spare parts management is central for maintaining a high availability of production systems and is crucial when considering both economic and technical aspects. The scarcity of real data on their failures under different operating conditions, which is a consequence of continuous developments in terms of the range of combinations of AM technologies and post-process treatments, cannot guarantee that AM parts will withstand complex loading scenarios; this has hindered the development of failure criteria useful to predict failures (Peron et al 2017, 2018a, 2018b; Chebat et al, 2018), leaving accelerated tests as the only viable alternative for estimating the mechanical properties of AM options (Razavi 2019). To accurately understand when a transition to AM is economically profitable, we first need to investigate how the changes in: (i) spare part application features (complexity and size of the part, backorder cost and consumption) and (ii) AM/CM features (mechanical properties, production costs and times) affect the selection of the manufacturing option (defined as the combination of CM or AM tech nology and post-process treatments).
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