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.

Conventional or additive manufacturing for spare parts management: An extensive comparison for Poisson demand / Sgarbossa, Fabio; Peron, Mirco; Lolli, Francesco; Balugani, Elia. - In: INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS. - ISSN 0925-5273. - 233:(2021), pp. 1-16. [10.1016/j.ijpe.2020.107993]

Conventional or additive manufacturing for spare parts management: An extensive comparison for Poisson demand

Lolli, Francesco;Balugani, Elia
2021

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.
2021
233
1
16
Conventional or additive manufacturing for spare parts management: An extensive comparison for Poisson demand / Sgarbossa, Fabio; Peron, Mirco; Lolli, Francesco; Balugani, Elia. - In: INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS. - ISSN 0925-5273. - 233:(2021), pp. 1-16. [10.1016/j.ijpe.2020.107993]
Sgarbossa, Fabio; Peron, Mirco; Lolli, Francesco; Balugani, Elia
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1226206
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