Title: An integrated approach for demand forecasting and inventory management optimisation of spare parts

Authors: Mattia Armenzoni; Roberto Montanari; Giuseppe Vignali; Eleonora Bottani; Gino Ferretti; Federico Solari; Marta Rinaldi

Addresses: Interdepartmental Centre SITEIA.PARMA, c/o Department of Industrial Engineering, University of Parma, Parco Area Delle Scienze, 181 – 43124 Parma, Italy ' Department of Industrial Engineering, University of Parma, Parco Area Delle Scienze, 181 – 43124 Parma, Italy ' Department of Industrial Engineering, University of Parma, Parco Area Delle Scienze, 181 – 43124 Parma, Italy ' Department of Industrial Engineering, University of Parma, Parco Area Delle Scienze, 181 – 43124 Parma, Italy ' Department of Industrial Engineering, University of Parma, Parco Area Delle Scienze, 181 – 43124 Parma, Italy ' Department of Industrial Engineering, University of Parma, Parco Area Delle Scienze, 181 – 43124 Parma, Italy ' Interdepartmental Centre CIPACK, c/o Department of Industrial Engineering, University of Parma, Parco Area Delle Scienze, 181 – 43124 Parma, Italy

Abstract: In this paper, we develop and test an advanced model, based on discrete-event simulation, whose purpose is to forecast the demand of spare parts during the whole lifetime of a complex product, such as, for instance, an industrial machine. To run the model, the relevant data of the product manufactured by a targeted company should be collected. With those data, the model provides an estimate of the optimal level of spare parts inventory the company should keep available. The data provided by the model are subsequently applied to a case example, referring to a hypothesised company, manufacturing industrial plants. The application is carried out considering two scenarios, i.e., a 'traditional' and an 'advanced' approach for demand forecasting, this latter reflecting the circumstance where the company makes use of the proposed forecasting method. The comparison of the outcomes obtained in the two scenarios highlights the efficiency and resolution capacity of the model developed.

Keywords: spare parts inventory; discrete event simulation; DES; demand forecasting; stock management; inventory optimisation; inventory management; inventory modelling; complex products.

DOI: 10.1504/IJSPM.2015.071375

International Journal of Simulation and Process Modelling, 2015 Vol.10 No.3, pp.233 - 240

Received: 29 Jan 2014
Accepted: 03 Jun 2014
Published online: 22 Aug 2015 *

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