A Neural Network Model on the Forecasting of Inventory Risk Management of Spare Parts

Weipeng Wang ()
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Weipeng Wang: Weifang University

A chapter in 2012 International Conference on Information Technology and Management Science(ICITMS 2012) Proceedings, 2013, pp 295-302 from Springer

Abstract: Abstract This paper proposes a neural network-based classification approach to inventory risk level of spare parts. Firstly a fuzzy evaluation of spare parts is made in terms of their availability of suppliers, importance, predictability of failure, specificity and lead time. Then a multilayer feed forward neural network model is established. The Back Propagation (BP) algorithm for training a neural network is used to decide the weights to connections in the model. Choosing a sample of historical data of 100 spare parts and undertaking a BP training stimulation, the model is used to predict the inventory risk levels of 60 spare parts for a well-logging service firm. The forecasting reliability reaches 84%.

Keywords: Management of spare parts; Neural network; Back propagation algorithm (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-34910-2_34

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DOI: 10.1007/978-3-642-34910-2_34

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