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Articles

A note on the demand distributions of spare parts

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Pages 6356-6358 | Received 13 Jun 2012, Accepted 16 Apr 2013, Published online: 14 Jun 2013

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Kamal Sanguri, Sabyasachi Patra, Konstantinos Nikolopoulos & Sushil Punia. (2023) Intermittent demand, inventory obsolescence, and temporal aggregation forecasts. International Journal of Production Research 0:0, pages 1-23.
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Xiong Li, Xiaodong Zhao & Wei Pu. (2020) Battle damage-oriented spare parts forecasting method based on wartime influencing factors analysis and ε-support vector regression. International Journal of Production Research 58:4, pages 1178-1198.
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Elia Balugani, Francesco Lolli, Rita Gamberini, Bianca Rimini & M. Z. Babai. (2019) A periodic inventory system of intermittent demand items with fixed lifetimes. International Journal of Production Research 57:22, pages 6993-7005.
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M. Hasni, M.S. Aguir, M.Z. Babai & Z. Jemai. (2019) Spare parts demand forecasting: a review on bootstrapping methods. International Journal of Production Research 57:15-16, pages 4791-4804.
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Ville Sillanpää & Juuso Liesiö. (2018) Forecasting replenishment orders in retail: value of modelling low and intermittent consumer demand with distributions. International Journal of Production Research 56:12, pages 4168-4185.
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Articles from other publishers (12)

Haytham Omar, Walid Klibi, M. Zied Babai & Yves Ducq. (2023) Basket data-driven approach for omnichannel demand forecasting. International Journal of Production Economics 257, pages 108748.
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Yuan Ye, Yonggang Lu, Powell Robinson & Arunachalam Narayanan. (2022) An empirical Bayes approach to incorporating demand intermittency and irregularity into inventory control. European Journal of Operational Research 303:1, pages 255-272.
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John E. Boylan & M. Zied Babai. (2022) Estimating the cumulative distribution function of lead-time demand using bootstrapping with and without replacement. International Journal of Production Economics 252, pages 108586.
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Kamal Sanguri & Kampan Mukherjee. (2021) Forecasting of intermittent demands under the risk of inventory obsolescence. Journal of Forecasting 40:6, pages 1054-1069.
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John Boylan & Aris Syntetos. 2021. Intermittent Demand Forecasting. Intermittent Demand Forecasting 347 364 .
Xinglu Xu, Mark D. Rodgers & Weihong (Grace) Guo. (2021) Hybrid simulation models for spare parts supply chain considering 3D printing capabilities. Journal of Manufacturing Systems 59, pages 272-282.
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M.Z. Babai, H. Chen, A.A. Syntetos & D. Lengu. (2021) A compound-Poisson Bayesian approach for spare parts inventory forecasting. International Journal of Production Economics 232, pages 107954.
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J. Jakob Heinen & Kai Hoberg. (2019) Assessing the potential of additive manufacturing for the provision of spare parts. Journal of Operations Management 65:8, pages 810-826.
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Laura Turrini & Joern Meissner. (2019) Spare parts inventory management: New evidence from distribution fitting. European Journal of Operational Research 273:1, pages 118-130.
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Qiwei Hu, John E. Boylan, Huijing Chen & Ashraf Labib. (2018) OR in spare parts management: A review. European Journal of Operational Research 266:2, pages 395-414.
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Sungil Kim & Heeyoung Kim. (2016) A new metric of absolute percentage error for intermittent demand forecasts. International Journal of Forecasting 32:3, pages 669-679.
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D. Lengu, A.A. Syntetos & M.Z. Babai. (2014) Spare parts management: Linking distributional assumptions to demand classification. European Journal of Operational Research 235:3, pages 624-635.
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