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Open AccessArticle

An Economic Order Quantity Stochastic Dynamic Optimization Model in a Logistic 4.0 Environment

Department of Chemical, Materials and Production Engineering of the University of Naples “Federico II”, 80125 Naples, Italy
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Sustainability 2020, 12(10), 4075; https://doi.org/10.3390/su12104075
Received: 9 April 2020 / Revised: 9 May 2020 / Accepted: 11 May 2020 / Published: 15 May 2020
(This article belongs to the Special Issue Smart Production Operations Management and Industry 4.0)
This paper proposes a stock dynamic sizing optimization under the Logistic 4.0 environment. The safety stock is conceived to fill up the demand variability, providing continuous stock availability. Logistic 4.0 and the smart factory topics are considered. It focuses on vertical integration to implement flexible and reconfigurable smart production systems using the information system integration in order to optimize material flow in a 4.0 full-service approach. The proposed methodology aims to reduce the occurring stock-out events through a link among the wear-out items rate and the downstream logistic demand. The failure rate items trend is obtained through life-cycle state detection by a curve fitting technique. Therefore, the optimal safety stock size is calculated and then validated by an auto-tuning iterative modified algorithm. In this study, the reorder time has been optimized. The case study refers to the material management of a very high-speed train. View Full-Text
Keywords: Full-Service; Logistic 4.0; Smart Factory; Maintenance; safety-stock; EOQ; Simulation-based optimization Full-Service; Logistic 4.0; Smart Factory; Maintenance; safety-stock; EOQ; Simulation-based optimization
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Di Nardo, M.; Clericuzio, M.; Murino, T.; Sepe, C. An Economic Order Quantity Stochastic Dynamic Optimization Model in a Logistic 4.0 Environment. Sustainability 2020, 12, 4075.

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