6533b852fe1ef96bd12aabcb

RESEARCH PRODUCT

Shelf life-based inventory management policy for RF monitored warehouse

G. La ScaliaRosa Micale

subject

021103 operations research05 social sciences0211 other engineering and technologies02 engineering and technologyInventory management policy shelf life RF technologyInventory management policy; shelf life; RF technologyShelf lifeIndustrial and Manufacturing EngineeringManagement Information SystemsWarehouseInventory managementManagement of Technology and Innovation0502 economics and businessSettore ING-IND/17 - Impianti Industriali MeccaniciOperations managementBusinessElectrical and Electronic Engineering050203 business & management

description

Post-harvest losses of perishable products strongly depend on inefficiencies of the entire supply chain. In particular, these inefficiencies can be reduced by optimizing the warehouse management, taking into account the remaining shelf life of the product, and matching it to the requirements of the subsequent part of the handling chain. The replacement of First In First Out picking rule with Last Shelf Life First Out policy has been proved to improve the overall performance of the supply chain. The practicability of such approach is related to the possibility of monitoring the deterioration rate of the products and of predicting the residual shelf-life, that is mainly influenced by harvesting conditions. Shelf-life based inventory management policies are seldom employed, generally due to the difficulties in the assessment of the environmental conditions. Such problem can be overcome by means of an automatic system able to acquire the volatile organic compound emitted by the product and of a communication tool that allows sending the information to be processed. RF technologies can be efficiently employed to reach this purpose in order to establish a shelf-life based prediction model. The present paper reports the technical/economic analysis related to the employment of an RF warehouse management system in an agro-industrial supply chain based upon an experimental campaign performed in a real case study.

10.3233/rft-181794http://hdl.handle.net/10447/325148