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EN
Until recently logistics systems supported only processes carried out in classical material flow from producer to final user. Recently it has been a remarkable growth of interest in optimizing logistics processes that supports recapturing value from used goods. The process of planning, implementing, and controlling the efficient, cost effective flow of raw materials, in-process inventory, finished goods and related information from the point of consumption to the point of origin for the purpose of recapturing value or proper disposal is called reverse logistics. Reuse of product parts can bring direct advantages to the company because it reduces costs associated with acquiring new components. Main goal of this paper is to create the reverse logistics inventory model that uses the reliability theory to describe re-usability of product parts with assumption that recovered components are used in a production process but they aren’t as good as new ones. The model allows to estimate the potential profits of the reusing policy in production and inven-tory management. It gives the base to optimize some of the process parameters: the threshold work time of returns, the warranty period for products containing reused elements or new components order size.
EN
Reverse logistics understood as the process of managing reverse flow of materials, in-process inventory, finished goods and related information has become one of the logisticians’ key areas of interest. Nowadays a growing number of companies realize the meaning of that field of logistics. Reuse of products can bring direct advantages because company uses recovered components instead of expensive new ones. On the base of literature overview the aims of the paper were established. It proposes the model that uses the reliability theory to optimize recovery policy parameters. The criterion of the policy parameters optimization is the total cost of the production, recovery and services during warranty period. Presented model is a development of existing approaches because it widely analyses the aspect of returns condition in the recovery policy optimization.
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