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• W2022673873 abstract "The introduction of intelligent machines and autonomous vehicles to agricultural operations will allow for increased efficiency as well as for reduced environmental impact. Currently, innovative sensing and actuating technologies together with improved information and communication technologies provide the potential for such advancements. However, the full exploitation of these engineering advances requires the traditional agricultural machinery management process to be revisited. As a result, traditional agricultural operations planning methods, especially the job-shop planning methodology, must be supplemented with new planning features, such as route planning and sequential task scheduling. The objectives of this review are to outline current and required advances in agricultural machinery management to prepare for future intelligent manned and/or autonomous sustainable operations in agriculture. In the following sections, five key management tasks for agricultural machinery management are selected that span the various management phases and levels. These tasks are i) capacity planning (strategic level), task times planning (tactical level), scheduling (operational), route planning (operational level), and performance evaluation (evaluation level). For each of the management tasks, a definition is provided, and the most recent related literature is presented. Finally, the future requirements which will facilitate and set the framework for the development efforts necessary for fully implementing future agricultural management models and tools are discussed." @default.
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• W2022673873 date "2014-10-01" @default.
• W2022673873 modified "2023-10-17" @default.
• W2022673873 title "Advances in agricultural machinery management: A review" @default.
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• W2022673873 doi "https://doi.org/10.1016/j.biosystemseng.2014.07.012" @default.
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