Leveraging I4.0 smart methodologies for developing solutions for harvesting produce

Ava Recchia, Jill Urbanic
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Abstract

Leveraging Computer-Aided Design (CAD) and Manufacturing (CAM) tools with advanced Industry 4.0 (I4.0) technologies presents numerous opportunities for industries to optimize processes, improve efficiency, and reduce costs. While certain sectors have achieved success in this effort, others, including agriculture, are still in the early stages of implementation. The focus of this research paper is to explore the potential of I4.0 technologies and CAD/CAM tools in the development of pick and place solutions for harvesting produce. Key technologies driving this include Internet of Things (IoT), machine learning (ML), deep learning (DL), robotics, additive manufacturing (AM), and simulation. Robots are often utilized as the main mechanism for harvesting operations. AM rapid prototyping strategies assist with designing specialty end-effectors and grippers. ML and DL algorithms allow for real-time object and obstacle detection. A comprehensive review of the literature is presented with a summary of the recent state-of-the-art I4.0 solutions in agricultural harvesting and current challenges/barriers to I4.0 adoption and integration with CAD/CAM tools and processes. A framework has also been developed to facilitate future CAD/CAM research and development for agricultural harvesting in the era of I4.0.
利用 I4.0 智能方法开发农产品收获解决方案
将计算机辅助设计(CAD)和制造(CAM)工具与先进的工业 4.0(I4.0)技术相结合,为各行各业优化流程、提高效率和降低成本提供了大量机会。虽然某些行业已经在这方面取得了成功,但包括农业在内的其他行业仍处于实施的早期阶段。本研究论文的重点是探索 I4.0 技术和 CAD/CAM 工具在开发农产品采摘和放置解决方案方面的潜力。推动这一进程的关键技术包括物联网 (IoT)、机器学习 (ML)、深度学习 (DL)、机器人技术、增材制造 (AM) 和仿真。机器人通常被用作收割作业的主要机制。AM 快速成型策略有助于设计特殊的末端执行器和抓手。ML 和 DL 算法可实现实时物体和障碍物检测。本文对文献进行了全面回顾,总结了农业收割领域最新的 I4.0 解决方案,以及当前采用 I4.0 并与 CAD/CAM 工具和流程集成所面临的挑战/障碍。此外,还制定了一个框架,以促进 I4.0 时代农业收获领域未来 CAD/CAM 的研究与开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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