智能 "供应链的崛起:人工智能和自动化如何彻底改变物流业

Temitayo Oluwadamilola Adesoga, Tolulope Olusola Ajibaye, Kenneth Chukwujekwu Nwafor, Ummulikhaeri Temitope Imam-Lawal, Emmanuel Ayobamidele Ikekwere, Daniel Ikechukwu Ekwunife
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摘要

在人工智能(AI)和自动化推动的 "智能 "供应链崛起的推动下,物流业正在经历转型变革。本研究报告探讨了这一技术带来的变革性影响,探讨了它如何在整个供应链中提高生产率、降低成本、增强决策和库存管理的能力。本文以运输、仓储和需求预测为重点,全面阐述了在物流领域实施人工智能和自动化的相关优势和挑战。真实世界的例子和案例研究说明了这些技术的实际应用及其重塑供应链管理未来的潜力。人工智能算法利用大数据精确预测未来,帮助企业通过自动补货和降低库存水平来简化运营,从而重塑库存管理。在运输方面,人工智能可根据交通、天气和交货时间优化路线,从而节省燃料、加快交货和降低成本。在仓储方面,人工智能通过加强调度、自动处理和机器人传送带提高了效率和准确性。此外,人工智能驱动的需求预测整合了销售数据、消费趋势和社交媒体洞察力,可准确预测需求,从而加强生产规划和客户服务。采用 "智能 "供应链面临几个障碍。由于对大数据的依赖,人们对数据隐私产生了担忧,因此必须采取严格的数据管理措施并遵守隐私法。实施人工智能的技术障碍和高昂的初始成本尤其令小型企业望而生畏。潜在的解决方案,如与人工智能提供商合作或关注长期效益,为克服这些挑战提供了策略。尽管存在这些障碍,人工智能和自动化仍具有巨大的潜力,可彻底改变物流业,为企业提供竞争优势、成本优化和优质客户服务。随着这些技术的进步,高效、敏捷的交付前景光明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The rise of the "smart" supply chain: How AI and automation are revolutionizing logistics
The logistics industry is experiencing transformational change driven by the rise of "smart" supply chains enabled by artificial intelligence (AI) and automation. This study examines the transformational impact of this technology, exploring how it increases productivity, reduces costs, and empowers better decision-making and inventory management throughout the supply chain. Focusing on transportation, warehousing, and demand forecasting, the paper provides a comprehensive view of the benefits and challenges associated with implementing AI and automation in logistics. Real-world examples and case studies illustrate the practical applications of these technologies and their potential to reshape the future of supply chain management. AI algorithms are reshaping inventory management by leveraging big data for precise future predictions, helping companies streamline operations through automated replenishment and reduced stock levels. In transportation, AI optimizes routes considering traffic, weather, and delivery times, leading to fuel savings, faster deliveries, and lower costs. Warehousing benefits from AI with enhanced scheduling, automated processing, and robotic conveyors improving efficiency and accuracy. Furthermore, AI-driven demand forecasting integrates sales data, consumer trends, and social media insights to forecast demand accurately, enhancing production planning and customer service. The adoption of "smart" supply chains faces several hurdles. Concerns over data privacy due to reliance on big data necessitate stringent data management practices and compliance with privacy laws. Technical barriers and high initial costs for AI implementation are particularly daunting for smaller businesses. Potential solutions, like partnering with AI providers or focusing on long-term benefits, offer strategies to overcome these challenges. Despite these obstacles, AI and automation hold immense potential to revolutionize logistics, offering companies competitive advantages, cost optimization, and superior customer service. As these technologies advance, the future of efficient and agile delivery looks promising.
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