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在正确的时间以合适的价格提供合适的产品是当今供应链管理的概念（Bastas和Liyanage，2018）。然而，在如此庞大的网络，用户和商品的前提下，人们很难完全依赖人工计算来满足精细运营管理的需求。因此，人工智能在整个供应链中的作用越来越重要。企业可以在供应链的多个环节中使用人工智能，这体现在以下几个方面，如智能预测，它基于历史数据和统计学习模型来预测未来商品的销量，单一的仓库数量促销期间的每个维度和促销活动，以便对相关业务数据和相关规划支持进行更智能的预测;智能商品，它是基于大数据实现智能商品分类和多维度的产品特征和价值评估;智能定价：它基于统计学习和决策树来进行动态定价，实现客户至上，供需协同和可持续的最优定价策略;智能库存：基于大数据平台和销售预测，为采购，库存管理等提供更智能的建议（Lieto，Bhatt，Oltramari和Vernon，2018）。此外，人工智能可以科学地分配订单生产路线和快递安排，以最佳方式满足每个客户的及时性要求。它还可以基于模式识别和其他技术的风险控制系统，以及时提醒订单的风险级别，并提供更安全和更可靠的客户体验。
Providing right products at right prices in right places at the right time is the concept of today's supply chain management (Bastas and Liyanage, 2018). However, under the premise of such a huge network, users, and commodities, it is difficult for people to rely solely on human computing to meet the needs of fine operation management. Thus, the role of artificial intelligence in the entire supply chain is increasingly important. Companies can use artificial intelligence in multiple segments of supply chain, which is reflected in the following aspects, such as intelligent forecasting, it is based on historical data and statistical learning models to forecast the future sales volume of commodities, the single volume of warehouses in each dimension, and the sales promotion during a promotion period to give more intelligent forecast of related business data and related planning support; intelligent goods, it is based on big data to achieve intelligent goods classification and evaluation of product features and values from multiple dimensions; intelligent pricing: it is based on statistical learning and decision trees to conduct dynamic pricing and achieve customer-first, supply-demand synergy and sustainable optimal pricing strategies; intelligent inventory: it is based on big data platform and sales forecast to provide more intelligent suggestions for procurement, inventory management, etc. (Lieto, Bhatt, Oltramari and Vernon, 2018). In addition, artificial intelligence can scientifically distribute order production route and express delivery arrangements to meet each client's timeliness requirements in an optimal manner. It can also be based on the risk control system of pattern recognition and other technologies to promptly alert an order's risk level and provide a safer and more reliable customer experience.
从以上分析可以看出，人工智能可以应用于供应链的每个环节。人工智能可以对供应链的不同环节带来颠覆性变化，例如采购，重复订单和库存管理（Liew，2018）。例如，在采购中，它根据交货期，生产能力，地区和产品类别等因素建立了综合分析模型。系统会自动推荐最合适的打样/生产供应商。越来越多的公司正试图以这种方式解决采购过程中的一些实际问题。
From the above analysis, it can be seen that artificial intelligence can be applied to every link of supply chain. Artificial intelligence can bring disruptive changes to different links of supply chain, such as procurement, repeating orders and inventory management (Liew, 2018). For instance, in procurement, it establishes a comprehensive analysis model from factors such as delivery period, production capacity, region, and product category. The system automatically recommends the most suitable proofing/production supplier at the moment. More and more companies are trying to solve some practical problems in the procurement process in this way.
就重复订单而言，智能选择是通过大数据技术进行的，大数据技术从大量商品中选择潜在畅销商品，并通过结合机器学习和统计数据设计预测模型和补货模型，并结合大数据技术实现预测和海量数据存储的补货计算，可以预测未来各地区的销量和库存量，实现智能自动补货。他们都可以准备抓住潜在的畅销商，为公司带来最大的利益，从而大大节省劳动力成本。许多公司现在采用VMI模型来降低成本。智能重复订单的实现正是VMI模式的完美结合。As far as repeating orders is concerned, smart selection is conducted through big data technology, which selects potential bestsellers from massive commodities and designs predictive models and replenishment models by using a combination of machine learning and statistics, and combining large data technologies to achieve forecasting and replenishment calculations of massive data memory, which can predict the sales volume and stocking volume in each region in the future and realize intelligent automatic replenishment. They can both prepare to grasp potential bestsellers to bring maximum benefits to a company to greatly save labor costs. Many companies are now adopting the VMI model to reduce their costs. The realization of intelligent repeating orders is precisely the perfect combination with VMI mode.
随着人工智能应用的深入，企业可以逐步建立有效的供应链系统模拟机制，并在此基础上构建强化学习系统，使供应链系统能够应对更复杂的问题。With the deepening of artificial intelligence applications, companies can gradually establish an effective supply chain system simulation mechanism, and build a reinforcement learning system based on this, so that the supply chain system can deal with more complex issues.
总而言之，供应链中的人工智能应用仍在探索中，但人们相信人工智能技术的使用将能够协同管理供应链的多个领域，如采购，物流，定价等，从而实现更优化的资源配置，为供应链管理带来巨大变化。All in all, artificial intelligence applications in supply chain is still explored, but it is believed that the use of artificial intelligence technology will be able to collaboratively manage multiple areas of supply chain, such as procurement, logistics, pricing, etc., thereby achieving more optimal resource allocation to bring great changes to supply chain management.
References
Bastas, A. and Liyanage, K. (2018). Sustainable supply chain quality management: A systematic review. Journal of Cleaner Production, 181(20), 726-744.
Lieto, A., Bhatt, M., Oltramari, A. and Vernon, D. (2018). The role of cognitive architectures in general artificial intelligence. Cognitive Systems Research, 48(5), 1-3.
Liew, C. (2018). The future of radiology augmented with Artificial Intelligence: A strategy for success. European Journal of Radiology, 102(5), 152-156.
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