Digital Twins & Real-Time Supply Chain Operations

2022-07-23 16:00:44
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Illustration: © IoT For All

Disruptions and instability within global supply chains have been the subject of intense media focus in the wake of the ongoing COVID-19 pandemic. Shortages of raw materials, ingredients, components, and certain finished goods are impacting daily life. Supply chain issues are not specific to any one industry, but global supply chain shocks are occurring more frequently and have a bigger impact on organizations than ever before. Visibility remains a key supply chain technology component, but expanded capabilities now move beyond that by deploying digital twin technology, enabling companies to digitize their entire end-to-end supply chains, embed intelligence and automation, optimize operations and increase on-time in-full (OTIF) delivery.

'Digital twin technology provides a virtual representation of the entire supply chain ecosystem—a virtual map of assets across operations and business processes.' -ParkourSCClick To Tweet

The costs of disruption are significant, too. In the pharmaceutical sector, the industry stands to lose an average of 24 percent of one year’s EBITDA every ten years due to supply chain disruptions. Clearly, this is not good business, nor is it sustainable in the long term. Companies must identify risks and vulnerabilities right away, and then adapt their plans and supply chain operations to mitigate these issues so they can course-correct as soon as possible. Ideally, organizations should have enough data-driven visibility and intelligence embedded into their supply chains to take preemptive steps rather than scrambling to find a solution. Alleviating supply chain challenges begins with gaining visibility into the end-to-end supply chain, then applying intelligence and automation to the workflow, allied to systems that manage risk and volatility.

Creating More Resilient Supply Chains

Across the whole ecosystem of customers, suppliers, and transportation modalities, new tools and technologies are fast emerging in the cloud to help build better, more resilient supply chains. There are three fundamental elements that, combined, will drive tangible improvements in real-time supply operations and help minimize the effect of disruption.

  1. Create digital twin models of supply chain networks, enabling real-time operational modeling and monitoring.
  2. Leverage actionable intelligence to anticipate problem scenarios, incorporate ground truth into operations, and automate response to potential disruptions.
  3. Empower partners and suppliers to collaborate and optimize the ecosystem to coordinate supply chain operations at all stages. This includes monitoring all assets and inventory throughout the supply chain to continuously align planning and execution with ground truths to improve service levels.

Advantages of Digital Twin Technology

#1: Virtual Representation

Digital twin technology provides a virtual representation of the entire supply chain ecosystem—a virtual map of assets across operations and business processes that is built from vast amounts of accessible, real-time, ground truth data flowing across connected systems. Historically, digital twins were associated more with static analysis, but now the concept is being operationalized to track many dependencies to mitigate risks, automate workflows and corrective action, and drive better supply chain resilience.

#2: Data Intelligence

Digitizing the supply chain using digital twins allows all constituents to be constantly monitored at multiple levels, including attributes, configuration, and metadata. Deep signal and data intelligence can be generated from any entity, system, or device—from containers and pallets right down to individual unit boxes, bottles, and vials—and shared via interactive dashboards in real-time. The resulting thread of connected data allows organizations to overcome data and organizational silos—within their own company and across every other organization involved in the supply chain—and truly understand how well the entire supply chain is performing on a minute-to-minute basis.

Embedding deep data intelligence into these digital twin models builds transparency. This creates approved cross-organizational collaboration across all partners in the ecosystem. Any variance or disruptions to the plans can be identified and flagged quickly. Partners can identify and resolve subpar performance or deviations in any aspect of the supply chain, thereby improving resilience. Predictive modeling is also possible with digital twins. So, organizations can virtually model and test what-if scenarios where disruptions may occur, with potential actions and outcomes outlined. Now, organizations can prepare contingency plans for supply chain failures, disruptions, and supply-demand fluctuations.

#3: Collaboration

Since secure components of digital twins can be shared with suppliers and other partners in the ecosystem, continuous realignment, collaboration, and communication are possible across every organization and constituent involved, regardless of location. Digital twins can be easily extended across these networks with AI/ML and low-code/no-code scripts that help drive predictive intelligence and automated workflows across the entire supply chain. Furthermore, networks of digital twins can be extensible, with more components added to the supply chain infrastructure that can provide the visibility required to highlight duplicate dependencies and sources for any given element, regardless of whether a supplier is one or more levels removed from the core. So, with a network of digital twins, there’s a common node where the risk of duplication of effort can be identified and removed. This serves to streamline and improve overall supply chain efficiencies.

The Future of Supply Chain Issues

Supply chain disruptions are here for the foreseeable future, and this is prompting more investment in solutions that drive greater resilience and agility to supply chain operations. Digital twins free organizations to innovate faster and on a larger scale while reducing risk by identifying points of weakness and driving strategic initiatives to reduce cycle time. They can greatly reduce some of the uncertainty that exists in supply chain operations today. Organizations can use digital twins to increase their competitive edge through efficiencies gained from better insight into sourcing, manufacturing, inventory locations, and logistics tracking—even at the individual item level.

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  • Asset Tracking
  • Equipment Tracking
  • Freight and Package Tracking
  • Industrial Internet of Things
  • Supply Chain and Logistics

  • Asset Tracking
  • Equipment Tracking
  • Freight and Package Tracking
  • Industrial Internet of Things
  • Supply Chain and Logistics

参考译文
数字双胞胎和实时供应链运营
插图:© IoT For All → 在持续的新冠疫情之后,全球供应链中的中断与不稳定性已成为媒体高度关注的焦点。原材料、配料、组件以及某些成品的短缺正在影响人们的日常生活。供应链问题并非某个行业的专属现象,但如今全球供应链冲击的频率更高,对组织的冲击也比以往任何时候都更大。供应链的可见性仍然是关键的技术要素,但如今通过部署数字孪生技术,其能力已得以扩展,使企业能够将整个端到端供应链数字化,嵌入智能化和自动化,优化运营,并提高准时完整交付(OTIF)的效率。“数字孪生技术为整个供应链生态系统提供了虚拟映射——一张横跨运营和业务流程的资产虚拟地图。”——ParkourSC 点击分享推特 中断所带来的成本也是巨大的。在制药行业,行业平均在每十年中由于供应链中断将损失一年息税折旧摊销前利润(EBITDA)的24%。显然,这并非良好的商业做法,也难以在长期内持续。企业必须迅速识别风险与脆弱点,并据此调整自己的计划与供应链运营,以减轻这些问题,从而尽快做出修正。理想情况下,组织应在供应链中嵌入充足的数据驱动可见性与智能,以便采取预防性措施,而不是仓促寻找解决方案。缓解供应链挑战的第一步是获得端到端供应链的可见性,然后将智能与自动化应用于工作流程,同时配合管理风险与波动性的系统。 打造更具韧性的供应链 在客户、供应商和运输方式的整个生态系统中,基于云的新工具和技术正在快速涌现,以帮助建立更强大、更具韧性的供应链。有三个基本要素结合在一起,将推动实时供应链操作的实质性改进,并有助于最大限度地减少中断带来的影响: 1. 创建供应链网络的数字孪生模型,实现实时操作建模与监控。 2. 利用可操作的智能,提前预测问题场景,将真实数据嵌入运营中,并对潜在中断进行自动化响应。 3. 赋能合作伙伴与供应商协作,优化生态系统,协调整个供应链流程。这包括监控供应链中的所有资产和库存,持续地将计划与执行与实际情况对齐,以提升服务水准。 数字孪生技术的优势 1. 虚拟映射 数字孪生技术为整个供应链生态系统提供了虚拟映射——这是由大量可访问的、实时的、真实数据构建而成的虚拟资产地图,这些数据来自相互连接的系统。历史上,数字孪生更多与静态分析有关,但现在这一概念已被操作化,用于追踪多种依赖关系,以缓解风险、自动化工作流程和纠正措施,并提升供应链的韧性。 2. 数据智能 通过数字孪生对供应链进行数字化,使得所有参与者可以在多个层面上被持续监控,包括属性、配置和元数据。深度信号与数据智能可以来自任何实体、系统或设备——从集装箱、托盘,一直到单个包装盒、瓶子和小瓶,并可通过交互式仪表板实时共享。由此产生的数据链使组织能够克服数据和组织壁垒——无论是在他们自己的公司内部,还是在供应链中每一家相关组织之间——并真正了解整个供应链每分钟的运行情况。将深度数据智能嵌入这些数字孪生模型中,可以提升透明度。这有助于在生态系统内所有合作伙伴之间建立正式的跨组织协作。任何计划偏差或中断都能快速识别并标记出来。合作伙伴可以在供应链的任何环节识别并解决低效表现或偏差,从而提高韧性。通过数字孪生,预测性建模也是可行的。因此,组织可以虚拟建模并测试各种可能发生的中断场景,并列出潜在的应对措施与结果。如今,组织可以为供应链故障、中断和供需波动提前制定备选计划。 3. 协作 由于数字孪生的安全组件可以与生态系统中的供应商和其他合作伙伴共享,因此所有涉及的组织和参与者都可以实现持续的重新校准、协作与沟通,无论其地理位置如何。数字孪生可以通过人工智能/机器学习(AI/ML)和低代码/无代码脚本轻松扩展到这些网络中,从而在整个供应链中推动预测性智能和自动化流程。此外,数字孪生网络可以扩展,可将更多组件加入供应链基础设施,从而提供所需的可见性,以突出任何特定元素的重复依赖关系和来源,无论供应商是核心环节的一级还二级。因此,通过数字孪生网络,可以识别出一个共同节点,用于识别并消除重复工作的风险。这有助于简化并提升整体供应链效率。 供应链问题的未来 供应链中断在未来一段时间内仍将持续存在,这促使企业加大对解决方案的投资,以增强供应链运营的韧性和敏捷性。数字孪生使组织能够以更快的速度和更大规模进行创新,同时通过识别弱点并推动战略性举措来减少周期时间,从而降低风险。它们可以大大减少目前供应链运营中存在的一些不确定性。企业可以利用数字孪生技术,通过更深入地了解采购、制造、库存位置和物流追踪(甚至到单个物品层级)所带来的效率,提升自身的竞争优势。 推文分享邮件 资产追踪 设备追踪 货运与包裹追踪 工业物联网 供应链与物流 → 资产追踪 设备追踪 货运与包裹追踪 工业物联网 供应链与物流
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