技术
- 分析与建模 - 预测分析
- 平台即服务 (PaaS) - 应用开发平台
适用行业
- 设备与机械
- 运输
适用功能
- 物流运输
- 销售与市场营销
用例
- 最后一英里交付
- 交通模拟
服务
- 硬件设计与工程服务
关于客户
思科是全球 IT 领导者,企业依靠其提供硬件、软件和服务来运行关键基础设施。该公司因可靠、高性能的设备和世界一流的客户服务而享有盛誉,这是其价值的核心部分。 DHL Service Logistics 代表思科在亚太地区 19 个国家/地区管理全面的服务和支持物流运营。该业务包括来自每年 365 天运营的 80 个 DHL 快速履行站点的硬件和备件,在短短两个小时内运送更换设备,并与思科自己的销售、客户支持和技术团队密切协调。
挑战
全球 IT 领导者思科依靠 DHL Service Logistics 来管理亚太地区 19 个国家/地区的综合服务和支持物流运营。该业务包括来自 80 个全年 365 天运营的 80 个 DHL 快速履行站点的硬件和备件。然而,该网络在应对突发事件方面面临着挑战,从轻微的运输延误到重大的自然灾害。目标是提高服务运营绩效并增强为思科客户提供的支持。需要增强网络的弹性和敏捷性,以有效处理突发事件。
解决方案
DHL 向领先的供应链预测分析公司 Everstream Analytics 寻求帮助,以提高思科供应链的弹性和敏捷性。 Everstream 基于历史事件数据提供位置级风险分析,并通过单一集成门户实时监控潜在的破坏性事件。该平台在新加坡的思科物流支持中心启动,提供网络中所有运营地点和主要货运通道的综合模型。每个位置都在街道地址级别进行地理编码,提供供应链风险的性质和严重性的详细概述。这有助于制定风险管理、缓解措施和应急计划。该平台还支持在考虑新仓库地点或运输路线时的风险评估流程,使公司能够为设施选择安全的位置,并有针对性地投资于风险缓解活动。
运营影响
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
相关案例.
![](/files/casestudy/Smart-Water-Filtration-Systems.png)
Case Study
Smart Water Filtration Systems
Before working with Ayla Networks, Ozner was already using cloud connectivity to identify and solve water-filtration system malfunctions as well as to monitor filter cartridges for replacements.But, in June 2015, Ozner executives talked with Ayla about how the company might further improve its water systems with IoT technology. They liked what they heard from Ayla, but the executives needed to be sure that Ayla’s Agile IoT Platform provided the security and reliability Ozner required.
![](/files/casestudy/IoT-enabled-Fleet-Management-with-MindSphere.png)
Case Study
IoT enabled Fleet Management with MindSphere
In view of growing competition, Gämmerler had a strong need to remain competitive via process optimization, reliability and gentle handling of printed products, even at highest press speeds. In addition, a digitalization initiative also included developing a key differentiation via data-driven services offers.
![](/files/casestudy/Predictive-Maintenance-for-Industrial-Chillers.png)
Case Study
Predictive Maintenance for Industrial Chillers
For global leaders in the industrial chiller manufacturing, reliability of the entire production process is of the utmost importance. Chillers are refrigeration systems that produce ice water to provide cooling for a process or industrial application. One of those leaders sought a way to respond to asset performance issues, even before they occur. The intelligence to guarantee maximum reliability of cooling devices is embedded (pre-alarming). A pre-alarming phase means that the cooling device still works, but symptoms may appear, telling manufacturers that a failure is likely to occur in the near future. Chillers who are not internet connected at that moment, provide little insight in this pre-alarming phase.
![](/files/casestudy/Premium-Appliance-Producer-Innovates-with-Internet-of-Everything.png)
Case Study
Premium Appliance Producer Innovates with Internet of Everything
Sub-Zero faced the largest product launch in the company’s history:It wanted to launch 60 new products as scheduled while simultaneously opening a new “greenfield” production facility, yet still adhering to stringent quality requirements and manage issues from new supply-chain partners. A the same time, it wanted to increase staff productivity time and collaboration while reducing travel and costs.
![](/files/casestudy/Integration-of-PLC-with-IoT-for-Bosch-Rexroth.png)
Case Study
Integration of PLC with IoT for Bosch Rexroth
The application arises from the need to monitor and anticipate the problems of one or more machines managed by a PLC. These problems, often resulting from the accumulation over time of small discrepancies, require, when they occur, ex post technical operations maintenance.
![](/files/casestudy/Data-Gathering-Solution-for-Joy-Global.png)
Case Study
Data Gathering Solution for Joy Global
Joy Global's existing business processes required customers to work through an unstable legacy system to collect mass volumes of data. With inadequate processes and tools, field level analytics were not sufficient to properly inform business decisions.