下载PDF
Large U.S. Based Appliance Manufacturer Relies on NETSCOUT to Ensure Reliability of Customer Ordering Process
技术
- 应用基础设施与中间件 - API 集成与管理
- 应用基础设施与中间件 - 数据交换与集成
- 应用基础设施与中间件 - 数据库管理和存储
适用功能
- 离散制造
- 销售与市场营销
用例
- 库存管理
- 预测性维护
- 供应链可见性(SCV)
服务
- 系统集成
- 测试与认证
挑战
该制造商面临的挑战是其定制订单管理应用程序出现中断,这干扰了订单处理,导致收入损失和客户体验受损。这些服务中断还引发了巨额罚款,必须向零售商支付。一次中断就可能轻易引发数十万美元的罚款。由于缺乏对其定制应用程序的远程站点监控,IT 部门在问题检测和跨多个远程位置分类的能力方面面临严重延迟。IT 团队不得不依靠用户报告问题,这给他们带来了巨大的压力,以确保可用性和性能。
关于客户
该客户是家用电器领域的领导者,旗下有多个品牌。他们生产和销售洗衣机、冰箱、热水器和空调。该公司通过革新其许多家用产品的数字连接和运营,引领行业创新并拥抱物联网。这家市值 60 亿美元的制造公司在其位于美国南部的总部、全球多个制造基地和运营地点拥有 10,000 多名员工。凭借在美国的多家工厂和全球各地的研发设施,以及遍布众多大型零售连锁店的销售点 (POS) 订购功能,连接是这家制造商业务的命脉。
解决方案
为了满足制造商的关键应用程序和网络性能监控需求,他们求助于 NETSCOUT®。部署了 nGeniusONE 和 InfiniStream 设备,以便在关键服务问题影响业务之前快速识别、隔离和缓解这些问题。nGenius 数据包流交换机用于将网络流量馈送到 InfiniStream 设备和其他分析工具,使 IT 能够持续监控应用程序以确保可用性和性能。NETSCOUT 解决方案使 IT 团队能够直接监控三个大型制造设施并远程监控 32 个分布式站点。这使 IT 能够确保公司中央订购应用程序的可用性,该应用程序被数千家商店和无数客户使用。
运营影响
数量效益
相关案例.
Case Study
Remote Monitoring & Predictive Maintenance App for a Solar Energy System
The maintenance & tracking of various modules was an overhead for the customer due to the huge labor costs involved. Being an advanced solar solutions provider, they wanted to ensure early detection of issues and provide the best-in-class customer experience. Hence they wanted to automate the whole process.
Case Study
Remote Temperature Monitoring of Perishable Goods Saves Money
RMONI was facing temperature monitoring challenges in a cold chain business. A cold chain must be established and maintained to ensure goods have been properly refrigerated during every step of the process, making temperature monitoring a critical business function. Manual registration practice can be very costly, labor intensive and prone to mistakes.
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.
Case Study
Aircraft Predictive Maintenance and Workflow Optimization
First, aircraft manufacturer have trouble monitoring the health of aircraft systems with health prognostics and deliver predictive maintenance insights. Second, aircraft manufacturer wants a solution that can provide an in-context advisory and align job assignments to match technician experience and expertise.
Case Study
Integral Plant Maintenance
Mercedes-Benz and his partner GAZ chose Siemens to be its maintenance partner at a new engine plant in Yaroslavl, Russia. The new plant offers a capacity to manufacture diesel engines for the Russian market, for locally produced Sprinter Classic. In addition to engines for the local market, the Yaroslavl plant will also produce spare parts. Mercedes-Benz Russia and his partner needed a service partner in order to ensure the operation of these lines in a maintenance partnership arrangement. The challenges included coordinating the entire maintenance management operation, in particular inspections, corrective and predictive maintenance activities, and the optimizing spare parts management. Siemens developed a customized maintenance solution that includes all electronic and mechanical maintenance activities (Integral Plant Maintenance).
Case Study
Hospital Inventory Management
The hospital supply chain team is responsible for ensuring that the right medical supplies are readily available to clinicians when and where needed, and to do so in the most efficient manner possible. However, many of the systems and processes in use at the cancer center for supply chain management were not best suited to support these goals. Barcoding technology, a commonly used method for inventory management of medical supplies, is labor intensive, time consuming, does not provide real-time visibility into inventory levels and can be prone to error. Consequently, the lack of accurate and real-time visibility into inventory levels across multiple supply rooms in multiple hospital facilities creates additional inefficiency in the system causing over-ordering, hoarding, and wasted supplies. Other sources of waste and cost were also identified as candidates for improvement. Existing systems and processes did not provide adequate security for high-cost inventory within the hospital, which was another driver of cost. A lack of visibility into expiration dates for supplies resulted in supplies being wasted due to past expiry dates. Storage of supplies was also a key consideration given the location of the cancer center’s facilities in a dense urban setting, where space is always at a premium. In order to address the challenges outlined above, the hospital sought a solution that would provide real-time inventory information with high levels of accuracy, reduce the level of manual effort required and enable data driven decision making to ensure that the right supplies were readily available to clinicians in the right location at the right time.