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Scalable Predictive Maintenance in Nissan
技术
- 分析与建模 - 机器学习
- 分析与建模 - 预测分析
- 功能应用 - 企业资产管理系统 (EAM)
- 功能应用 - 远程监控系统
适用行业
- 汽车
适用功能
- 维护
用例
- 预测性维护
挑战
由于拥有丰富的数据和不足以进行分析的熟练资源，Nissan 热衷于扩大使用数据影响维护的好处。它决定启动一项基于状态的维护计划，以将数千种不同资产的生产停机时间减少多达 50%。 Senseye 因其以机器学习为基础的强大预测产品而被 Senseye 所吸引。
客户
日产
关于客户
日产汽车在全球 20 个国家和地区生产汽车，包括日本、美国、俄罗斯和英国。 2016年全球汽车产量超过560万辆，产品和服务遍及160多个国家。
解决方案
Senseye 正在为多个全球日产生产基地提供预测性维护能力，这些生产基地生产逍客、X-Trail、Leaf 和英菲尼迪等车型。使用 Senseye 专有的机器学习算法远程监控 9,000 项连接的资产和 30 多种不同的机器类型，包括机器人、输送机、升降机、泵、电机和冲压机/冲压机。超过 400 名维护用户积极使用 Senseye 来优化维护活动，并在预测的机器故障前几个月进行维修。
运营影响
相关案例.
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
Monitoring of Pressure Pumps in Automotive Industry
A large German/American producer of auto parts uses high-pressure pumps to deburr machined parts as a part of its production and quality check process. They decided to monitor these pumps to make sure they work properly and that they can see any indications leading to a potential failure before it affects their process.
