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How AI is Transforming Manufacturing
技术
- 分析与建模 - 机器学习
适用行业
- 汽车
适用功能
- 离散制造
用例
- 工厂可见化与智能化
服务
- 软件设计与工程服务
挑战
让缺陷逃出工厂会损害客户关系和品牌，并导致代价高昂的拒收或退货，而对内部缺陷的过度控制会导致高昂的劳动力、废品和返工成本。缺陷检测的有害问题本应通过机器视觉检测来解决，但在许多情况下，机器视觉系统无法胜任这项任务。
- 没有对阀门和电机的状态监测。
- 对故障设备的根本原因分析很困难或根本不存在。
- 工程师每周花费数小时制作电子表格和分析。
客户
美利肯
关于客户
全球化学和纺织公司。
解决方案
在制造工厂中部署用于机器视觉的人工智能。提取物料清单、工程图纸和零件规格，以了解复杂的装配应该是什么样子——然后观察生产线上的文章，以确保每个工位的装配都是正确的。
运营影响
数量效益
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.
