Customer Success Story: Continental AG
公司规模
1,000+
地区
- Europe
国家
- Germany
产品
- ICONICS’ HMI/SCADA suite
- ICONICS data historian
技术栈
- Database for Online Process Analysis and Control (DOPAC)
- Statistical Process Control (SPC)
实施规模
- Enterprise-wide Deployment
影响指标
- Innovation Output
- Productivity Improvements
技术
- 分析与建模 - 实时分析
- 应用基础设施与中间件 - 数据交换与集成
适用行业
- 汽车
适用功能
- 离散制造
- 质量保证
用例
- 自动化制造系统
- 实时定位系统 (RTLS)
服务
- 系统集成
关于客户
Continental AG, headquartered in Hanover, Germany, is the world’s fourth largest tire manufacturer. Founded in 1871 as a rubber manufacturer, the company now contains additional divisions handling brake systems, interior electronics, automotive safety, powertrain/chassis components, tachographs and additional parts for the automotive and transportation industries. Almost every third car in Europe is delivered with tires from Continental. Its Division Tires features tire brands like Continental, Uniroyal, General Tire, Semperit, Barum and many more. Today the company has over 227,000 employees in 56 countries.
挑战
Continental AG, a leading tire manufacturer, sought to update their process analysis and control systems across 18 separate locations worldwide. The company aimed to develop a system capable of near real-time data collection from production equipment for process and product analysis and optimization. This led to the initiation of the 'DOPAC' project, standing for 'Database for Online Process Analysis and Control'. A pilot project began in 2016 in the company’s Puchov, Slovakia plant, with a year spent on prototype development. The company decided to move on from installed legacy systems and, after considering multiple vendor solutions, decided upon ICONICS HMI/SCADA and data historian to comprise the heart of DOPAC.
解决方案
Continental AG selected ICONICS’ HMI/SCADA suite, in addition to the high-speed, reliable, robust plant historian. The new system was intended to steer and continuously improve the company’s production processes based on statistical process control (SPC) measurement of product performance-relevant data. A taskforce was put together to clearly define the company’s IT requirements, as the right pertinent performance data was deemed necessary for continuous improvement. On top actual product and process data were for intended advanced analytics. High on the list was real-time data collection. Another necessity was a redundant architecture, including data buffering at sources. The company also highly valued integrating specification systems, high-rate data compression and data mapping.
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