工厂运营可见性和智能
概述
可视化工厂运营数据是当今许多制造商面临的挑战。一些制造商今天正在推行的 IIoT 计划之一是提供工厂运营和机器健康状况的实时可见性。目标是提高制造效率。挑战在于组合和关联在性质、来源和生命周期方面差异很大的不同数据源。工厂运营可视性和智能 (FOVI) 旨在收集工厂车间生成的传感器数据、生产设备日志、生产计划和统计数据、操作员信息,并将所有这些信息和其他相关信息集成到云中。通过这种方式,它可以用来为生产设施带来可见性,分析和预测结果,并支持更好的改进决策。
适用行业
- 重型车辆
- 汽车
适用功能
- 离散制造
市场规模
案例研究.
Case Study
Automotive Component Manufacturer Improves with Datonis IoT Solution
As a part of their Industry 4.0 initiative, the customer primarily wished to leverage IoT for maximizing operational efficiencies, productivity, reducing the energy footprints and maximizing capacity utilization. But there were several challenges at the outset:Firstly, the customer had multiple assembly lines with a diverse set of machines, systems and sensors, all communicating on different protocols. As such, primarily they needed a partner who could connect diverse set of assets on to a single platform and make use of underutilized ‘dark’ data.Secondly, the amount of data, data types and their applications was so vast, that the platform handling it, needed to be scalable and flexible.Lastly, Varroc faced the typical challenge of innovating in ‘Brownfield’ markets – wherein the real bottleneck is in integrating IoT in tandem with both the new and legacy equipment without any further CAPEX for asset substitution.
Case Study
AGCO is Increasing the Efficiency of its Manufacturing Programs Using Glass
The thorough inspection of a finished product is an essential step in the quality-control process. In the beginning, quality checklists were accessed using paper on clipboards. As technology improved, computers were utilized. But computers required additional time to access, and couldn’t be carried to the equipment being inspected. Tablets replaced computers, but were easily broken and expensive to replace.
Case Study
Geith International
The complex Business requirements and existing Legacy platforms posed challenges for Geith. Given the size of business, the costs had to be kept under strict control so as to justify the business case and extract the expected returns. Moreover, the implementation timelines were to be kept at a minimum, so as to avoid business disruption.