- 分析与建模 - 机器人过程自动化 (RPA)
• 手动数据收集导致运营成本高 • 计费不准确和延迟导致客户满意度低
美国领先的运输和物流服务提供商，服务于北美、南美、欧洲和亚洲的客户。它拥有 1,000 多个地点和 200,000 辆汽车，解决了运输和物流难题
• 有效的数据管理，以提高计费预测的准确性和速度 • 自动化的收入收集和报告流程，以提高可见性
Billing information , Logistics Cost, Order Fulfillment Accuracy, Process Procedure
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IoT-based Fleet Intelligence Innovation
Speed to market is precious for DRVR, a rapidly growing start-up company. With a business model dependent on reliable mobile data, managers were spending their lives trying to negotiate data roaming deals with mobile network operators in different countries. And, even then, service quality was a constant concern.
Digitize Railway with Deutsche Bahn
To reduce maintenance costs and delay-causing failures for Deutsche Bahn. They need manual measurements by a position measurement system based on custom-made MEMS sensor clusters, which allow autonomous and continuous monitoring with wireless data transmission and long battery. They were looking for data pre-processing solution in the sensor and machine learning algorithms in the cloud so as to detect critical wear.
Cold Chain Transportation and Refrigerated Fleet Management System
1) Create a digital connected transportation solution to retrofit cold chain trailers with real-time tracking and controls. 2) Prevent multi-million dollar losses due to theft or spoilage. 3) Deliver a digital chain-of-custody solution for door to door load monitoring and security. 4) Provide a trusted multi-fleet solution in a single application with granular data and access controls.
Airport SCADA Systems Improve Service Levels
Modern airports are one of the busiest environments on Earth and rely on process automation equipment to ensure service operators achieve their KPIs. Increasingly airport SCADA systems are being used to control all aspects of the operation and associated facilities. This is because unplanned system downtime can cost dearly, both in terms of reduced revenues and the associated loss of customer satisfaction due to inevitable travel inconvenience and disruption.
Vehicle Fleet Analytics
Organizations frequently implement a maintenance strategy for their fleets of vehicles using a combination of time and usage based maintenance schedules. While effective as a whole, time and usage based schedules do not take into account driving patterns, environmental factors, and sensors currently deployed within the vehicle measuring crank voltage, ignition voltage, and acceleration, all of which have a significant influence on the overall health of the vehicle.In a typical fleet, a large percentage of road calls are related to electrical failure, with battery failure being a common cause. Battery failures result in unmet service agreement levels and costly re-adjustment of scheduled to provide replacement vehicles. To reduce the impact of unplanned maintenance, the transportation logistics company was interested in a trial of C3 Vehicle Fleet Analytics.
IoT Based Asset Tracking System
The existing system used by the customer could only track a few thousand assets and was able to generate only a few standard set of reports. As the number of assets tracked grew exponentially, the system started to break at the seams. The Tracking devices were from different manufacturers following different protocols. There was no proper integration among the devices to send instant alerts. There are thousands of tracking devices spread across multiple geographies, that are moving. The configuration and troubleshooting of these devices incurred heavy costs, which was a logistics challenge. The existing system did not provide sophisticated Analytics, Business Intelligence and Insights from the data