Cisco Case Studies Cisco Kinetic for Oil and Gas: Refineries and Plants
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Cisco Kinetic for Oil and Gas: Refineries and Plants

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Cisco Kinetic for Oil and Gas: Refineries and Plants - Cisco Industrial IoT Case Study
Functional Applications - Remote Monitoring & Control Systems
Sensors - Gas Sensors
Sensors - GPS
Oil & Gas
Business Operation
Leakage & Flood Monitoring
Personnel Tracking & Monitoring

The plant manager and safety teams needed a solution that provided near real-time visibility of gas detection and personnel location, with easy to understand visualization and alerting dashboards. This would enable them to improve productivity through decreasing the time taken to start work, optimize evacuation route planning, and to meet critical staff safety and compliance goals.

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An oil and gas major had limited visibility into gas leaks in the refinery as their sensors were installed in fixed locations. They also had no visibility into the location of personnel, raising potential safety issues as they couldn’t see where wor
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Undisclosed
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Engineers are equipped with mobile 4-way gas detectors, supplemented by fixed wireless gas detectors in key locations. The plant is covered by a pervasive industrial wireless MESH. Real-time gas monitoring measurements information is sent from the gas detectors, across the wireless infrastructure, to the Cisco Mobility Services Engine (MSE). 

Cisco Kinetic receives the data, processes it using customer defined policies and key performance indicators (KPIs), and turns the data into actionable insight via a near real-time gas monitoring and detection risk map in an operational dashboard. The dashboard is viewable by operations, maintenance and safety teams, and can be extended securely to the enterprise. 

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Fast, easy deployment, with reduced deployment costs.

Optimized equipment performance leading to increased production.

Intuitive and easy to understand multi-vendor operational information dashboard, providing a vendor agnostic way to connect and monitor assets.

Quantifiable benefits with the company realizing annual $1.5M USD savings due to performance monitoring, process condition optimization, and predictive maintenance.

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