Twin Sight - Intuitive and User-Friendly Visualization Tool
A modern rapid prototyping approach to operational dashboard authoring, accelerating the adoption of AI-based anomaly detection, production optimization, and operation monitoring across all production sites. Offering fast, easy, and secure access to operational, engineering, and transactional real-time data, as well as semantic data, Twin Sight revolutionizes the way you visualize and analyze information in the industrial sector.
Challenge
Manufacturing and energy operators require real-time operational data, fully integrated with business asset metadata, to make better and faster data-driven business decisions without disrupting mission-critical plant operations. These decisions rely on insights derived from computationally intensive ML models across enterprise industrial assets. Modernizing legacy operational tools, applications, and systems is a foundational step to innovation, as plant infrastructure is built on a highly heterogeneous IoT infrastructure that lacks integration and ultimately limits the value extracted from data leveraging AWS cloud services capabilities.
What is Twin Sight?
EOT Twin Sight™ supports the visualization and reporting of large-scale analytics and machine learning (ML) models. The ML model results are embedded in the use-case driven modern, low-code, AI-powered visualization platform, enabling operational users to make data-supported decisions that drive operational efficiency across their enterprise. With Twin Sight™, industrial users can leverage the power of low-code AI-driven software to modernize asset information and data visualization, and rapidly create use-case specific visual dashboards, templates, and reports. Twin Sight's flexibility and ease of use allow individuals within the company to access enterprise-wide operational data through a self-service model and develop dashboards and reports tailored to their specific use cases and business needs.
A partial list of use cases where applying modern data science and machine learning across all operating assets yields the highest level of cost savings and efficiency gains includes:
Anomaly Detection:
- Equipment choking
- Leakage
- Erratic valves
- Blowout event
- Output
- Tank levels
- Frequencies
Optimizations:
- Cycle Optimization
- Pressure Optimization
- Frequency Optimization
