BHC3 Reliability
Prevent process failure in filtration
BHC3 Reliability
Prevent process failure in compression
BHC3 Reliability
Prevent process failure in power generation
Take Early Action to Identify and Prevent Anomalies
BHC3 Reliability™ is a comprehensive software solution that provides reliability engineers, process engineers and maintenance managers with AI-enabled insights to address process and equipment performance risks. The application identifies anomalies, provides prioritized alerts to operators, recommends prescriptive actions, and enables collaboration across the enterprise. The application delivers value through increased revenue from recovered production, reduced costs of unplanned downtime, extended equipment life, and improved safety in operations.
Preventing Petrochemical Process Failure Using AI
Features
System-of-systems AI approach
Leverage AI to identify equipment and process issues that impact system-level health and operational performance. Understand how individual tags across
independent systems are related to overall system health. Assess system and subsystem health trends over varying time intervals across configurable risk indicators.
Unsupervised anomaly detection
Leverage sophisticated deep learning and machine learning technology to identify anomalies in process flow and equipment performance. Respond to risks and anomalies in process flow and equipment performance, along with failure process upset predictions.
Root cause identification
Prescribe root cause remediation to guide reliability engineers to enable faster, more consistent, and traceable root cause investigations.
Continuous learning
Continuously train and improve AI models based on new data and user feedback. Increase the accuracy of failure mode recommendations and anomaly detection alerts over time.
Prioritized alerting
Focus operations on prioritized alerts and reduce the number of unnecessary alerts through AI-enabled detection and categorization of process risks. Investigate and take action using AI-recommended failure mode assessments for each identified risk.
Visualization across process equipment
View and traverse unified process data at the aggregate level or drill down to understand individual equipment performance. Aggregate process data to view all relevant data for interdependent process equipment.
Seamless integration with existing tools
Aggregate process data to view all relevant data for interdependent process equipment. Understand how tags from independent systems correlate to distinct process steps. Collaborate across the enterprise with case management tools, including data investigations, messaging, user tagging, file upload, and external messaging (e.g., email or text).
Benefits
Improve
Improve production recovery with early identification, prioritization, and resolution of equipment and process risks.
Extend
Extend equipment life by improving operating conditions and turnaround decisions with data-driven history and risk predictions.
Reduce
Reduce unplanned downtime by proactively addressing process and equipment reliability issues. Arm operators with prescriptive actions to change operating conditions and reduce upset risks.
Improve
Improve safety with reduced high-risk emergency repairs.
Case Studies
BHC3 Reliability Data Sources
The application leverages the BHC3 AI Suite to integrate terabyte-scale data from disparate sources such as sensor networks, enterprise systems, and data historians. BHC3 Reliability uses unsupervised and supervised machine learning algorithms to predict system health of processes and process equipment. Processes monitored include off-shore oil platforms, downstream refineries, and connected field equipment.
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Proven results in weeks, not years
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