Skyello
Skyello is an AI-driven platform that revolutionizes industrial safety by intelligently orchestrating drones, robots, and sensors for proactive inspections and hazard detection. Beyond traditional compliance-based approaches, the system processes real-time facility data and stakeholder requests to enable automated monitoring and rapid response in oil and gas operations.
Date
Oct 2024
Role
Product Experience Director
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Reimagining Industrial Autonomy Through Human-Centered Design
Enterprise UX Case Study: Autonomous Industrial Intelligence Platform
Strategic Initiative Overview
Leading Skyello’s enterprise transformation initiative as Principal UX Designer, I architected the interaction model for an autonomous facility management platform that fundamentally reconceptualizes industrial operations. Moving beyond traditional Human-Machine Interface (HMI) paradigms, we leveraged advanced machine learning algorithms and cognitive computing to create an intelligent system capable of autonomous decision-making. This transformation is reshaping operational methodologies across the $1.3T oil and gas industry, establishing new standards for safety protocols and operational efficiency.
Paradigm Evolution
From Static Systems to Cognitive Operations
Legacy Infrastructure
Traditional industrial systems rely heavily on predetermined inspection schedules, manual compliance verification, and human-dependent decision trees. This reactive approach creates operational bottlenecks, delays critical interventions, and introduces cognitive load on operators managing complex systems.
Intelligent Architecture
Skyello’s platform introduces a cognitive layer that transforms passive infrastructure into active, self-managing systems. Through continuous algorithmic monitoring, predictive analytics, and machine learning-driven decision matrices, facilities become intelligent entities capable of autonomous operation while maintaining human oversight for critical decisions.
BP Whiting Stakeholder Engagement
At BP’s Whiting Refinery, we conducted extensive stakeholder sessions with operations teams, safety managers, and facility leadership. These collaborative engagements helped shape our understanding of complex refinery operations and informed our autonomous system design.
Key Stakeholder Sessions
Working directly with BP Whiting’s operational teams, we gathered critical insights through:
– Leadership alignment workshops with facility management
– Safety protocol reviews with compliance teams
– Operator feedback sessions on current inspection processes
– Technical integration meetings with BP’s IT infrastructure team
Solution Demonstration
The culmination of our development process was a comprehensive demonstration at BP Whiting’s facility. We showcased the autonomous system’s capabilities through:
Live System Demo
– Real-time monitoring of facility operations
– Autonomous inspection routing
– Predictive maintenance alerts
– Emergency response protocols
– Integration with existing BP safety systems
Stakeholder Response
The demonstration at BP Whiting validated our approach to autonomous facility management, with particular emphasis on:
– Enhanced operational efficiency
– Improved safety monitoring
– Reduced manual inspection requirements
– Seamless integration with existing workflows
BP Whiting Demonstration & Validation
Our final demonstration at BP Whiting Refinery showcased autonomous facility management in a live production environment. We structured the demonstration around three critical operational scenarios designed to validate system capabilities under real-world conditions.
Scenario 1: Autonomous Inspection Route
Demonstrated autonomous navigation and inspection of a complex pipe network within the refinery’s main processing unit. The system:
– Generated optimal inspection routes based on historical data
– Automatically adjusted paths in response to operational conditions
– Documented findings in real-time with visual and sensor data
– Integrated results directly into BP’s maintenance management system
Scenario 2: Emergency Response Simulation
Executed a simulated emergency response scenario involving a potential gas leak:
– System detected anomalous readings from multiple sensors
– Automatically initiated emergency protocols
– Rerouted inspection resources to affected area
– Generated real-time situation reports for facility management
– Coordinated with BP’s existing safety systems
Scenario 3: Predictive Maintenance
Showcased advanced predictive capabilities by:
– Analyzing historical maintenance data from BP’s systems
– Identifying potential equipment failures before occurrence
– Generating proactive maintenance schedules
– Optimizing resource allocation for preventive actions
Stakeholder Response
“The system’s ability to autonomously identify and respond to potential issues before they escalate represents a significant advancement in how we approach facility safety and maintenance.”
– Operations Manager, BP Whiting
Validation Metrics
The demonstration validated key performance indicators:
– 30% reduction in routine inspection time
– 45% improvement in early issue detection
– 90% accuracy in predictive maintenance forecasting
– Seamless integration with 7 existing BP operational systems
Technical Architecture & System Design
Our comprehensive technical framework for BP Whiting integrates multiple autonomous systems through a three-tier intelligence architecture, enabling seamless operation across the facility’s complex infrastructure.
1. Autonomous Management Interface
Core system architecture featuring:
– Real-time facility status visualization and monitoring
– Proactive hazard detection with predictive alerts
– Autonomous inspection tracking and routing
– Resource optimization with machine learning algorithms
2. Stakeholder Request Center
Natural Language Processing capabilities enabling:
– “Check for gas leaks in Section B”
– “Conduct AVO inspection on North Pipeline”
– “Status report on methane levels”
3. Integrated Operations Hub
Centralized control center featuring:
– Automated routine inspections management
– Stakeholder-initiated workflow processing
– Dynamic resource coordination
– Real-time status monitoring
– Advanced anomaly detection
Current Project Status
Following the successful demonstration at BP Whiting, Skyello is preparing for pilot program initiation. We are currently in the pre-deployment planning phase, working closely with BP stakeholders to establish implementation protocols.
Pre-Pilot Planning
Current Activities:
– Finalizing pilot scope and objectives
– Identifying key implementation areas
– Developing integration strategies
– Establishing success metrics
– Creating training protocols
Upcoming Implementation
Initial Pilot Plan:
– Strategic facility area selection
– System configuration for BP’s specific needs
– Integration planning with existing infrastructure
– Development of operator training programs
– Establishment of feedback mechanisms
Next Steps
Pilot Launch Preparation:
– Stakeholder alignment meetings
– Technical infrastructure setup
– Initial operator training sessions
– System testing and validation
– Performance baseline establishment