AI-Powered Asset Integrity and Performance Management: From Predictive Diagnostics to Prescriptive Intelligence

Overview

INGENERO X is an AI-driven industrial platform purpose-built to enhance asset integrity and performance in petrochemical operations. The platform comprises four interoperable modules—OptimaX (optimization), AlertX (predictive anomaly detection), AnalyticX (no-code analytics), and NetZ (sustainability management)—that unify plant data into actionable intelligence. With seamless integration into plant historians, DCS, and ERP systems, INGENERO X enables real-time asset health monitoring, early fault detection, and prescriptive operational guidance. From identifying degradation trends in rotating equipment to forecasting heat exchanger fouling or predicting polymer loop upsets, INGENERO X empowers engineers to prevent failures before they occur. Its ML-powered engines not only detect drift and deviations but also prescribe corrective actions through contextual parameter guidance—enabling better uptime, fewer shutdowns, and extended asset life. With an intuitive interface, flexible deployment, and measurable ROI, INGENERO X transforms asset management from reactive to predictive—and from predictive to prescriptive.

Purpose

Petrochemical facilities depend on asset reliability to maintain safety, productivity, and profitability. Yet many still operate in reactive or time-based maintenance modes—missing early signs of failure or inefficiency. INGENERO X addresses this gap through predictive and prescriptive analytics designed specifically for high-value assets in complex process environments. It aggregates operational data, applies ML models to forecast failures, and delivers engineer-friendly recommendations to mitigate emerging risks. With AlertX, operators gain anomaly alerts contextualized with process variables, while AnalyticX enables chemical engineers to build asset-health models—no coding required. These capabilities help avoid unplanned outages, reduce maintenance costs, and ensure long-term integrity of equipment like compressors, exchangers, and polymer loops. More than just alerts, INGENERO X drives prescriptive action through guided setpoint recommendations and reliability insights, turning asset data into operational foresight. The platform equips maintenance and reliability teams with the tools to act early, act smart, and act with confidence.

Method

INGENERO X is a modular platform that connects to real-time data sources such as SCADA, DCS, and historian systems (e.g., OSI PI, Honeywell PHD, Aspen IP.21, etc,) to deliver predictive and prescriptive insights across critical equipment. Key modules include:

1. AlertX – Predictive Asset Monitoring

• Continuously analyzes 100,000+ process tags from critical rotating and static equipment.
• Applies ML algorithms for drift, spike, and pattern detection across vibration, temperature, flow, and pressure signals.
• Features customizable alert thresholds, noise suppression, and grouping logic to avoid alarm fatigue.
• Detects early failure indicators (e.g., bearing wear, exchanger fouling) and supports root cause diagnostics.
• Directly integrates with maintenance workflows, enabling faster intervention and minimized downtime.

2. AnalyticX – No-Code Predictive & Prescriptive Analytics

• Engineers can create soft sensors and asset failure models using historical and real-time data—without writing code.
• Enables forecasting of failure windows, degradation rates, and process-performance correlation.
• Prescriptive analytics engine provides “next best actions” based on historical correction patterns and real-time conditions.
• What-if simulation tools allow reliability engineers to evaluate intervention scenarios (e.g., changing reboiler duty or feed composition) to prevent asset stress.

3. OptimaX – Optimization for Asset Longevity

• Provides live parameter tuning guidance that optimizes performance without compromising equipment health.
• Uses multi-variable AI models to recommend operating envelopes that balance output with reliability.
• Helps extend maintenance cycles by reducing stress conditions through real-time setpoint recommendations.

4. NetZ – Emissions & Energy Accountability

• Tracks Scope 1 & 2 emissions tied to asset operations.
• Ensures asset integrity and energy efficiency goals align under global compliance frameworks (ISO 14064, GHG Protocol).
• Supports decision-making where asset condition affects sustainability outcomes.

Platform Features:

• Role-based dashboards for reliability, operations, and ESG teams.
• Secure architecture with audit trails, encryption, and mobile/web access.
• Integration-ready for CMMS and ERP systems to close the loop on asset management.

Results

Across deployments in petrochemical complexes, INGENERO X has delivered the following asset integrity and reliability outcomes:

Predictive Reliability (via AlertX)

• 40% reduction in unplanned shutdowns for rotating machinery and polymer loops.
• 60–70% faster troubleshooting during stress events, enabling earlier corrective actions.
• $2M+ annual cost avoidance from predictive maintenance and extended asset lifespan.
• 90% reduction in false positives, ensuring focus on real risks.

Prescriptive Actions (via OptimaX + AnalyticX)

• Engineers acted on real-time parameter guidance to avoid conditions leading to exchanger fouling and reactor imbalance.
• 3–7% increase in throughput with no additional asset stress by optimizing within safe KPI bands.
• ML-guided recommendations led to 5–10% energy efficiency gains without compromising integrity.

Soft Sensor Models & Forecasting (via AnalyticX)

• 30% faster development of asset health models (e.g., for melt index, viscosity, or exchanger fouling indices).
• 50% fewer unscheduled shutdowns linked to heat duty anomalies and unstable flow rates.
• Over $1M/year in savings due to reduced lab testing and proactive anomaly corrections.

Cultural & Adoption Benefits

• Reliability engineers gained hands-on control of AI models without IT dependency.
• Adoption >90% across 3 facilities within 4 months due to intuitive UX.
• Executive teams attributed ROI gains to measurable asset risk reduction and downtime avoidance.

Conclusion

INGENERO X redefines asset integrity management in petrochemical plants by bridging predictive diagnostics with actionable prescriptions. Through AI-powered modules like AlertX and AnalyticX, it enables early detection of asset risks and guides engineers with contextual responses—not just insights, but instructions. OptimaX closes the loop by adjusting parameters in real time to reduce stress on key assets, while NetZ connects asset health with energy and emissions accountability. Together, they form a platform that transforms how maintenance, operations, and reliability teams manage plant assets—smarter, faster, and more sustainably. For organizations seeking not just visibility, but predictive control and prescriptive intelligence, INGENERO X is the next step in digital transformation of asset integrity.