Engineering Intelligence Unlocked

Our Client

Our client is a major American multinational oil and gas corporation. As one of the world’s largest integrated providers of energy, lubricants, and chemical solutions, the client operates on a global scale with a strong emphasis on delivering sustainable and forward-looking energy innovations.

Industry Pulse: Why Transformation Became Urgent

The oil and gas industry is undergoing a rapid digital transformation driven by the need for operational efficiency, regulatory compliance, and sustainability. The increasing complexity of global operations, coupled with fragmented legacy systems and inconsistent data taxonomies, has made it challenging for enterprises to maintain visibility and control over critical equipment data. Regulatory pressures across regions demanded robust data governance and traceability. Additionally, the rise of intelligent automation, immersive visualizations, and high-fidelity data models has created a strategic imperative for modernization. These dynamics compelled the client to initiate modernization of the equipment data ecosystem by implementing P&ID (Piping and Instrumentation Diagrams) digitization solutions. This initiative aimed to digitize process schematics, improve data quality, enable scalable and intelligent data governance across multiple sites, and deliver a sustainable Equipment Data Product.

Challenges in the Shadows: What Held Operations Back

The clients’ IT engineering teams, including data management specialists, chemical engineers, and operational heads, faced the following challenges:

• Disparate taxonomies and material definitions across systems Multiple systems used inconsistent naming conventions for the same materials, resulting in duplication and confusion in trading and planning workflows.
• Manual ingestion of chemical specifications from semi-structured/unstructured sources Analysts had to manually extract critical chemical data from PDFs and Excel files, which increased their effort and risk of errors.
• Lack of a unified hierarchy for trading and manufacturing specifications Absence of a global classification made it difficult to align refinery outputs with trading needs, impacting scheduling and compliance.
• Compliance with regional data governance standards Varying regulations across the EU, NA, and AMP required tailored data governance, lineage tracking, and secure access controls.
• Digitization of over 100,000 P&IDs with inconsistent drafting standards P&IDs varied in complexity and quality, requiring both algorithmic and manual intervention for accurate data extraction.
• Scaling and training of 50+ chemical engineers within 3 months A POD-based model enabled rapid onboarding and upskilling through structured training and hands-on diagram solving.
• Manual intervention was required for symbol recognition and asset connections Non-standard symbols and complex connections often bypassed automation, demanding expert review and correction.

LTM’s Solution

The initiative aimed to digitize P&IDs from refineries, chemicals, and mid-stream. The P&ID digitization solutions effort focused on extracting valuable data related to equipment, sensors, analyzers, and instruments using StudioPro software. LTM was the execution partner, and Cerebre was the vendor partner chosen to digitize P&IDs using Studio Pro.

• Comprehensive Methodology for Equipment Data Modernization : A structured approach was adopted to ensure consistent delivery quality across diverse sites, especially when managing unknown symbols. Site-specific documentation was developed to address unique challenges at each location.
• Unified Solving Guidance Document : A centralized reference was created by consolidating insights from all participating sites, enabling standardization and best practices in the digitization process.
• Integration with PlantGraph for System Classification : Digitized P&ID data was transferred to PlantGraph and used for system and sub-system classification, ensuring equipment and site standardization in line with ISO 14224. PlantGraph also provides a connected view of the facility.
• POD-Based Delivery Model : LTM implemented a POD-based model with super users and QA teams to streamline execution and maintain quality.
  • Studio Pro Workflow for Solving Diagrams : A 9-step solving process was designed in Studio Pro to extract tags and metadata from P&IDs, supported by symbol recognition, flow analysis, and asset connection mapping.
  • Tiered QA Framework : A 10-step QA process was established, incorporating automated health checks, tiered validation rules, and feedback loops to ensure high accuracy and continuous improvement.
• Training and Support Enablement : Extensive training was conducted via Zendesk, Jira office hours, and workshops to upskill teams and ensure consistent delivery.
• Productivity Tracking and Optimization : Solving efficiency improved from 2 to 5 P&IDs per person per day through process standardization, training, and tool enhancements, reducing turnaround time and operational costs.

Business Benefits

The P&ID digitization solutions initiative delivered significant operational and quality improvements across the client’s global sites. By combining structured processes, intelligent tooling, and expert-led execution, LTM enabled scalable delivery, accelerated turnaround times, and measurable gains in data accuracy and productivity.

• Digitized over 50,000 P&IDs from upstream, mid-stream, refinery, and chemicals sectors within a span of 1.5 years, leveraging the expertise of more than 50 core chemical engineers.

• Quality improvement from 25% to 50% over 6 months through tiered QA rules, feedback loops, and recorded training sessions.

• 8+ tool enhancements were identified and proposed by LTM and Cerebre, as a software vendor, implemented them, including symbol detection upgrades, undo/redo features, and regex setting transfers.

• QA comments per diagram reduced from 16.7 to 8.3, indicating a 50% improvement in diagram quality.

• Solving time per diagram for a very high complexity P&ID reduced from 11.4 hours to 4 hours, a 65% improvement through process optimization and tool improvement.

• QA time per diagram reduced from 2.75 hours to 0.9 hours, indicating ~67% improvement, with major gains in symbol and line type validation.

• Achieved a 75% reduction in manual effort and approximately USD 150K in annual savings.

Business Value of Engagement

• Streamlined Data Traceability : Centralized equipment data foundation reduced manual effort and enabled faster, more accurate traceability and fleet analytics.
• 360° Equipment Visibility : Unified data view empowered improvements in strategy, routine maintenance, and turnaround planning.
• Improved Data Quality & Accessibility : Contextualized, discoverable, and standardized data enhanced decision-making across business processes and technologies.

Conclusion

The successful implementation of Equipment Data Products marks a significant leap in the client’s digital transformation journey. As part of the broader equipment data ecosystem modernization effort, LTM harmonized disparate data sources, automated complex ingestion processes, and established robust governance frameworks. This enabled the client to unlock operational efficiencies, reduce costs, and improve data quality across global sites.