• RBI Assessment (Pipelines & Piping): Execute comprehensive Risk-Based Inspection assessments for critical energy assets. Perform pipeline sub-segmentation to isolate segments based on damage mechanism susceptibility and define corrosion circuits/loops and inventory groups for facility piping.
• Asset Life Analysis: Conduct Fitness-for-Service (FFS) and Remaining Life Assessments (RLA) to evaluate the structural integrity of aging equipment and optimize inspection intervals.
• Corrosion Mitigation: Design Impressed Current Cathodic Protection (ICCP) systems for buried parallel pipelines, utilizing COMSOL Multiphysics for advanced numerical modelling and interference analysis.
• Project: Digital Workflow Innovation (Project Lead)
  • Automated Sub-Segmentation: Developed a Python and Excel-based methodology to automate pipeline sub-segmentation using UT and Walkthrough inspection data. Increased assessment efficiency by 300% compared to manual processing.
  • Deep Learning P&ID Analyzer: Engineered an OCR-based system to automate text and tag extraction from A0/A1 P&IDs. Reduced manual diagram analysis time from 4 hours to 30 minutes (85% reduction). https://youtu.be/fgEFr8aQgbk
    • Roadmap: Architecting a future module for automated symbol and line detection to enable the "one-click" generation of corrosion circuits, inventory groups and other analysis process involving P&ID.

• Standard Compliance: Ensured all composite piping products (FRP/GRP) met 100% compliance with internal company protocols and international engineering standards, including ASTM, ISO, API, and ASME B31.3.

• Dimensional & Material Inspection: Conducted rigorous inspections of product dimensions, material performance, and fabrication procedures, utilizing AutoCAD to verify accuracy against design specifications.

• Root Cause Analysis (RCA): Spearheaded technical investigations into product defects and customer complaints, identifying systemic failures and implementing corrective actions that reduced persistent manufacturing defect rates from 5% to 3% in one month.

• Project: Quality Inspection Digitalization |

  • Challenge: Legacy quality inspection processes were entirely paper-based, causing data bottlenecks, high error rates, and a lack of real-time visibility for management.

  • Solution: Architected a full-stack digital solution utilizing the Microsoft Power Platform. I designed a custom Power App for field inspectors, automated data transformation via Power Query, and centralized reporting through Power BI.

  • Key Outcome: Transformed a reactive quality department into a data-driven environment. This project eliminated clerical inefficiencies, enabled simultaneous data collection for root-cause analysis, and provided senior leadership with live dashboard monitoring of floor-level compliance.

• Conducted metallurgy and materials characterization practicum sessions including mechanical testing and microstructure analysis of metals — materials directly relevant to piping and pressure vessel service environments.
• Supervised 20+ students per session through experimental procedures with strict adherence to safety and laboratory protocols.

• ASIIN International Accreditation
• Thesis: Effect of Temperature and Times of Aging on Hardness and Microstructure of Aluminum Alloy 7075
  • Relevant Coursework: Metallurgy, Materials Characterization, Corrosion (API 571), Failure Analysis, Auto CAD/SolidWorks.
• Project: Automated Motion-Detection & Response Prototype (ITB) | May – June 2020
  • Challenge: Addressed chronic vehicle congestion and unauthorized idling at the Dayang Sumbi gate by developing an automated, non-violent means.
  • Technical Action: https://youtu.be/aQW6wBEDbIo
    • System Integration: Engineered a prototype combining computer vision (CV) with embedded systems, featuring an Arduino-controlled 3-axis servo mechanism.
    • Advanced Logic: Developed a real-time motion-tracking algorithm using Processing IDE and pixel-data analysis.
    • Hardware Optimization: Successfully bypassed Arduino hardware limitations by offloading complex computer vision processing to a laptop-microcontroller interface, ensuring high-speed tracking and response.
    • Prototyping: Designed and assembled a 3-axis response mechanism on a custom-built chassis to execute targeted signalling.
  • Impact: Successfully demonstrated a functional application of computer vision to solve urban infrastructure challenges, proving the viability of automated, low-cost solutions for real-time traffic management.

o   Deep Learning P&ID Analyzer: Engineered an OCR-based system to automate text and tag extraction from A0/A1 P&ID and PFD documents in PDF format. Reduced manual diagram analysis time from 4 hours to 30 minutes (85% reduction).

o   Roadmap: Architecting a future module for automated symbol and line detection to enable the "one-click" generation of corrosion circuits, inventory groups and other analysis process involving P&ID.

o   Challenge: Legacy quality inspection processes were entirely paper-based, causing data bottlenecks, high error rates, and a lack of real-time visibility for management.

o   Solution: Architected a full-stack digital solution utilizing the Microsoft Power Platform. I designed a custom Power App for field inspectors, automated data transformation via Power Query, and centralized reporting through Power BI.

o   Key Outcome: Transformed a reactive quality department into a data-driven environment. This project eliminated clerical inefficiencies, enabled simultaneous data collection for root-cause analysis, and provided senior leadership with live dashboard monitoring of floor-level compliance.

o   Challenge: Addressed chronic vehicle congestion and unauthorized idling at the Dayang Sumbi gate by developing an automated, non-violent means.

o   Technical Action:

§  System Integration: Engineered a prototype combining computer vision (CV) with embedded systems, featuring an Arduino-controlled 3-axis servo mechanism.

§  Advanced Logic: Developed a real-time motion-tracking algorithm using Processing IDE and pixel-data analysis.

§  Hardware Optimization: Successfully bypassed Arduino hardware limitations by offloading complex computer vision processing to a laptop-microcontroller interface, ensuring high-speed tracking and response.

§  Prototyping: Designed and assembled a 3-axis response mechanism on a custom-built chassis to execute targeted signalling.

o   Impact: Successfully demonstrated a functional application of computer vision to solve urban infrastructure challenges, proving the viability of automated, low-cost solutions for real-time traffic management.