About

Cross-disciplinary engineer (ITB) who consistently turns complex, real-world problems into efficient, measurable solutions — by combining rigorous engineering fundamentals with hands-on digital and data technology. Rather than treating engineering and technology as separate disciplines, I integrate both to design solutions that neither a pure engineer nor a pure developer could build alone. In practice, this has meant applying deep learning and computer vision to eliminate 85% of manual technical review time, building full-stack data platforms on Microsoft Power Platform to convert paper-based industrial workflows into live management dashboards, and developing Python-based automation that increased engineering assessment efficiency by 300% — all initiated independently, on live projects, without prior templates. Certified across three domains — Data Analytics (Google), Project Management (Google), and AI Fundamentals (Microsoft Azure) — and formally trained as a Materials Engineer at ITB, I bring a rare combination: the structured analytical thinking of a traditional engineer, the technical fluency of a data practitioner, and the initiative of someone who builds solutions rather than waits for them.

Experience

Jr. RBI Engineer at Radiant Utama Interinsco

Jakarta

  • 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.

Piping Quality Inspector (Management Trainee) at Future Pipe Industries

Banten

  • 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.

Laboratory Assistant at Institut Teknologi Bandung (ITB)

Bandung

  • 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.

Education

Institut Teknologi Bandung (ITB)

Bachelor of Engineering in Materials Engineering

GPA: 3.23 / 4.00

  • 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.

Skills

Piping & Integrity

P&ID Reading & InterpretationPipe Stress Analysis (PASS/START-PROF)Piping Material Compliance (FRP/GRP)Corrosion & Damage Mechanism Analysis and simulation (COMSOL Multiphysics)Risk-Based Inspection (RBI)Root Cause Analysis (RCA)Remaining Useful Life (RUL)

Digital & Automation

Technical Drawing (e.g. AutoCAD, Solid Works, Free CAD)PythonDeep Learning & OCR (Computer Vision)Power BI & Power AppsExcel Automation & Power QuerySQL & Data Analysis

Projects

P&ID Intelligent Extraction Tool for RBI Assessment

Python | EasyOCR | TrOCR | Deep Learning | VLM

Situation

Risk-Based Inspection (RBI) assessments require engineers to manually review large-format P&ID and PFD documents (typically A0/A1 size) to identify and number all piping equipment, define corrosion circuits, and establish inventory groups. This manual process is cognitively demanding, time-consuming, and highly prone to human error — especially across interconnected, multi-sheet P&ID sets common in large plant facilities.

Task

To address this bottleneck, I set out to develop an intelligent P&ID analysis tool capable of automating the extraction and interpretation of the three fundamental components of any P&ID/PFD: text, symbols, and lines. The end goal was a system that could:

  • Automatically identify and locate all equipment and piping tags

  • Recognize instrument and equipment symbols to auto-generate inventory groups

  • Trace process lines to support corrosion circuit creation

  • Serve as a general-purpose P&ID analysis platform beyond RBI use cases

Action

I developed a Python-based application integrating OCR engines (EasyOCR, TrOCR) and deep learning/Visual Language Models (VLM) for symbol recognition. Key engineering challenges and solutions included:

  • PDF format limitation — Converted PDF drawings to high-resolution images (PNG) to enable compatibility with OCR and vision models

  • Image scale problem — P&ID images often exceed 10,000 px in dimension while tag text occupies only 10–20 px, exceeding model input limits. I designed a sliding window mechanism with overlapping tiles to process large images in smaller, overlapping segments, eliminating blind spots at tile boundaries

  • Symbol diversity — P&ID standards include hundreds of symbol variants. I curated a labeled dataset covering primary symbols (valves, flanges, instruments, etc.) and trained a deep learning model for initial recognition, with plans to expand coverage as compute resources allow

Result

  • Text extraction module: Successfully deployed — the tool accurately extracts every equipment and piping tag along with its coordinates, enabling instant location of any item within a P&ID without manual searching, making the equipment numbering step in RBI assessments trivial

  • Symbol extraction module: Functional for primary symbols (valves, flanges, instruments); model accuracy improvements are ongoing to cover the full symbol library

  • Line extraction module: Planned as the next development phase, to be initiated after symbol recognition reaches production-level accuracy

The tool has significantly accelerated the RBI assessment workflow, reducing both the time and cognitive load required during the P&ID review stage — a process that previously required hours of manual interpretation per document.

Quality Inspection Digitalization

Root Cause Investigation & Defect Reduction

  • Identified and investigated a persistent curing defect on a Glass Reinforced Epoxy (GRE) production line, in which discrete fibre glass sections exhibited incomplete resin curing, while adjacent sections remained unaffected.

  • Formulated a technical hypothesis attributing the defect to an imbalanced or non-uniform application of the binding agent (binder) along the fibre glass substrate; designed a Loss on Ignition (LOI) test methodology to quantify binder distribution across fibre glass rolls, which were sectioned into 50 cm specimens for systematic evaluation.

  • Proposed and implemented an adjustment to the resin mixing process, elevating the mixing temperature to enhance resin viscosity and substrate wettability; this intervention reduced the monthly defect occurrence rate from 5% to 3% within the trial period, while maintaining full compliance with company product standards.

Quality Inspection Digitalisation Project

  • Identified a critical operational gap: all production, quality inspection, and compliance records were maintained in paper-based format, rendering parameter tracking and data-driven decision-making impractical.

  • Proposed and led the design and implementation of a digital quality inspection system within the Microsoft Power Platform ecosystem, comprising:

    • A Power Apps mobile application for field inspectors to capture real-time inspection data, including defect details and photographic evidence.

    • A SharePoint List as the primary data repository (selected as a cost-effective alternative to Microsoft Dataverse for the project's early-stage phase).

    • Microsoft Power Query (Excel) for automated data transformation and cleansing of raw inspection records.

    • A Power BI Dashboard for live monitoring and visualization of quality metrics.

    • A Power Automate workflow to programmatically generate and archive standardized inspection reports directly from the Power Apps interface.

  • Conducted a one-month pilot trial; the system successfully captured 100% of quality defect records, the dashboard was operational, and the automated report generation function performed without failure.

  • Planned subsequent integration with the production division to enable cross-functional, data-driven analysis of process parameter adjustments — however, this phase was not completed due to a transition to a new workplace.

Automated Motion-Detection & Response Prototype (ITB)

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.

Testimonials

“1. Kompetensi Teknis dan Inovasi Saudara Aris telah menunjukkan kemampuan teknis yang luar biasa dalam pengembangan teknologi informasi untuk mendukung proses Quality Control (QC). Beliau berhasil membuat aplikasi QC menggunakan Power Apps yang signifikan meningkatkan efisiensi pelaporan QC di perusahaan. Inovasi ini menunjukkan kemampuan problem-solving dan adaptasi teknologi yang sangat baik. 2. Pengalaman Praktis dan Hands-on Sebagai Jr RBI Engineer, Saudara Aris memiliki pengalaman hands-on yang mendalam terhadap seluruh proses Quality Control. Pemahaman praktis yang komprehensif ini menjadi fondasi kuat untuk pengembangan kompetensi lebih lanjut melalui pendidikan tinggi. 3. Kemampuan Analitis dan Pemecahan Masalah Dalam setiap project yang ditangani, Saudara Aris selalu menunjukkan kemampuan analitis yang tajam dalam mengidentifikasi area improvement dan mengimplementasikan solusi yang efektif. Hal ini tercermin dari keberhasilannya dalam mengoptimalkan proses QC melalui digitalisasi. 4. Dedikasi dan Etos Kerja Beliau menunjukkan dedikasi tinggi dalam setiap tugas yang diberikan, selalu berusaha memberikan hasil terbaik dan tidak ragu untuk belajar hal-hal baru demi kemajuan perusahaan dan pengembangan diri. 5. Potensi Kepemimpinan Saudara Aris memiliki kemampuan komunikasi yang baik dan sering menjadi rujukan rekan kerja dalam hal teknis. Ini menunjukkan potensi kepemimpinan yang akan sangat bermanfaat untuk masa depan. 6. Visi Pengembangan Industri Dengan background engineering dan pengalaman di industri, Saudara Aris memiliki visi yang jelas tentang bagaimana pendidikan lanjutan dapat berkontribusi pada pengembangan industri nasional, khususnya dalam bidang quality assurance dan risk-based inspection. ”

Ivan Eka — Plant Manager