Hello I’m Pham Le Huu Dan

Investigating Root Causes of Longitudinal Crack on Section Steel

I undertook an in-depth project to investigate the root causes of Longitudinal Cracks in Beamblank steel materials – a critical defect that significantly impacts the quality of finished steel sections. During this project, I collected all relevant production data concerning instances of cracking, subsequently conducting a comparative analysis against batches of normal, defect-free products.

Utilizing advanced statistical methods such as quantitative statistics, ANOVA, and linear regression analysis with the aid of specialized software like Minitab and Excel 365, I meticulously analyzed the collected data. The analysis revealed that the potential causes of these vertical cracks were a discrepancy in chemical composition combined with a specific process error during production.

Based on these findings, I proposed a concrete solution involving adjustments to the chemical composition, aimed at preventing the recurrence of this defect. While this solution hasn't yet fully eradicated the vertical cracks, it has yielded significant progress in reducing the defect rate.

Carbon Inventory follow ISO14064 & 14067

I'm proud to have been a key member of the Greenhouse Gas (GHG) inventory team at POSCO YAMATO VINA STEEL JSC (PY Vina), a leading Vietnamese steel joint venture. This project adhered to stringent international standards: ISO 14064 (for organizational GHG reporting) and ISO 14067 (for product carbon footprint).

This was critical to POSCO Group's sustainable development strategy, affirming their commitment to environmental impact reduction and fostering a "Better World with Green Steel." The Product Carbon Footprint (CFP) study focused on identifying, evaluating, and minimizing total emissions across the product lifecycle.

In my role, I was primarily responsible for synthesizing complex production data from factory operations, including raw materials, energy consumption, and transportation. I calculated GHG emissions strictly following ISO methods. To ensure data accuracy and representativeness, I applied advanced statistical methods like descriptive statistics and linear regression to determine key values.

The inventory reports and calculations were subsequently audited and verified by BSI, confirming their reliability and compliance.

To optimize workflows and enhance efficiency, I proactively developed an automated calculation dashboard based on the initial framework. This tool streamlined data collection and processing, significantly reducing manual errors and enabling continuous, effective monitoring of emission performance.

Modern Slavery Statement Reporting

I served as a key member of the team responsible for drafting and submitting the Australia's Modern Slavery Statement. This is a mandatory and critically important requirement for our company to achieve SSA (Sustainable Steel Australia) certification, which is an essential permit for us to export steel to the Australian market.

In this project, I directly coordinated with various internal departments to collect, analyze, and verify all data related to our supply chain and internal operations. The primary goal was to ensure that all company processes strictly complied with modern slavery regulations, making us eligible to submit the official statement.

After ensuring the completeness and accuracy of the report, I successfully submitted the document to the official Australian government portal at Modern Slavery Portal. As a direct result of these efforts, PYVINA achieved SSA certification, significantly expanding our opportunities to export sustainable steel into the Australian market. You can check it out at SSA Website.

Interactive Dashboard for Quality monitoring

I took the initiative to build an automated quality data monitoring dashboard, significantly boosting the efficiency of reporting and analysis. This dashboard quickly provides quality reports, serving daily, weekly, or ad-hoc reporting needs.

To develop this tool, I used a combination of Power BI and Excel to consolidate and process data from various sources and create an intuitive interface. The dashboard not only automates the data collection and presentation process but also allows users to easily track key quality metrics, spot trends, and make timely decisions based on up-to-date data.