Iron and steel - ARL iSpark Plus Optical Emission Spectrometer

Importance of the Topic

Non-metallic inclusions in steel can lead to degraded mechanical properties, process interruptions and costly rejects. Rapid and reliable inclusion monitoring is therefore essential for modern steelmakers to maintain product quality and minimize production downtime.

Objectives and Study Overview

This application note presents the Basic Inclusion Analysis Spark-DAT option for the Thermo Scientific ARL iSpark Plus optical emission spectrometer. The goal is to illustrate how inclusion counts and elemental composition are obtained simultaneously, enabling real-time quality control on hundreds of steel samples per day.

Methodology and Instrumentation

The Basic Inclusion Analysis is integrated into the standard elemental analysis workflow. Key features include:

• Simultaneous measurement of inclusion counts and elemental concentrations in low-alloy steel.
• Classification of inclusions by chemical type (Al, Ca, Mg and S bearing) and specific compounds (Al₂O₃, Al₂O₃–CaO, CaO, Al₂O₃–MgO, CaS, MnS).
• SML sizing categories (small, medium, large) to assess criticality levels.
• Throughput of up to several hundred samples per 24 hours with less than one second added to each elemental analysis.

Instrumentation Used

• ARL iSpark Plus Series optical emission spectrometer.
• OXSAS analytical software with Spark-DAT inclusion analysis module.
• Photomultiplier tube (PMT) detectors for Al, Ca, Mg, Mn and S channels.
• Standard low-alloy steel calibration standards.

Main Results and Discussion

The method delivers inclusion counts per mm³ for each chemical class, along with SML size distribution. Results are displayed and archived in OXSAS, exportable to Excel, SPC systems or LIMS. A dedicated PDF inclusion report summarizes total and size-resolved counts, facilitating rapid decision-making in production environments.

Benefits and Practical Applications

• Enhanced control of inclusion-dependent properties such as toughness, machinability and fatigue resistance.
• Early detection of process deviations like nozzle clogging or refractory wear.
• Reduction of scrap, rework and customer complaints through proactive quality assurance.
• Seamless integration with existing analytical workflows and data management systems.

Future Trends and Opportunities

Advances may include expanded inclusion libraries, real-time process feedback loops and machine-learning algorithms for predictive quality control. Integration with plant information management systems and cloud-based data analytics will further streamline production and research workflows.

Conclusion

The Basic Inclusion Analysis Spark-DAT option on the ARL iSpark Plus offers a rapid, accurate and cost-effective solution for combined elemental and inclusion analysis in steel. By delivering critical inclusion metrics alongside conventional chemistry data, it empowers steel producers to optimize quality and reduce operational risks.

References

• AN41219 – Standard Inclusion Analysis Spark-DAT Application Note.
• AN41218 – ARL iSpark Plus Basic Inclusion Analysis Application Note.