A press release by Technavio Research last Fall, stated that the global galvanized steel market is expected to grow by 35.18 million MT during 2020-2024. The release says in part:
The strong economic growth in China and India has increased the number of infrastructure and construction projects such as roads, highways, and railways in these countries. Besides, the easy availability of raw materials and cost-effective labor has fueled the growth of the manufacturing industry in China and India. Moreover, these countries are among the largest crude steel manufacturers in the world, and India is expected to emerge as the second-largest producer of crude steel during the forecast period. All these factors are significantly contributing to the growth of the global galvanized steel market.
To meet this demand and supply quality products, manufacturers of galvanized steel must overcome two key challenges associated with creating accurate standards for calibration of online X-ray Fluorescence (XRF) based coating weight gauges. First, the lack of internationally recognized primary standards requires galvanizing lines to develop their own reference samples following the ASTM A754 / A754M standard test method. Secondly, with an increase in the use of Advanced High Strength Steel (AHSS) and their unique chemistry in galvanizing lines, separate calibration samples may be needed to account for the different behaviors of the substrate in the alloy layer growth.
The method used to demonstrate these challenges was to measure galvanized samples from different production lines on an XRF coating weight gauge and compare the predicted value with assigned coating weight based on destructive analysis of nearby samples.
We have tested this method and have presented a sample of results from the gauge readings demonstrating the influence of different substrate materials on XRF signals in a white paper, entitled Challenges Associated with Developing XRF Coating Weight Standards.
The results include an overview of the sensor repeatability, statistical variation and long-term stability. Additional considerations are given with respect to typical variations that occur in the rolling environment. Related discussions on the range of calibration samples versus expected production range and potential errors from extrapolation are also presented.
The conclusions presented include a modified technique for calibrating XRF-based coating weight gauges that maximizes the sample data available. The benefits of increasing the number of samples on the overall gauge accuracy are also included.
- Read the white paper Challenges Associated with Developing XRF Coating Weight Standards that includes a review of XRF coating weight gauges, calibration methods and charts, and notes about the ideal GI sample collection process.