Automation of X-ray fluorescence equipment has proliferated during the last 10 years. However, the focus has been on data collection and data massage. Data presentation has been limited to a few rudimentary formats. These formats ‘ generally involve printing the results in some arbitrary fashion, followed by manual transfer to the client.

This paper describes a system (using rudimentary artificial intelligence techniques) that automates data presentation. It handles data from 14 different methods; evaluates the data against the requirements of the method (i.e. mass balance, detection and reporting limits, and matrix interferences). Further, a data report is generated in a consistent format, including the reporting of significant figures. Additionally, an exception report is printed when the measured results are outside the applicable range of the method or violate quality assurance constraints. In such cases, alternative methods are recommended in the exception report.