Automated X-ray inspection (AXI) is a technology based on the same principles as automated optical inspection (AOI). It uses X-rays as its source, instead of visible light, to automatically inspect features, which are typically hidden from view.
Automated X-ray inspection is used in a wide range of industries and applications, predominantly with two major goals:
Process optimization, i.e. the results of the inspection are used to optimize following processing steps,
Anomaly detection, i.e. the result of the inspection serve as a criterion to reject a part (for scrap or re-work).
Whilst AOI is mainly associated with electronics manufacturing (due to widespread use in PCB manufacturing), AXI has a much wider range of applications. It ranges from the quality check of alloy wheels to the detection of bone fragments in processed meat. Wherever large numbers of very similar items are produced according to a defined standard, automatic inspection using advanced image processing and pattern recognition software (Computer vision) has become a useful tool to ensure quality and improve yield in processing and manufacturing.
With the advancement of image processing software the number applications for automated x-ray inspection is huge and constantly growing. The first applications started off in industries where the safety aspect of components demanded a careful inspection of each part produced (e.g. welding seams for metal parts in nuclear power stations) because the technology was expectedly very expensive in the beginning. But with wider adoption of the technology, prices came down significantly and opened automated x-ray inspection up to a much wider field- partially fueled again by safety aspects (e.g. detection of metal, glass or other materials in processed food) or to increase yield and optimize processing (e.g. detection of size and location of holes in cheese to optimize slicing patterns).[4]
In mass production of complex items (e.g. in electronics manufacturing), an early detection of defects can drastically reduce overall cost, because it prevents defective parts from being used in subsequent manufacturing steps. This results in three major benefits: a) it provides feedback at the earliest possible state that materials are defective or process parameters got out of control, b) it prevents adding value to components that are already defective and therefore reduces the overall cost of a defect, and c) it increases the likelihood of field defects of the final product, because the defect may not be detected at later stages in quality inspection or during functional testing due to the limited set of test patterns.
Post time: Dec-28-2021