In metal additive manufacturing (AM)

rapid material temperature changes and complicated material behavior inevitably lead to various types of surface and internal defects

which are detrimental to the performance of final parts

and hinder the development and application of metal AM in key areas. Acquiring defect information in time is beneficial for adjusting process parameters

improving manufacturing process

and elevating parts quality. Meanwhile

the defect information can be utilized to conduct subsequent machining and processing. Therefore

it is of significance to conduct research on defect detection technologies to improve AM technology and expand its applications. To resolve this issue

this paper introduces the common defects in AM parts and summarizes their origins. Then typical studies on AM defect detection technologies in recent years are reviewed

with a focus on the monitoring of process signatures and the online non-destructive testing methods. The application scope of different methods is also presented. Finally

the development trend of defect detection technology is forecasted. A conclusion is drawn that defects in AM are complicated and the parts quality needs to be assured by detection methods and technologies. However

methods proposed so far still cannot satisfy the requirement of AM

and the technology should be developed towards integration and intelligence in the future.