The deep layout of the industrial chain of machine vision industry further enriches the product line and capacity construction, and strengthens the research and development of artificial intelligence technology in the field of machine vision industrial inspection.
The traditional detection equipment, completely relying on the algorithm database set by the technical side, can only repeatedly detect known types of defects that have been input, but can not identify and detect new and uncommon defects.
By redefining the process of defect definition to the front-line staff, the front-line staff only need to carry out preliminary mark classification for defects, and the equipment will "remember" these judgments, and simulate the human brain for analysis and identification. With the increasing amount of detection data and the continuous expansion of the database, the detection results will be more accurate.
In the application case, AI technology is integrated into the visual inspection of crystalline silicon battery, which breaks the barriers of traditional automation equipment and realizes real intelligence and data. At present, in addition to the crystalline silicon battery industry, Lipper technology also applies artificial intelligence technology to other visual inspection fields, and the application of AI technology is an inevitable trend in the defect detection industry.
The general machine vision development platform combines thousands of operators into nearly one hundred core algorithm tools. Users do not need to write any code, but only need to combine various algorithms and tools through "drag", "pull" and "point", so as to realize various visual inspection tasks, simplify the complexity of machine vision system implementation, and solve the problem of long project development cycle and human and material resources cost High industry pain points.
Machine vision, as a technology to make robots and other automation equipment more intelligent, has been widely favored by the capital market in recent years. Even in the special period of capital shortage, machine vision still maintains a high degree of attention, and enterprise financing events continue to flow.
In the future, a greater breakthrough in the depth and width of AI technology applied to machine vision inspection system is a tool that can impart human knowledge and experience to equipment, so that robots can understand manufacturing and realize the ideal of real machine automation.