Artificial Intelligence Techniques In IC Chip Marking Inspection

In this paper, an industrial machine vision system incorporating Optical Character Recognition (OCR) is employed to inspect the marking on the Integrated Circuit (/C) Chips. This inspection is carried out while the /Cs are coming out from the manufacturing line. A TSSOP-DGG type of /C package from Texas Instrument is used in this investigation. The /C chips markings are laser printed. This inspection system tests are laser printed marking on IC chips and are according to the specifications. Artificial intelligence (AI) techniques are used in this inspection. AI techniques utilized are neural network and fuzzy logic. The inspection is carried out to find the print errors; such as illegible character, upside down print and missing characters. The vision inspection of the printed markings on the /C chip is carried out in three phases, namely, image preprocessing, feature extraction and classification. MATLAB platform and its toolboxes are used for designing the inspection processing technique. The percentage of accuracy of the classification is found to be between 97%100%. INTRODUCTION In 1954, Rainbow developed a prototype machine that was able to read upper case written output atthe speed of one character per minutes [1]. From the late 1960's, the OCR technology has undergone many dramatic developments. Multiple recognition system used in the postal department has the capability to read and recognize the characters one by one [2]. Now, reading several hundred characters per minutes is a reality [3]. The document analysis has reached an important position in certain market. The application of OCR in the postal automation followed into the banks and industrial inspection [4, 5]. Further more, a successful recognition rate of 99.9% of multifont of any size has been reported [6]. IC chips play a vital role in the electronic industry. Mass production of IC chips have brought down the price of the electronic products. Texas Instrument is one of