IC scanner and recommendation

Modern electronic devices heavily rely on integrated circuits (ICs) and their effective testing and verification is essential for maintaining system dependability. This IC Tester and Recommendation System mobile application helps users to identify information about ICs. It utilizes Optical Character Recognition (OCR) through Google ML Kit to extract imaged IC model numbers and look them up against a stored database for accurate identification. The app is made on Flutter which helps easy use on many devices and customizability with simple design change implementation. This study looks at IC testing methods of lower cost while dealing with ATE limits, showing the benefits of pseudo random testing in cheap and sure testing. For validation purposes, the system employs truth table validation methods on 74 series logic ICs and other combinational and sequential circuits. With the aim of implementation on a microcontroller such as Arduino Mega nor PIC18F4550, the system performed truth table checks on digital ICs and displayed the results with answer confirmation on an LCD. The suggested answer gives a cheap, easy-to-carry, and simple substitute for usual IC testers, making it good for use in industries, schools, and labs. By adding automatic IC spotting and checking, the setup much boosts work speed, cuts human mistakes, and helps fix problems in the steps of making and mending electronics.

Authors

Publication Details

Journal
World Journal of Advanced Engineering Technology and Sciences
Published
2025-05-09
DOI
https://doi.org/10.30574/wjaets.2025.15.2.0542
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

IC scanner and recommendation

Nikhil Raj, Sunil Gupta, Nilima Chapke, Kamal Vaishnav
1 links
World Journal of Advanced Engineering Technology and Sciences
Manufacturing Process and Optimization
article

IC scanner and recommendation

Nikhil Raj, Sunil Gupta, Nilima Chapke, Kamal Vaishnav
article en

Abstract

Modern electronic devices heavily rely on integrated circuits (ICs) and their effective testing and verification is essential for maintaining system dependability. This IC Tester and Recommendation System mobile application helps users to identify information about ICs. It utilizes Optical Character Recognition (OCR) through Google ML Kit to extract imaged IC model numbers and look them up against a stored database for accurate identification. The app is made on Flutter which helps easy use on many devices and customizability with simple design change implementation. This study looks at IC testing methods of lower cost while dealing with ATE limits, showing the benefits of pseudo random testing in cheap and sure testing. For validation purposes, the system employs truth table validation methods on 74 series logic ICs and other combinational and sequential circuits. With the aim of implementation on a microcontroller such as Arduino Mega nor PIC18F4550, the system performed truth table checks on digital ICs and displayed the results with answer confirmation on an LCD. The suggested answer gives a cheap, easy-to-carry, and simple substitute for usual IC testers, making it good for use in industries, schools, and labs. By adding automatic IC spotting and checking, the setup much boosts work speed, cuts human mistakes, and helps fix problems in the steps of making and mending electronics.

World Journal of Advanced Engineering Technology and SciencesVol. 15(2)
Openalex Percentile: Top 87%
Manufacturing Process and Optimization
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