IMAGE PROCESSING SYSTEM FOR SEMICONDUCTOR CHIP  COUNTING AT PT ELEKTRONIK INDONESIA

Hasbullah Hasbullah; Agus Indra Gunawan; Setiawardhana

doi:10.33330/jurteksi.v12i3.4314

Hasbullah Hasbullah Politeknik Elektronika Negeri Surabaya
Agus Indra Gunawan Politeknik Elektronika Negeri Surabaya
Setiawardhana Politeknik Elektronika Negeri Surabaya

DOI: https://doi.org/10.33330/jurteksi.v12i3.4314

Keywords: semiconductor chips counting; image processing; Desktop applications; Production efficiency; Grid detection; Hough transform

Abstract

Abstract: Conventional semiconductor chip counting at PT Elektronik Indonesia relies on manual weighing, which is prone to human error and inefficiency. This study proposes a desktop-based counting system using a digital scanner and image processing. The novelty lies in integrating horizontal-vertical projection with probabilistic Hough transform to robustly detect grid lines, form square cells, and enable accurate unit estimation via average intensity analysis, eliminating the need for reference weighing. Experiments on 15 actual chip images yielded an error rate of 0.009519% and up to 73.674%time efficiency gains compared to the manual method. The system reduces operator dependency, minimizes errors, and accelerates counting, providing a practical machine vision solution for semiconductor production.

Keywords: chip counting; image processing; probabilistic hough transform; grid line detection; time effeciency.

Abstrak: Penghitungan chip semikonduktor konvensional di PT Elektronik Indonesia bergantung pada penimbangan manual, yang rentan terhadap kesalahan manusia dan kurang efisien. Penelitian ini mengusulkan sistem penghitungan berbasis desktop menggunakan scanner digital dan pengolahan citra. Kebaruan terletak pada integrasi proyeksi horizontal-vertikal dengan probabilistic Hough transform untuk mendeteksi garis grid secara kuat, membentuk sel persegi, serta memungkinkan estimasi unit akurat melalui analisis intensitas rata-rata, sehingga menghilangkan kebutuhan penimbangan referensi. Eksperimen pada 15 citra chip aktual menghasilkan tingkat kesalahan 0,009519% dan peningkatan efisiensi waktu hingga 73,674% dibandingkan metode manual. Sistem ini mengurangi ketergantungan operator, meminimalkan kesalahan, dan mempercepat penghitungan, menyediakan solusi machine vision praktis untuk produksi semikonduktor.

Kata kunci: penghitungan chip; pengolahan citra; probabilistic Hough transform; deteksi garis grid; efisiensi waktu.

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