Creating the Slider Tester Repair Recommendation System to Enhance the Repair Step by Using Machine Learning DOI Creative Commons

Rattaphong Udomsup,

Suphatchakan Nuchkum,

Jiraphon Srisertpol

и другие.

Machines, Год журнала: 2024, Номер 12(9), С. 661 - 661

Опубликована: Сен. 21, 2024

This project aims to develop a recommendation system mitigate looping issues in HDD slider testing using the Amber machine (Machine A). Components simulating often fail and require repair before re-testing. However, post-repair, there is 34% probability that component (referred as Product A) will experience looping, characterized by repeated failures with error code A. recurring issue significantly hampers efficiency reducing number of successful tests. To address this challenge, we propose dual-approach provides technicians actionable insights minimize occurrence looping. For previously analyzed components, collaborative filtering technique utilizing implicit ratings employed generate recommendations. new for which prior data are unavailable, cosine similarity approach applied suggest optimal actions. An automatic training implemented retrain model become available, ensuring remains robust effective over time. The proposed expected offer precise guidance technicians, thereby improving overall process frequency issues. work represents significant advancement enhancing operational reliability productivity testing.

Язык: Английский

Industrial Expert Systems Review: A Comprehensive Analysis of Typical Applications DOI Creative Commons

Xianzhe Yang,

Changsheng Zhu

IEEE Access, Год журнала: 2024, Номер 12, С. 88558 - 88584

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

7
Creating the Slider Tester Repair Recommendation System to Enhance the Repair Step by Using Machine Learning DOI Creative Commons

Rattaphong Udomsup,

Suphatchakan Nuchkum,

Jiraphon Srisertpol

и другие.

Machines, Год журнала: 2024, Номер 12(9), С. 661 - 661

Опубликована: Сен. 21, 2024

This project aims to develop a recommendation system mitigate looping issues in HDD slider testing using the Amber machine (Machine A). Components simulating often fail and require repair before re-testing. However, post-repair, there is 34% probability that component (referred as Product A) will experience looping, characterized by repeated failures with error code A. recurring issue significantly hampers efficiency reducing number of successful tests. To address this challenge, we propose dual-approach provides technicians actionable insights minimize occurrence looping. For previously analyzed components, collaborative filtering technique utilizing implicit ratings employed generate recommendations. new for which prior data are unavailable, cosine similarity approach applied suggest optimal actions. An automatic training implemented retrain model become available, ensuring remains robust effective over time. The proposed expected offer precise guidance technicians, thereby improving overall process frequency issues. work represents significant advancement enhancing operational reliability productivity testing.

Язык: Английский

Процитировано

0