Implementasi Program Analisis Reliability Dengan Python Pada Komponen Mesin Capper PT. BBC Untuk Menginvestigasi Nilai Keandalan Dan Implikasinya
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Institusion
Universitas Kristen Indonesia
Author
Adhi, Dodhit Setyo
Subject
Mechanical engineering and machinery
Datestamp
2023-03-31 04:03:58
Abstract :
Keandalan adalah probabilitas suatu item, produk, mesin atau peralatan akan menjalankan fungsi yang diperlukan untuk kurun waktu tertentu, di bawah keadaan operasi tertentu, di bawah kondisi operasi tertentu. Dari penelitian yang ada, telah membahas seputar keandalan (reliability) suatu komponen dalam hal proses manufaktur khususnya, dijelaskan juga urutan proses perhitungan keandalannya menggunakan beberapa aplikasi analisis seperti: Minitab, Reliasoft Blocksim dan sebagainya tetapi juga perlu perhitungan secara manual untuk menentukan nilai keandalannya. Dalam penelitian ini pengaplikasian google colab menggunakan program reliability analisis dengan python untuk menentukan nilai keandalan proses manufaktur dan implikasinya diinvestigasi. Data diperoleh dari PT. BBC pada mesin produksi khususnya komponen Holder 138 kali rusak, Capper 75 kali rusak, dan Transfer Cap 54 kali rusak, komponen tersebut yang menyebabkan sering berhentinya mesin saat proses produksi. Dari proses penggunaan aplikasi google colab dan pemrograman reliability analisis dengan python langsung didapatkan nilai reliability dalam waktu 1 minggu dan 2 minggu untuk komponen holder (82.6% dan 19.12%), capper (88.40% dan 38.04%), dan transfer cap (89.18% dan 35.23%). Hal tersebut dapat dilakukan dengan cepat, akurat, dan mudah dalam 1 siklus baris program python dan dapat dijalankan berulang untuk mendapatkan nilai reliability berdasarkan data yang dimiliki./ Reliability is the probability that an item, product, machine or equipment or even a system will perform a required function for a certain period of time, under certain operating conditions. From the existing research that has discussed the reliability of a component in terms of the manufacturing process in particular, it is also explained the sequence of the reliability calculation process using several analytical applications such as: Minitab, Reliasoft Blocksim, and etc., but also need to be calculated manually to determine the value of reliability. In this study, the Google Colab application uses a program reliability analysis in python to determine the reliability value of the manufacturing process and its implications are investigated. Data obtained from PT. BBC on production machines, especially the Holder component, was damaged 138 times, the Capper was damaged 75 times, and the Transfer Cap was damaged 54 times, these components caused frequent machine stops during the production process. From the process of using the Google Colab application and programming reliability analysis using python, the reliability values were obtained within 1 week and 2 weeks for component holders (82.6% and 19.12%), cappers (88.40% and 38.04%), and transfer caps (89.18% and 19.12%). 35.23%). This can be done quickly, accurately, and easily in a 1 line cycle python program and can be run repeatedly to get a reliability value based on available data.
Keandalan adalah probabilitas suatu item, produk, mesin atau peralatan akan menjalankan fungsi yang diperlukan untuk kurun waktu tertentu, di bawah keadaan operasi tertentu, di bawah kondisi operasi tertentu. Dari penelitian yang ada, telah membahas seputar keandalan (reliability) suatu komponen dalam hal proses manufaktur khususnya, dijelaskan juga urutan proses perhitungan keandalannya menggunakan beberapa aplikasi analisis seperti: Minitab, Reliasoft Blocksim dan sebagainya tetapi juga perlu perhitungan secara manual untuk menentukan nilai keandalannya. Dalam penelitian ini pengaplikasian google colab menggunakan program reliability analisis dengan python untuk menentukan nilai keandalan proses manufaktur dan implikasinya diinvestigasi. Data diperoleh dari PT. BBC pada mesin produksi khususnya komponen Holder 138 kali rusak, Capper 75 kali rusak, dan Transfer Cap 54 kali rusak, komponen tersebut yang menyebabkan sering berhentinya mesin saat proses produksi. Dari proses penggunaan aplikasi google colab dan pemrograman reliability analisis dengan python langsung didapatkan nilai reliability dalam waktu 1 minggu dan 2 minggu untuk komponen holder (82.6% dan 19.12%), capper (88.40% dan 38.04%), dan transfer cap (89.18% dan 35.23%). Hal tersebut dapat dilakukan dengan cepat, akurat, dan mudah dalam 1 siklus baris program python dan dapat dijalankan berulang untuk mendapatkan nilai reliability berdasarkan data yang dimiliki./ Reliability is the probability that an item, product, machine or equipment or even a system will perform a required function for a certain period of time, under certain operating conditions. From the existing research that has discussed the reliability of a component in terms of the manufacturing process in particular, it is also explained the sequence of the reliability calculation process using several analytical applications such as: Minitab, Reliasoft Blocksim, and etc., but also need to be calculated manually to determine the value of reliability. In this study, the Google Colab application uses a program reliability analysis in python to determine the reliability value of the manufacturing process and its implications are investigated. Data obtained from PT. BBC on production machines, especially the Holder component, was damaged 138 times, the Capper was damaged 75 times, and the Transfer Cap was damaged 54 times, these components caused frequent machine stops during the production process. From the process of using the Google Colab application and programming reliability analysis using python, the reliability values were obtained within 1 week and 2 weeks for component holders (82.6% and 19.12%), cappers (88.40% and 38.04%), and transfer caps (89.18% and 19.12%). 35.23%). This can be done quickly, accurately, and easily in a 1 line cycle python program and can be run repeatedly to get a reliability value based on available data.
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