Klasifikasi Level Pada Sistem Checker Asam Baterai Menggunakan Metode Fuzzy Logic

Ariyanto, Maulana Dicky (2024) Klasifikasi Level Pada Sistem Checker Asam Baterai Menggunakan Metode Fuzzy Logic. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Proses pemeriksaan ketinggian air asam pada baterai di PT GS Battery yang menggunakan mesin level checker saat ini masih sering terjadi ketidaksesuaian standart kualitas, sehingga mesin perlu dilakukan pengembangan. Berdasarkan data yang ada, terjadi kesalahan pembacaan ketinggian air asam pada baterai. Hal ini menajdi fokus permasalahan tim engineer. Setelah melakukan observasi di lapangan terdapat beberapa faktor, salah satunya adalah keakuratan pembacaan ketinggian air asam pada baterai yang masih manual dengan visual operator. Maka dari itu, pada penelitian proyek akhir ini diciptakanlah sebuah pembaruan sistem pengukur ketinggian air asam menggunakan sensor fiber optik. Pada pembaruan ini mengubah metode pembacaan terhadap ketinggian asam pada baterai yang awalnya menggunakan visual operator menajdi pergerakan sensor secara vertikal untuk mengukur ketinggian air asam dari tiap sel baterai. Selain itu, juga dapat meningkatkan keakurasian pembacaan sensor terhadap ketinggian air asam pada baterai dengan menampilkan nilai pembacaan dua angka dibelakang koma. Pembaruan ini dapat di kontrol menggunakan metode Fuzzy Logic. Fuzzy Logic memiliki beberapa tahapan sebelum diaplikasikan kedalam mesin level checker, yaitu fuzzifikasi, inferensi, dan deffuzifikasi. Fuzzifikasi merupakan proses mengubah input sistem yang mempunyai nilai tegas (crisp) menjadi variabel linguistik (fuzzy) menggunakan fungsi keanggotaan yang disimpan pada basis pengetahuan. Inferensi merupakan proses mengubah input fuzzy menjadi output fuzzy dengan cara mengikuti aturan-aturan yang telah ditetapkan pada basis pengetahuan fuzzy. Deffuzifikasi merupakan proses mengubah hasil dari tahap inferensi menjadi output yang bernilai tegas (crisp) menggunakan fungsi keanggotaan yang telah ditetapkan. Tahapan inilah yang membuat mesin level checker dapat mengambil keputusan yang lebih akurat sehingga tidak terjadinya misjudgment. Dari hasil pengujian pembacaan sensor dan aktual jangka sorong sudah terverifikasi dengan baik dan melakukan judgement sesuai dengan kondisi aktual. Dengan pengujian komparasi menggunaan jangka sorong, sistem baru memiliki angka error 1,82%. Ketinggian asam pada sel baterai dapat diukur sesuai dengan standart kualitas dan tidak terjadinya kesalahan pembacaan akibat sensor yang kurang akurat. Metode Fuzzy Logic juga dapat diimplementasikan dengan baik di sistem ini meski memiliki nilai MAPE 2,3% sebelum menggunakan fuzzy grid dan 1,5% setelah menggunakan fuzzy grid.
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The process of checking the acid water level in the battery at PT GS Battery using the current level checker machine still often does not meet the quality standards, so the machine needs to be developed. Based on existing data, there is an error in reading the acid water level in the battery. This is the focus of the engineer team's problems. After making observations in the field, there are several factors, one of which is the accuracy of reading the acid water level in batteries that are still manual with visual operators. Therefore, in this final project research, an update of the acid water level measuring system using fiber optic sensors was created. This update changes the method of reading the acid level in the battery which initially uses the operator's visual to move the sensor vertically to measure the acid water level of each battery cell. In addition, it can also increase the accuracy of the sensor reading of the acid water level in the battery by displaying the reading value two digits behind the comma. This update can be controlled using the Fuzzy Logic method. Fuzzy Logic has several stages before being applied to the level checker machine, namely fuzzification, inference, and deffuzification. Fuzzification is the process of converting crisp system inputs into fuzzy linguistic variables using membership functions stored in the knowledge base. Inference is the process of converting fuzzy inputs into fuzzy outputs by following the rules established in the fuzzy knowledge base. Defuzzification is the process of converting the inference results into crisp output values using predetermined membership functions. These stages make the level checker machine able to make more accurate decisions so that there is no misjudgment. From the test results, the sensor readings and actual thrusters have been verified properly and make judgments in accordance with actual conditions. With comparative testing using a vernier, the new system has an error rate of 1.82%. The height of the acid in the battery cell can be measured according to the quality standard and there is no reading error due to inaccurate sensors. Fuzzy Logic method can also be implemented well in this system even though it has a MAPE value of 2.3% before using fuzzy grid and 1.5% after using fuzzy grid.

Item Type: Thesis (Other)
Uncontrolled Keywords: Air Asam, Fiber Optic Sensor, Fuzzy Grid, Fuzzy Logic, Level Checker, Acid Water, Fiber Optic Sensor, Fuzzy Grid, Fuzzy Logic, Level Checker
Subjects: Q Science > QA Mathematics > QA39.3 Fuzzy mathematics
Q Science > QA Mathematics > QA9.64 Fuzzy logic
Q Science > QA Mathematics > QA248_Fuzzy Sets
T Technology > T Technology (General) > T58.8 Productivity. Efficiency
T Technology > T Technology (General) > T59.7 Human-machine systems.
T Technology > TA Engineering (General). Civil engineering (General) > TA1573 Detectors. Sensors
T Technology > TA Engineering (General). Civil engineering (General) > TA1800 Fiber Optics
T Technology > TC Hydraulic engineering. Ocean engineering > TC424 Water levels
T Technology > TJ Mechanical engineering and machinery > TJ1398 Conveyors
T Technology > TJ Mechanical engineering and machinery > TJ174 Maintenance and repair of machinery
T Technology > TJ Mechanical engineering and machinery > TJ219 Pneumatic control systems
T Technology > TJ Mechanical engineering and machinery > TJ223.P76 Programmable controllers
T Technology > TJ Mechanical engineering and machinery > TJ230 Machine design
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7878 Electronic instruments
Divisions: Faculty of Vocational > 36304-Automation Electronic Engineering
Depositing User: Maulana Dicky Ariyanto
Date Deposited: 23 Aug 2024 02:04
Last Modified: 23 Aug 2024 02:04
URI: http://repository.its.ac.id/id/eprint/115485

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