Perancangan Aplikasi Long-Range Engine Performance And Fuel Consumption Monitoring Berbasis Digital Platform Untuk Pengembangan Digital Twin

Fahlevi, Syach Reza (2023) Perancangan Aplikasi Long-Range Engine Performance And Fuel Consumption Monitoring Berbasis Digital Platform Untuk Pengembangan Digital Twin. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 04211940000053-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only until 1 September 2025. Download (6MB) | Request a copy

Abstract

Industri 4.0 merupakan era revolusi industri yang ditandai dengan adopsi teknologi digital dan otomatisasi yang luas untuk meningkatkan efisiensi dan produktivitas di berbagai sektor industri. Perkembangannya di industri maritim telah membawa perubahan yang signifikan. Penggunaan teknologi seperti Internet of Things (IoT), big data, dan digital twin telah memungkinkan pemantauan real-time terhadap mesin kapal. Ini membantu meningkatkan efisiensi operasional, keamanan, dan keselamatan kapal tersebut. Oleh karena itu, diperlukan alat monitor digital yang dapat memantau dan menganalisis data secara real-time dalam permesinan kapal. Alat monitor digital ini dapat mengintegrasikan data dari berbagai sensor, perangkat, dan sistem untuk memberikan informasi yang akurat dan dapat dipercaya. Dengan demikian, pengambilan keputusan dapat dilakukan dengan lebih efektif dan tepat waktu. Website dikembangkan menggunakan framework ReactJS. Framework ini sangat populer dalam pengembangan aplikasi web karena kemampuannya dalam menciptakan antarmuka pengguna yang responsif dan interaktif. Dengan menggunakan ReactJS, pengembang dapat memanfaatkan komponen reusable dan pembaruan data yang efisien, sehingga meningkatkan kecepatan pengembangan dan kualitas aplikasi web. Hasil yang didapat berupa pembacaan data dari perangkat monitor secara real-time. Data yang dikumpulkan melalui alat monitor digital dapat memberikan informasi yang akurat tentang kondisi mesin kapal. Dengan pembacaan data yang tepat waktu, pemangku kepentingan dapat melakukan analisis dan pengambilan keputusan berdasarkan informasi yang terkini. Hal ini membantu meningkatkan efisiensi, keamanan, dan keselamatan di sektor industri maritim. ==================================================================================================================================
Lubrication is one of the most important components in the machining process. Lubrication can extend tool life, reduce cutting forces and reduce workpiece surface roughness. One lubrication technique that is starting to be widely used in the machining process is Minimum Quantity Lubrication (MQL). MQL is a lubrication based on the concept of near-dry machining. MQL is widely applied as an environmentally friendly lubrication technique compared to flood lubrication. MQL greatly reduces the amount of lubricant used in the machining process and also addresses environmental, economic, and process performance issues. This study discusses the turning process with MQL on S45C material. The experimental design used is Taguchi L9. The parameters used were cutting speed (97, 192, and 308 m/min), feeding speed (0.15; 0.20; and 0.25 mm/rev), and depth of cut (0.50; 0.75; and 1.0 mm). The response variables studied were cutting force, surface roughness, and tool wear. The effect of the parameters on the response variables was analyzed using Analysis of Variance (ANOVA). The optimization method used in this research is Back Propagation Neural Network - Genetic Algorithm (BPNN-GA). Genetic Algorithm (GA) is an optimization method based on the principles of genetics and natural selection. The basic elements of GA include selection, crossover, and mutation. The selection method used is roulette wheel. The advantage of GA over other optimization methods is that GA can optimize problems with complex problems and a very wide search space. The results showed that the BPNN-GA optimization method can provide optimal response variables. BPNN-GA optimization is able to predict the resulting response variable with an average difference between the predicted results and the experimental results of 1.40%. The process parameter settings that can provide the minimum cutting force, surface roughness, and tool wear values are cutting speed 97 m/min, feeding speed 0.15 mm/rev, and depth of cut 0.55 mm.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Digital Twin, Real Time, Website, Framework.
Subjects:	V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering
Divisions:	Faculty of Marine Technology (MARTECH) > Marine Engineering > 36202-(S1) Undergraduate Thesis
Depositing User:	Syach Reza Fahlevi
Date Deposited:	14 Sep 2023 04:06
Last Modified:	14 Sep 2023 04:06
URI:	http://repository.its.ac.id/id/eprint/102028

Actions (login required)

View Item