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All Journal Jurnal Teknik ITS IPTEK Journal of Proceedings Series KERN Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Jurnal Chemurgy Journal of Robotics and Control (JRC) Vocatech : Vocational Education and Technology Journal ASEAN Journal of Chemical Engineering International Journal of Robotics and Control Systems Sewagati
Totok Ruki Biyanto
Engineering Physics, Institut Teknologi Sepuluh Nopember
Aerospace Engineering Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Public Health Social Sciences Other

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Journal : IPTEK Journal of Proceedings Series

 1 
Abstract of Invited Speaker : Green Concept in Engineering Practice Biyanto, Totok Ruki
IPTEK Journal of Proceedings Series No 1 (2015): 1st International Seminar on Science and Technology (ISST) 2015
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (559.126 KB) | DOI: 10.12962/j23546026.y2015i1.1119

Abstract

In recent time, becoming green is not only a matter of compliance with regulations, however it is a matter of responding to the expectations and demands of our world, country, community, stockholders, customers, employees and competitors. These matters create tremendous pressure for companies to carry out their activities in a more environmental friendly.Being green requires the best engineering minds and commitment from the entire organization. Engineering is all  about  practicality  finding  solutions  to  improve  theconditions. Excellent understanding of the fundamental engineering  is  a  key  to  helping  industrial  activities  tobecome greener and the engineers are in an ideal position to contribute in these activities, in term of development andimplementation of technologically sound, as well as cost- effective solutions.Green initiatives create big business opportunities in the order of trillions of dollars for innovative companies and engineers,  in  this  decade.  These  business  activities  arestarted from research and development, plant design, plant construction and plant operation stage. This paper presents some ideas on how to implement the green concept in engineering  activities.  The  case  studies  application  ofgreen engineering in refinery crude preheat train and cement plant waste heat recovery generation are also presented
Performance Optimization of Gas Turbine Generator Based on Operating Conditions Using ANN-GA at Saka Indonesia Pangkah Ltd Risma Yudhanto; Totok Ruki Biyanto
IPTEK Journal of Proceedings Series No 6 (2020): 6th International Seminar on Science and Technology 2020 (ISST 2020)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j23546026.y2020i6.8901

Abstract

A Gas Turbine is a rotary engine that extracts energy from a flow combustion gas. The reliability and efficiency of gas turbines are one of the top priorities at Saka Indonesia Pangkah Ltd (SIPL). In order to optimize the operating conditions of a gas turbine, three components are needed. First is the problem formulation which consists of objective functions, problem boundaries or constraints, and determination of optimized variables. The second component is a valid model, which represents the characteristics of a gas turbine installed in SIPL. The third component is the optimization technique that is suitable with the optimization problem that will be solved. In this paper, the objective function is maximizing gas turbine efficiency, some operational limitation as constrains by manipulating air to fuel ratio. The model was developed using Artificial Neural Network (ANN) and Genetic Algorithm (GA) was selected as the stochastic optimization technique to solve the problem. The neural network model created directly using the operational data from an actual parameter gas turbine generator. The data needed for ANN-based modeling is around 8150 data sets that will be used to train and validate the ANN model. Variable data sets were divided in two parts, for training purposes is 87.5% and for validation is 12.5%. Weight management for neural networks was carried out using Levenberg-Marquardt algorithm which could give good results with RMSE = 7.3 X 10-3. From the results of the stochastic optimization (GA) simulation, the potential reduction of fuel gas consumption is around 280.8 kg/hr if the air mass flow can be increased from 2.4 kg/s to 2.7 kg/s or efficiency increase up to 10.6%.
Co-Authors Agustina, Nilla Perdana Ahnaf, Hudzaifa Dhiaul Al Farros, Mohammad Naufal Darmoyono, Aditya Gautama Detak Yan Pratama Eka Mutia Lubis Fathoni, Rif'an Franky Kusuma Gideon Saputra Nainggolan Gideon Saputra Nainggolan Gusnam, Mu'thiana Hairul Huda Imron, Choirul Iwan Cony Setiadi, Iwan Cony Kamarudin Kamarudin Mahdaliza, Rahmi Mohammad Okky Mabruri Mohammad Okky Mabruri Muhammad Andro Purnomo Muhammad Andro Purnomo Nanda Erzhiavica Tama Nanda Erzhiavica Tama Oktani, Dessy Purwadi Agus Darwito Renanto Handogo Rifnaldi Veriyawan Risma Yudhanto Roosydi, Syahrizal Faried Santoso, Hari H. Syafi'i, Ahmad Tantra Diwa Larasati Utami, Intan Tri Vieri Limanto Vincentius Surya Kurnia Adi Wei Wu WimbangWicaksono, Muhammad Jaka Yaumar Yaumar, Yaumar