eng
Research Expansion Alliance (REA) on behalf of Ayandegan Institute of Higher Education
Journal of Applied Research on Industrial Engineering
2538-5100
2676-6167
2018-11-01
5
3
181
184
10.22105/jarie.2018.76770
76770
An energy storage and rapid charge system using supercapacitor for a light rail system which runs on renewable energy
Takaki Kameya
143d9101@st.kumamoto-u.ac.jp
1
Jamal Uddin
2
William Ghann
3
Hiroshi Takami
4
Genji Suzuki
5
Hidetoshi Katsuma
6
Tokyo University of Technology, 1404-1 Katakura-machi, Hachioji, Tokyo 192-0982, Japan.
Center for Nanotechnology, Coppin State University, USA.
Center for Nanotechnology, Coppin State University, USA.
College of Engineering, Shibaura Institute of Technology, Japan.
School of Science and Engineering, Tokyo Denki University, Japan.
Shonan Research Center for LRT, Japan.
A light rail system which runs on 100% renewable energy named the “Solar Light Rail” has been proposed by authors. Experiments using a prototype model have been carried out to demonstrate the availability of the rechargeable power supply method using supercapacitors. In the experiments using the updated equipment, the experimental condition is changed from the passed experiments, and the energy consumption per run is decreased. Low energy consumption causes running for a longer time after sunset. The handmade equipment is more efficient and makes the better result by the improvement.
https://www.journal-aprie.com/article_76770_9f6710bbe803cede302bc3e5d4905882.pdf
Transportation
Renewable Energy
Supercapacitor
Energy Storage
Rapid Charge
eng
Research Expansion Alliance (REA) on behalf of Ayandegan Institute of Higher Education
Journal of Applied Research on Industrial Engineering
2538-5100
2676-6167
2018-11-01
5
3
185
204
10.22105/jarie.2018.144919.1052
73623
Initialization of a multi-objective evolutionary algorithms knowledge acquisition system for renewable energy power plants
Burak Saracoglu
burakomersaracoglu@hotmail.com
1
Miguel De Simón Martín
miguel.simon@unileon.es
2
Orhantepe Mahallesi, Tekel Caddesi, Istanbul, Turkey
Department of Electrical, Systems and Automatics Engineering, University of León, Spain.
The design of Renewable Energy Power Plants (REPPs) is crucial not only for the investments' performance and attractiveness measures, but also for the maximization of resource (source) usage (e.g. sun, water, and wind) and the minimization of raw materials (e.g. aluminum: Al, cadmium: Cd, iron: Fe, silicon: Si, and tellurium: Te) consumption. Hence, several appropriate and satisfactory Multi-Objective Problems (MOPs) are mandatory during the REPPs' design phases. MOPs related tasks can only be managed by very well organized knowledge acquisition on all REPPs' design equations and models. The proposed MOPs need to be solved with one or more multi-objective algorithm, such as Multi-Objective Evolutionary Algorithms (MOEAs). In this respect, the first aim of this research study is to start gathering knowledge on the REPPs' MOPs. The second aim of this study is to gather detailed information about all MOEAs and available free software tools for their development. The main contribution of this research is the initialization of a proposed multi-objective evolutionary algorithm knowledge acquisition system for renewable energy power plants (MOEAs-KAS-F-REPPs) (research and development loopwise process: develop, train, validate, improve, test, improve, operate, and improve). As a simple representative example of this knowledge acquisition system research with two selective and elective proposed standard objectives (as test objectives) and eight selective and elective proposed standard constraints (as test constraints) are generated and applied as a standardized MOP for a virtual small hydropower plant design and investment. The maximization of energy generation (MWh) and the minimization of initial investment cost (million €) are achieved by the Multi-Objective Genetic Algorithm (MOGA), the Niched Sharing Genetic Algorithm/Non-dominated Sorting Genetic Algorithm (NSGA-I), and the NSGA-II algorithms in the Scilab 6.0.0 as only three standardized MOEAs amongst all proposed standardized MOEAs on two desktop computer configurations (Windows 10 Home 1709 64 bits, Intel i5-7200 CPU @ 2.7 GHz, 8.00 GB RAM with internet connection and Windows 10 Pro, Intel(R) Core(TM) i5 CPU 650 @ 3.20 GHz, 6,00 GB RAM with internet connection). The algorithm run-times (computation time) of the current applications vary between 20.64 and 59.98 seconds.
https://www.journal-aprie.com/article_73623_69ab6206ca6c3af7baa6ad204a543964.pdf
Multi-Objective Optimization
multi-objective problem
multi-objective evolutionary algorithm
Scilab
Renewable Energy
eng
Research Expansion Alliance (REA) on behalf of Ayandegan Institute of Higher Education
Journal of Applied Research on Industrial Engineering
2538-5100
2676-6167
2018-11-01
5
3
205
222
10.22105/jarie.2018.79157
79157
Sustainable reliability centered maintenance optimization considering risk attitude
Ali Karevan
ali_karevan1992@yahoo.com
1
Mohammadreza Vasili
reza.vasili@hotmail.com
2
Department of Industrial Engineering, Islamic Azad University, Najafabad Branch, Iran.
Department of Industrial Engineering, Islamic Azad University, Lenjan Branch, Isfahan, Iran.
Maintenance costs are one of the major costs in plants and companies. The observation in many cases illustrates the lack of plans or mistakes in maintenance activities that incurred great costs. In this study, the number of equipment failures have been determined. Then the failure rate and reliability of each equipment are calculated. The third step calculates total system reliability so the initial plan is presented. After that, by using the obtained information, the sustainability aspects of the program will generate and the maintenance costs and sustainability functions will assess. At the end, this multi-objective optimization problem is solved by MOPSO algorithm and the results are compared with a simulation method. As a result, with this reliability centered maintenance program, the reliability of each equipment, as well as the whole system are improved; economic aspect of sustainability and customer satisfaction are increased; environmental pollutions and maintenance costs are decreased by offering more reliability based program; a scheduling plan for each maintenance procedures is provided and also more stable internet connection is established by reducing the system failures.
https://www.journal-aprie.com/article_79157_ddc2b936e8a2f86cfb87422a54310744.pdf
Sustainability
Reliability
maintenance
Risk Attitude
Multi-objective Particle swarm optimization
Internet Telecommunications Equipment
eng
Research Expansion Alliance (REA) on behalf of Ayandegan Institute of Higher Education
Journal of Applied Research on Industrial Engineering
2538-5100
2676-6167
2018-11-01
5
3
223
238
10.22105/jarie.2018.138366.1041
68036
Reduction bottle cost of Milkuat LAB 70 ml using optimal parameter setting with Taguchi method
Yudi Prastyo
prasdi.utomo@gmail.com
1
Wahyu Adhi Yatma
wahyu.yatma@gmail.com
2
Hernadewita Hernadewita
hernadewita@mercubuana.ac.id
3
Department of Industrial Engineering, University of Mercu Buana, Jakarta, Indonesia.
Department of Industrial Engineering, University of Mercu Buana, Jakarta, Indonesia.
Department of Industrial Engineering, University of Mercu Buana, Jakarta, Indonesia.
The profit margins decrease up to 30%; the bottles are as the main cause of 10%. This study focuses on bottle analysis and aims to get the optimal weight of the Milkuat LAB 70 ml bottle by not forgetting about some standard parameters that cannot be changed. This experiment uses the Taguchi method, which includes knowing the factor level settings, optimal settings, optimal bottle weight, optimal bottle strength, getting QLF (Quality Loss Function), results from transportation test, and reject ratio in the production line. And some additional methods such as transportation tests have also carried out in this study. The results of this study are that the influential level factor settings are S2 and S4, for setting the optimal level is S2 (A3) is 1.25 mm and bottle S4 (B3) is 0.95 mm, the optimal bottle weight is 7.00 gr from before 7.80 gr, with current bottle strength 19.64 Kg with the previous weight is 19.80 Kg, the value of QLF (Quality Loss Function) is IDR. 7,000, - from before is IDR. 7,815, - deviation of IDR. 16.02, - and efficient per Day IDR. 28,836,000, - with output 1,800,000 bottles per day and the results of transportation tests remain on 22 cartons stack; the reject decline production ratio is not too much different for 1 hour production, 1 production shift and up to 1-3 months of production using a bottle of 7.00 gr with the conclusion of the statistics that is "Not Significant Difference from 7.80 gr" that means that the results are good in productivity and cost efficiency.
https://www.journal-aprie.com/article_68036_a52d5ef3936b0c35ff60dcd52b96a7f4.pdf
Strength
Bottle Strength
Design
QLF (Quality Loss Function)
Optimum
COVI (Cost Out Value In)
Taguchi method
eng
Research Expansion Alliance (REA) on behalf of Ayandegan Institute of Higher Education
Journal of Applied Research on Industrial Engineering
2538-5100
2676-6167
2018-11-01
5
3
239
252
10.22105/jarie.2018.148642.1054
76939
On solving fully fuzzy multi-criteria De Novo programming via fuzzy goal programming approach
Hamiden Khalifa
hamiden_2008@yahoo.com
1
Operations Research Department, Institute of Statistical Studies and Research, Cairo University, Giza, Egypt.
In this paper, a Multi-Criteria De Novo Linear Programming (F- MDNLP) problem has been developed under consideration of the ambiguity of parameters. These fuzzy parameters are characterized by fuzzy numbers. A fuzzy goal programming approach is applied for the corresponding multi-criteria De Novo linear programming (MDNLP) problem by defining suitable membership functions and aspiration levels. The advantage of the approach is that the decision maker's role is only the specification of the level and hence evaluate the efficient solution for limitation of his/ her incomplete knowledge about the problem domain. A numerical example is given for illustration.
https://www.journal-aprie.com/article_76939_193e05cad042cda82e48a3ba1cee4622.pdf
Multi-criteria De Novo
Fuzzy Numbers
fuzzy goal programming
Optimal compromise solution
eng
Research Expansion Alliance (REA) on behalf of Ayandegan Institute of Higher Education
Journal of Applied Research on Industrial Engineering
2538-5100
2676-6167
2018-11-01
5
3
253
262
10.22105/jarie.2018.138086.1042
76940
Selection of tugboat gearbox supplier using the analytical hierarchy process method
Astrid Maulidina
astriddiandra.m@gmail.com
1
Fibi Putra
fibiekoputra@gmail.com
2
Faculty of Industrial Technology, Master Program of Industrial Engineering, Mercu Buana University, Jakarta, Indonesia.
Faculty of Industrial Technology, Master Program of Industrial Engineering, Mercu Buana University, Jakarta, Indonesia.
Some company strategies in managing business that can be implemented are Supply Chain Management (SCM). SCM works to ensure the availability of the material obtained from the supplier. With the increasingly advanced information technology in line with the progress in hardware and software technologies, the computing methods are also growing. One of the most important computing methods in its development is the Decision Support System (DSS). Every company is required to move quickly in decision-making or action, similarly, in the selection of suppliers. With reference to the Hierarchy Analytical Process (AHP) method, this research aims to make decisions in the selection of suppliers objectively based on the various criteria set. This is made so that the goods supply process can be run according to the needs of the company as one of the utilization and availability of Tugboat.
https://www.journal-aprie.com/article_76940_088e220835d4df1defbc5232db341ebf.pdf
SCM
Supplier
DSS
AHP
eng
Research Expansion Alliance (REA) on behalf of Ayandegan Institute of Higher Education
Journal of Applied Research on Industrial Engineering
2538-5100
2676-6167
2018-11-01
5
3
263
270
10.22105/jarie.2018.76925
76925
Methodology for retrofitting electric power train in conventional powertrain-based three wheeler
Kiran Patar
pattar.kiranb@gmail.com
1
Praveen Kumar R H
praveenkumar23101996@gmail.com
2
Rahul Raj Jain
rahulrajkjain@gmail.com
3
Sharanbasappa Pati
sspatil@pes.edu
4
Department of Mechanical Engineering, PES Institute of Technology, India.
Department of Mechanical Engineering, PES Institute of Technology, India.
Department of Mechanical Engineering, PES Institute of Technology, India.
Department of Mechanical Engineering, PES Institute of Technology, India.
India is a country of 1.32 billion population with 221 million registered vehicles on the road. Of these, 933950 three wheelers entered service in the year 2015-16 (114% increase from 2005-06). With atmospheric pollution and emission norms in mind, it is essential that we bring down the emission of vehicles. Tail pipe emission reduction is one of the ways to achieve that but, it is a difficult process. This paper explores the alternative. This work describes a methodology for retrofitting the conventional drivetrain of a vehicle with an electric power unit. This work describes the development of a real world drive cycle for three wheeler Autorickshaws in Bengaluru city. For this, the micro trip generation method is employed, which captures the driving conditions encountered by the vehicle on a regular working day. A Bajaj RE 4 stroke CNG vehicle is used as the test vehicle throughout the process. A GPS based data logging system VBOX 3i is used for data acquisition. The vehicle dynamics are simulated to determine the power rating required for the electric motor to retrofit the IC engine using one dimensional longitudinal acceleration analysis. Coast down test results determine aerodynamic drag and rolling resistance coefficients. Dyno test helps us to understand the torque requirements for the electric motor to be retrofitted. The results of the mathematical model and the dyno test are then used to find a suitable electric motor. The adopted methodology in this work can be used to find the suitable power train replacement for any vehicle.
https://www.journal-aprie.com/article_76925_2d692ef5229834804625053b8802fc2b.pdf
Power Train
Drive Cycle
Coast Down Test
Dyno Test
Electric Vehicle
Conversion Methodology