2021-06-14T09:56:50Z
http://www.journal-aprie.com/?_action=export&rf=summon&issue=13595
Journal of Applied Research on Industrial Engineering
J. Appl. Res. Ind. Eng
2538-5100
2538-5100
2019
6
4
Modelling and analysis of 2-stage planetary gear train for modular horizontal wind turbine application
Aniekan
Ikpe
Ekom
Etuk
Azum
Adoh
Wind turbine incorporates a gear box which aids the transmission of torque for the generation of wind energy, industry professionals have streamlined the gearbox design to suite this purpose. Despite the advancement in the gear box design, most wind turbine downtime is attributed to gearbox-related problems. In this study, Finite Element Method through ANSYS R15.0 software was employed in modelling and analysis of a 2-stage planetary gear train for modular horizontal wind turbine. The ring gear was considered as statically constrained member because it is practically fixed to the gearbox housing while the dynamics of the planet gear, planet carrier and the sun pinion were considered as rotating members. Using Factor of Safety (FOS) ranging from 10-15, the gear model was simulated to determine the equivalent stresses, strains and total deformation. The simulation which was conducted for five (5) steps at 2.5 seconds each yielded minimum and maximum Von-mises stress of 10.168 Pa and 5.9889e+009 Pa for the 5th step, minimum and maximum equivalent elastic strain of 5.0839e-011 and 2.9944e-002 for the 5th step and maximum total deformation of 1.7318e-003 m at the 5th step. The findings revealed that the higher the design FOS, the lower the stress-strain deformations, indicating longevity and optimum performance of the gear system. It was observed that increase in contact forces between the meshing gear teeth may cause larger elastic deformations, increasing tooth bending deformation as well as larger backlash on the gear teeth while continuously varying gear mesh stiffness with time can result in excessive vibration and noise.
modelling
Planetary gear
Wind Turbine
Stress
Strain
deformation
FOS
2019
12
01
268
282
http://www.journal-aprie.com/article_100626_10230b4f743ce6a5fb070bb4462aa5a6.pdf
Journal of Applied Research on Industrial Engineering
J. Appl. Res. Ind. Eng
2538-5100
2538-5100
2019
6
4
Ranking aggregation of preferences with common set of weights using goal programming method
Seyed Hamzeh
Mirzaei
In aggregation of preferences system, each decision maker (DM) selects a subset of the alternative and places them in a ranked order. The key issue of the aggregation preference is how to determine the weights associated with different ranking places. To avoid the subjectivity in determining the weights, data envelopment analysis (DEA) is used in Cook and Kress to determine the most favorable weights for each alternative. With respect to DEA-based models, two main criticisms appear in the literature: multiple top-ties and overly diverse weights. DEA models use assignments of the same aggregate value (equal to unity) to evaluate multiple alternatives as efficient. There is no criterion to discriminate among these alternatives in order to construct a ranking of alternatives. furthermore, overly diverse weights can appear, given that each alternative can have its own vector of weights (i.e., the one that maximizes its aggregate value). Thus, the efficiencies of different alternatives obtained by different sets of weights may be unable to be compared and ranked on the same basis In order to solve these two problems above, In order to rank all the alternatives on the same scale, In this paper we proposed an improvement to Kornbluth’s approach by introducing an multiple objective linear programming (MOLP) approach for generating a common set of weights in the DEA framework. In order to solve the MOLP model we use a goal programming (GP) model. solving the GP model gives us a common set of weights and then the efficiency scores of candidate can be obtained by using these common weights and finally we can rank all alternative.
aggregation of preferences
Data Envelopment Analysis
Goal Programming
Common set of weights
Ranking
2019
12
01
283
293
http://www.journal-aprie.com/article_100627_573102f3b3e14fc491ff8bb79b2d957e.pdf
Journal of Applied Research on Industrial Engineering
J. Appl. Res. Ind. Eng
2538-5100
2538-5100
2019
6
4
TPM implementation in automotive component manufacturing companies to analyze efficiency injection machine
Supriyati
.
Humiras
Purba
The development of motorcycle industry in Indonesia is quite rapid. The mode of transportation is a favorite the people of Indonesia, especially in industrial area. The average motorcycle user is a company employee because it facilitates access and avoids traffic. Motorcycle component production in Indonesia is spread across several companies, one of the companies that manufactures components made of plastic material has 16 injection machines. These machines have different performance, when analyzed using the OEE approach it is known that Machine 16 has the lowest performance compared to others at only 91.2%. Factors that affect the low efficiency of the machine due to the 7 biggest losses namely Dandori, Mold Repair, Machine Damage, re-setting, Material jams, robot damage and Cleaning Mold
OEE
Six bg losses
TPM
maintenance
Equipment
2019
12
01
294
313
http://www.journal-aprie.com/article_100628_49e819641c5927869e3bb49fd266f476.pdf
Journal of Applied Research on Industrial Engineering
J. Appl. Res. Ind. Eng
2538-5100
2538-5100
2019
6
4
Combinatorial optimization of permutation-based quadratic assignment problem using optics inspired optimization
Soheila
Badrloo
Ali
Husseinzadeh Kashan
A lot of real-world problems such as the assignment of special rooms in hospitals, operating room layout, image processing, etc., could be formulated in terms of Quadratic assignment problem. Different exact methods are suggested to solve these problems, but because of the special structure of these problems, by increasing the size of the problem, finding an exact solution become more complicated and even impossible. So, employing meta-heuristic algorithms is inevitable, due to this problem we use optics inspired optimization (OIO) in this paper. The obtained results and its comparison with the solutions of the central library of Quadratic assignment problem (QAPLIB) show that the proposed algorithm can exactly solve small-sized problems with 100% efficiency while the efficiency of medium-to-large size instances is 96%. Accordingly, one can conclude that the proposed OIO has generally high efficiency for solving permutation-based problems.
Quadratic assignment problem
Optics inspired optimization
NP-complete
Metaheuristics
2019
12
01
314
332
http://www.journal-aprie.com/article_95859_1136d63853e0d66d7f9f928b43eec2b5.pdf
Journal of Applied Research on Industrial Engineering
J. Appl. Res. Ind. Eng
2538-5100
2538-5100
2019
6
4
Development of a forecasting model for investment in Tehran stock exchange based on seasonal coefficient
Reza
Darvishinia
Hossein
Ebrahimzadeh Shermeh
Samira
Barzkar
The present study aims at suggesting a model for intelligent investment, through enabling us to be Autoregressive Integrated Moving Average of ARIMA and seasonal coefficient. In this study, the researcher uses seasonal fluctuation Model. The previous trend of time series, related to the companies for a period of 11 years, from 2006 to 2017, was carried out based on seasonal data. Then the researcher predicted the final price based on moving average method. In the next stage, the proportion of real final price and predicted the final price is calculated regarding each period. Then, the seasonal coefficient average is calculated for similar seasons. In the final stage, the value of a prediction, for a given period, is calculated when moving average method is multiplied by a seasonal coefficient average. As a result, seasonal coefficient of a given stock is derived.
exchange
investment on exchange
seasonal coefficient
ARIMA time series
2019
12
01
333
366
http://www.journal-aprie.com/article_96786_c3ea58d31595aea0b09f396b201cf27a.pdf
Journal of Applied Research on Industrial Engineering
J. Appl. Res. Ind. Eng
2538-5100
2538-5100
2019
6
4
A nonlinear approach for neutrosophic linear programming
Seyed Ahmad
Edalatpanah
Traditional linearl programming usually handles optimization problems involving deterministic objective functions and/or constrained functions. However, uncertainty also exists in real problems. Hence, many researchers have proposed uncertain optimization methods, such as approaches using fuzzy and stochastic logics, interval numbers, or uncertain variables. However, In practical situations, we often have to handle programming problems involving indeterminate information. The aim of this paper is to put forward two new algorithms, for solving the Single-Valued Neutrosophic linear Problem. A numerical experiments are reported to verify the effectiveness of the new algorithms.
Single valued neutrosophic number
Neutrosophic linear programming problem
Linear programming problem
2019
12
01
367
373
http://www.journal-aprie.com/article_102443_3bbc738df84bff8d262ae807e915a5de.pdf
Journal of Applied Research on Industrial Engineering
J. Appl. Res. Ind. Eng
2538-5100
2538-5100
2019
6
4
Forecasting as a framework for reducing food waste in Ethiopian university canteens
Abdella
Ali
Jemal
Hassen
Gebrekidan
Wendim
This paper uses forecasting model to prevent over production of uneaten food in student’s cafeteria in Woldia University (Ethiopia). Students arrival in the university is highly variable. And it is difficult for the canteen management to estimate the number of students attend the meal during first two weeks of operation. The moving average and exponential smoothing forecasting methods were used to forecast the student’s arrival for the year 2019. Mean absolute deviation (MAD) was used as a measure of forecasting accuracy. Finally, it is found that moving average were more accurate forecasting method than exponential smoothing for forecasting student’s arrival in Woldia University.
moving average
exponential smoothing
student’s arrival
Students cafeteria
Food waste
2019
12
01
374
380
http://www.journal-aprie.com/article_100629_69d80b6f69e1432aa11bf715620aa72e.pdf