Engineering Optimization
Ayodeji Nathaniel Oyedeji; Ibrahim Iliyasu; James Bitrus Bello; Kazeem Adeniyi Salami; Musa Nicholas Dibal; Danjuma S Yawas
Abstract
This study considered the consequence of the length and weight composition percentage of Deleb palm fruit fiber on the physio-mechanical characteristics of an epoxy-based composite through the Taguchi grey relational optimization technique. Considering fiber reinforcement of 30-40 wt% and fiber reinforcement ...
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This study considered the consequence of the length and weight composition percentage of Deleb palm fruit fiber on the physio-mechanical characteristics of an epoxy-based composite through the Taguchi grey relational optimization technique. Considering fiber reinforcement of 30-40 wt% and fiber reinforcement length of 1-5mm, the physical and mechanical properties were determined based on standards. The findings demonstrated that the Deleb palm fruit fiber's characteristics tend to differ from those of other types of fiber reinforcement in that they significantly impact the physio-mechanical characteristics of the resulting epoxy-based reinforced Deleb palm fruit fiber composite. The ANOVA result showed that, at a confidence interval of 5%, the effects of the fiber characteristics on the physio-mechanical properties of the composites were particularly notable for tensile strength and a decrease in water absorption.
Engineering Optimization
Md. Aqib Aman; Md. Mahraj Uddin; Golam Sakaline; Kaushik Debnath; Md. Abu Shahed; Tanver Rahman
Abstract
Bangladesh is blessed with various agro-based natural resources like Date sap, extracted from date trees. As this date sap is found in rural areas in large quantities annually but a very small fraction is converted into some value-added delicious foods at a domestic level while a large portion is left ...
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Bangladesh is blessed with various agro-based natural resources like Date sap, extracted from date trees. As this date sap is found in rural areas in large quantities annually but a very small fraction is converted into some value-added delicious foods at a domestic level while a large portion is left underutilized due to negligence, improper collection, and preservation system from the industry level. The processed delicious foods have conspicuous demand in the national market due to their nutritious value and the growth of the national economy. Despite its economic importance, very little researches have been conducted in this field for its industrial processing. So, this research implies to improve this straggled sector providing much attention for collecting raw sap from source and processing into value-added products from industrial level cost-effectively. The key objectives of this paper are to determine optimal facility location for processing date sap and set vehicle routes that can pick up date sap from source to processing plant simultaneously curtailing operational transportation costs. Initially, a Mixed Integer Linear Programming (MILP) model is introduced to determine optimal facility location. Besides, the Large Neighborhood Search (LNS) algorithm has been used to find the optimal set of vehicle routes. This paper outlines a summary of final results that Jessore (A south-western city in Bangladesh) is an optimal plant location and 10 vehicles are necessary for covering 15 areas which ultimately optimize the total supply time, respecting constraints concerning routing, timing, capacity, and supply as well transportation costs.
Engineering Optimization
Osarobo Osamede Ogbeide; Kolawole Akeredolu; Samuel Ayodeji Omotehinse
Abstract
The service life of engineering structure is mostly affected by the quality and strength of the welded joints. Tensile tests are performed for several reasons. The results are used in selecting materials for engineering applications. Tensile properties are frequently included in material specifications ...
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The service life of engineering structure is mostly affected by the quality and strength of the welded joints. Tensile tests are performed for several reasons. The results are used in selecting materials for engineering applications. Tensile properties are frequently included in material specifications to ensure quality. The tests are measured during development of new materials and processes, so that different materials and processes can be compared. The objective of this study is to predict and optimize the tensile strength of a butt joint weldment on mild steel plate using Response Surface Methodology (RSM). The RSM was applied to predict and optimize the maximum tensile strength of a butt joint weldment on an I-section mild steel plate using Tungsten Inert Gas (TIG) welding process. The mild steel plate was cut into dimension 60mm x 40mm x 10mm with a power hacksaw, grinded and cleaned before the welding process. The experimental matrix was made of twenty (20) runs, generated by the design expert 11.1.0.1 software adopting the central composite design. The response (tensile strength) was measured and then modelled using the RSM. The result obtained show that the current and voltage has a very strong influence on the tensile strength. Based on the findings, the maximum tensile strength of 450Mpa was attained at the welding voltage (V) of 24V, current of 170A and gas flow rate of 13lit/min respectively. This study will serve as a guide to welding operators on parameter settings selection.
Engineering Optimization
Okwuchi Smith Onyekwere; Mobolaji Humphrey Oladeinde; Raphael Olumese Edokpia
Abstract
In composite production, hydrophilic nature of plant fibres results in poor interfacial adhesion between polar-hydrophilic fibre and non-polar-hydrophobic matrix and dimensional instability of the resulting product. Therefore, there is need to reduce the percentage of water absorption of natural fibres ...
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In composite production, hydrophilic nature of plant fibres results in poor interfacial adhesion between polar-hydrophilic fibre and non-polar-hydrophobic matrix and dimensional instability of the resulting product. Therefore, there is need to reduce the percentage of water absorption of natural fibres before incorporating them in composite. Bamboo fibre polyester composites were subjected to three modification treatments which are mercerization, acetylation and mercerized-acetylation at fibre content levels of 10, 20 30, 40 and 50 wt % in order to reduce the moisture absorption of the composites. Taguchi method was used to optimize the parameter settings for reduced moisture absorption. The diffusion coefficient, absorption coefficient and permeability coefficient of the composites for each fibre treatment was used to study the absorption kinetics. Mercerized-acetylated fibre composites show the best moisture absorption performance among all the considered treatments. The application of optimization techniques and statistical analysis was used to improve the processes of bamboo fibre polyester composite production in order to achieve improved moisture degradation behavior of the composite and promote the expansion of natural fibres application in engineering.
Engineering Optimization
Okwuchi Smith Onyekwere; Mobolaji Humphrey Oladeinde; Kindness Alfred Uyanga
Abstract
There is great interest in application of natural fibres, such as bamboo fibre, as reinforcement in composite production. Herein, to achieve high performance under optimum process conditions, experimental design and optimization techniques are used to investigate the best parameter settings for processing ...
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There is great interest in application of natural fibres, such as bamboo fibre, as reinforcement in composite production. Herein, to achieve high performance under optimum process conditions, experimental design and optimization techniques are used to investigate the best parameter settings for processing bamboo fibre polyester composites. Single response optimization of the properties of bamboo fibre polyester composites using Taguchi orthogonal array, analysis of variance and Post hoc test was carried out. The test samples comprised of untreated, mercerized, acetylated and mercerized-acetylated bamboo fibre composites at fibre contents of 10, 20, 30, 40, and 50 wt %. All composite samples were fabricated using conventional hand lay-up process on randomly oriented long bamboo fibres. It was found that optimum parameter setting for impact strength was achieved at mercerization treatment and 30wt% fibre content with impact strength of 158.23 J/cm. For flexural strength, optimum parameter setting was found to be mercerization treatment at 50 wt % level of fibre content which resulted to flexural strength of 62.7 MPa. The optimum parameter setting for tensile strength is observed at mercerized-acetylation treatment at 50 wt% fibre content with tensile strength of 72.96 MPa. However, no significant difference, (P <.005) was observed in flexural strength, tensile strength and impact strength of mercerized and mercerized-acetylated fibre composites. This study established a research approach to improve bamboo fibre composite properties for more extended applications and to obtain optimal operating conditions by using optimization techniques. It will also serve as a guide for composite manufacturers on parameter settings selection.
Engineering Optimization
Danisment Vural; Erkan Kose
Abstract
Bed production has an important market in the furniture sector. In spite of the fact that sponge is generally preferred as filler in the production process of beds, increasing prices in recent years and the preference of new materials with the development of alternative filling materials have increased. ...
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Bed production has an important market in the furniture sector. In spite of the fact that sponge is generally preferred as filler in the production process of beds, increasing prices in recent years and the preference of new materials with the development of alternative filling materials have increased. Recently it is seen other than sponge, the granule, wadding, and STW are also used as filling material in bed production. From the management point of view, the choice of filler is an important decision problem that depends on the situation of the business and many objective and subjective criteria must be taken into consideration. It is appropriate to examine such a problem with the Analytical Hierarchy Method (AHP) and the ELECTRE method, which have the ability to make quantitative evaluations and synthesize factor weights from subjective judgments. The criteria for selection of the filler material and the extent to which the criterion will affect the evaluation are important decision points. The opinions of experts in bed production were consulted to determine the criteria to be used in the evaluation. The obtained results show that four basic criteria must be taken into consideration in the selection of filler material. In this study, AHP was used for determining the criteria weights, and ELECTRE methods were used for the selection of the best filling material. The results showed that wadding is the optimum filler material for bed production.
Engineering Optimization
Suresh Aluvihara; Jagath K. Premachandra
Abstract
Crude oil is an energy resource that mostly composed with hydrocarbons and trace corrosive compounds as well found some cruxes in the petroleum refining industry because of the vast applications of the different types of metals. There were expected to investigate the effect of two different types of ...
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Crude oil is an energy resource that mostly composed with hydrocarbons and trace corrosive compounds as well found some cruxes in the petroleum refining industry because of the vast applications of the different types of metals. There were expected to investigate the effect of two different types of crude oils on the corrosion of seven types of selected ferrous metals in the pertinent research. The concerned corrosive properties of both crude oils were tested by standard methods and instruments also the chemical compositions of selected ferrous metals were tested. The corrosion rates of a series of similar size prepared metal coupons were tested after limited immersion time periods as three trials in crude oils by the weight loss method since aiding the microscopic analysis to identify the corrosion compounds. Apart from those speculations the decayed metallic elemental mounts from the metals into crude oils and the reductions of the initial hardness of metal coupons were tested. The obligatory results showed the relatively higher corrosion rates from carbon steels, relatively lower corrosion rates from stainless steels in both crude oils, formation of FeS in most of observations, decay of ferrous and copper into crude oils from some metals and slight reductions of the initial hardness of metal coupons due to the formation of the corrosion on the metal surfaces.
Engineering Optimization
Burak Omer Saracoglu; Miguel De Simón Martín
Abstract
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: ...
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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.
Engineering Optimization
Yudi Prastyo; Wahyu Adhi Yatma; Hernadewita Hernadewita
Abstract
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 ...
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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.
Engineering Optimization
Amir Parnianifard; Siti Azfanizam Ahmad; Mohd Khairol Anuar Ariffin; Mohd Idris Shah Ismail
Abstract
Computational complexity and time-consuming iteration of simulation for tuning of Proportional-Integral-Derivative (PID) controller is a common drawback in many types of existing methods. This paper aims to propose a new method for achieving an optimal design for PID gains parameters with the least number ...
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Computational complexity and time-consuming iteration of simulation for tuning of Proportional-Integral-Derivative (PID) controller is a common drawback in many types of existing methods. This paper aims to propose a new method for achieving an optimal design for PID gains parameters with the least number of simulation runs. To achieve this purpose, we combine polynomial regression and Latin Hypercube Sampling (LHS) in order to Design and Analyze of Computer Experiments (DACE). In this method, the LHS is performed three times to design the associated sample points for different usage that includes training sample points to fit polynomial regression as a common surrogate model; validating sample points to scale standardized residuals; grid search sample points for investigating optimal point over whole design space. To show the flexibility and applicability of the proposed method, we serve a numerical case in the tuning of PID controller for linear speed control of Direct Current (DC) motor. Four different polynomial regression fit input/output (I/O) data over separately four model’s performances that includes Integral-Square-Error (ISE), Integral-Absolute-error (IAE), Integral-Time-Square-Error (ITSE), and Integral-Time-Absolute-Error (ITAE). Comparison of the result with two existing approaches such as traditional Zeigler-Nichols method and Taguchi-Gray Relational Analysis (Taguchi-GRA) confirms the reliability and superiority of the proposed method.
Engineering Optimization
Ala’ K. Abu-Rumman; Iyad Muslih; Mahmoud. A. Barghash
Abstract
Life cycle costing (LCC) is a methodology used first time by the Department of Defense of United State, it’s an economic calculation of all costs propagated during the life span of any technical system. For Renewable Energy (RE) systems, LCC is a good methodology, which shows the cost-effectiveness ...
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Life cycle costing (LCC) is a methodology used first time by the Department of Defense of United State, it’s an economic calculation of all costs propagated during the life span of any technical system. For Renewable Energy (RE) systems, LCC is a good methodology, which shows the cost-effectiveness of using RE as an alternative source compared to conventional power generations. A LCC model was introduced for PV generation system. Data collection was done through four different cost data sources. The results shows that the average module price is $0.56/Wp and the capital investment cost is $1.184/Wp. For a 20 years PV project life-time, the operation and maintenance cost forms 27% of the total LCC of the system.
