Search results for: pareto ANOVA

Authors: Brahim Boukabcha, Amar Rebbouh

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The bootstrap method based on the idea of exploiting all the information provided by the initial sample, allows us to study the properties of estimators. In this article we will present a theoretical study on the different methods of bootstrapping and using the technique of re-sampling in statistics inference to calculate the standard error of means of an estimator and determining a confidence interval for an estimated parameter. We apply these methods tested in the regression models and Pareto model, giving the best approximations.

Keywords: bootstrap, error standard, bias, jackknife, mean, median, variance, confidence interval, regression models

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Authors: Nelson Igaba, C. Onaga, S. Hlongwane

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Background: Medical Male Circumcision (MMC) is part of a comprehensive HIV prevention strategy. The quality of MMC done at Right To Care (RtC) sites is maintained by Continuous Quality Improvement (CQI) based on findings of assessments by internal and independent external assessors who evaluate such parameters as the quality of the surgical procedure, infection control, etc. There are 12 RtC MMC teams in Mpumalanga, two of which are headed by Medical Officers and 10 by Clinical Associates (Clin A). Objectives: To compare the quality (i) of care rendered at doctor headed sites (DHS) versus Clin A headed sites (CHS); (ii) of CQI assessments (external versus internal). Methodology: A retrospective review of data from RightMax™ (a novel RtC data management system) and CQI reports (external and internal) was done. CQI assessment scores of October 2015 and October 2016 were taken as the baseline and latest respectively. Four sites with 745-810 circumcisions per annum were purposively selected; the two DHS (group A) and two CHS (group B). Statistical analyses were conducted using R (2017 version). Results: There were no significant difference in latest CQI scores between the two groups (DHS and CHS) (Anova, F = 1.97, df = 1, P = 0.165); between internal and external CQI assessment scores (Anova, F = 2.251, df = 1, P = 0.139) or among the individual sites (Anova, F = 1.095, df = 2, P = 0.341). Of the total of 16 adverse events reported by the four sites in the 12 months reviewed (all were infections), there was no statistical evidence that the documented severity of the infection was different for DHS and CHS (Fisher’s exact test, p-value = 0.269). Conclusion: At RtC VMMC sites in Mpumalanga, internal and external/independent CQI assessments are comparable, and quality of care of VMMC is standardized with the performance of well-supervised clinical associates comparing well with those of medical officers.

Keywords: adverse events, Right to Care, male medical circumcision, continuous quality improvement

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Authors: Ritesh Joshi, Kishan Fuse, Gopal Zinzala, Nishit Nirmal

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Ti-6Al-4V is a titanium alloy having high strength, low weight and corrosion resistant which is a required characteristic for a material to be used in aerospace industry. Titanium, being a hard alloy is difficult to the machine via conventional methods, so it is a call to use non-conventional processes. In present work, the effects on Ti-6Al-4V by drilling a hole of Ø 6 mm using copper (99%) electrode in Electric Discharge Machining (EDM) process is analyzed. Effect of various input parameters like peak current, pulse-on time and pulse-off time on output parameters viz material removal rate (MRR) and electrode wear rate (EWR) is studied. Multi-objective optimization technique Grey relational analysis is used for process optimization. Experiments are designed using an L9 orthogonal array. ANOVA is used for finding most contributing parameter followed by confirmation tests for validating the results. Improvement of 7.45% in gray relational grade is observed.

Keywords: ANOVA, electric discharge machining, grey relational analysis, Ti-6Al-4V

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Authors: Shweta K. Vyas, Rakesh Musale, Sanjeev R. Shukla

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Eri silk is a non mulberry silk which is obtained without killing the silkworms and hence it is also known as Ahmisa silk. In the present study, the results on degumming of eri silk with alkaline peroxide have been compared with those obtained by using ionic liquid (IL) 1-Butyl-3-methylimidazolium chloride [BMIM]Cl. Experiments were designed to find out the optimum processing parameters for degumming of eri silk by response surface methodology. The statistical software, Design-Expert 6.0 was used for regression analysis and graphical analysis of the responses obtained by running the set of designed experiments. Analysis of variance (ANOVA) was used to estimate the statistical parameters. The polynomial equation of quadratic order was employed to fit the experimental data. The quality and model terms were evaluated by F-test. Three dimensional surface plots were prepared to study the effect of variables on different responses. The optimum conditions for IL treatment were selected from predicted combinations and the experiments were repeated under these conditions to determine the reproducibility.

Keywords: silk degumming, ionic liquid, response surface methodology, ANOVA

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Authors: Sima Hassankhali, Ildar Sadeqi

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In the theory of Pareto efficient points, the existence of a bounded base for a cone K of a normed space X is so important. In this article, we study the geometric structure of a nonzero closed convex cone K with a bounded base. For this aim, we study the structure of the polar cone K# of K. Furthermore, we obtain a necessary and sufficient condition for a nonempty closed convex set C so that its recession cone C∞ has a bounded base.

Keywords: solid cones, recession cones, polar cones, bounded base

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Authors: Azhar Equbal, Anoop Kumar Sood, M. Asif Equbal, M. Israr Equbal

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In the present work response surface methodology (RSM) based central composite design (CCD) is used for analyzing the electrical discharge machining (EDM) process. For experimentation, mild steel is selected as work piece and copper is used as electrode. Three machining parameters namely current (I), spark on time (T_on) and spark off time (T_off) are selected as the input variables. The output or response chosen is material removal rate (MRR) which is to be maximized. To reduce the number of runs face centered central composite design (FCCCD) was used. ANOVA was used to determine the significance of parameter and interactions. The suitability of model is tested using Anderson darling (AD) plot. The results conclude that different parameters considered i.e. current, pulse on and pulse off time; all have dominant effect on the MRR. At last, the optimized parameter setting for maximizing MRR is found through main effect plot analysis.

Keywords: EDM, electrode, MRR, RSM, ANOVA

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Authors: Svetlana Pushkar, Oleg Verbitsky

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An energy-conscious design for a classroom in a hot-humid climate is reanalyzed. The hypothesis of this study is that use of photovoltaic (PV) electricity generation in building operation energy consumption will lead to re-analysis of the energy-conscious design. Therefore, the objective of this study is to reanalyze the energy-conscious design by evaluating the environmental impact of operational energy with PV electrical generation. Using the hierarchical design structure of Eco-indicator 99, the alternatives for energy-conscious variables are statistically evaluated by applying a two-stage nested (hierarchical) ANOVA. The recommendations for the preferred solutions for application of glazing types, wall insulation, roof insulation, window size, roof mass, and window shading design alternatives were changed (for example, glazing type recommendations were changed from low-emissivity glazing, green, and double- glazed windows to low-emissivity glazing only), whereas the applications for the lighting control system and infiltration are not changed. Such analysis of operational energy can be defined as environment-conscious analysis.

Keywords: ANOVA, Eco-Indicator 99, energy-conscious design, hot–humid climate, photovoltaic

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Authors: Shannon Hashemi, Alireza Daneshfar

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Accounting ethical awareness has been widely promoted in recent years both in academia and in practice. However, the effectiveness of ethical awareness on accountants' judgment and choice of action is still debatable. This study investigates whether Machiavellianism and gender, as significant personality factors, influence the effect of ethical awareness on accountants' decision-making. Using an experiment, the results of ANOVA tests show that although introducing ethical awareness positively influences the accountants' judgment and choice of action, such an effect is significantly moderated by the accountants' Machiavellianism score and gender. Specifically, the test results show that the effect of introducing ethical awareness was higher on males with low Machiavellian score. The results also show that when the Machiavellian scores were high, the effect of ethical awareness was lower for both males and females. Applications of the results are discussed for accounting professionals as well as accounting ethics educators and researchers.

Keywords: ethical awareness, accounting decision making, Machiavellianism, ANOVA, ethics, accounting education

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Authors: Mohammad Reza Esmaili

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One of the most important parts of the restoration process of a power network is the synchronizing of its subsystems. In this situation, the biggest concern of the system operators will be the reduction of the standing phase angle (SPA) between the endpoints of the two islands. In this regard, the system operators perform various actions and maneuvers so that the synchronization operation of the subsystems is successfully carried out and the system finally reaches acceptable stability. The most common of these actions include load control, generation control and, in some cases, changing the network topology. Although these maneuvers are simple and common, due to the weak network and extreme load changes, the restoration will be associated with low speed. One of the best ways to control the SPA is to use FACTS devices. By applying a soft control signal, these tools can reduce the SPA between two subsystems with more speed and accuracy, and the synchronization process can be done in less time. Meanwhile, the unified power controller (UPFC), a series-parallel compensator device with the change of transmission line power and proper adjustment of the phase angle, will be the proposed option in order to realize the subject of this research. Therefore, with the optimal placement of UPFC in a power system, in addition to improving the normal conditions of the system, it is expected to be effective in reducing the SPA during power system restoration. Therefore, the presented paper provides an optimal structure to coordinate the three problems of improving the division of subsystems, reducing the SPA and optimal power flow with the aim of determining the optimal location of UPFC and optimal subsystems. The proposed objective functions in this paper include maximizing the quality of the subsystems, reducing the SPA at the endpoints of the subsystems, and reducing the losses of the power system. Since there will be a possibility of creating contradictions in the simultaneous optimization of the proposed objective functions, the structure of the proposed optimization problem is introduced as a non-linear multi-objective problem, and the Pareto optimization method is used to solve it. The innovative technique proposed to implement the optimization process of the mentioned problem is an optimization algorithm called the water cycle (WCA). To evaluate the proposed method, the IEEE 39 bus power system will be used.

Keywords: UPFC, SPA, water cycle algorithm, multi-objective problem, pareto

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Authors: Svetlana Pushkar

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Eco-indicator 99 (EI99) considers fundamental life cycle assessment (LCA) uncertainties via egalitarian/egalitarian (e/e), hierarchist/hierarchist (h/h), individualist/individualist (i/i), individualist/average (i/a), egalitarian/average (e/a), and hierarchist/average (h/a) methodological options. The objective of this study is to provide a reliable two-stage nested mixed balanced Analysis of Variance (ANOVA) test as a supplemental test to EI99 to address the problematic combination of similarly and not similarly produced materials usually found in building technologies. The robustness of the test was determined from both the “EI99 (all options)” stage (including e/e, i/i, h/h, e/a, i/a, and h/a - all methodological options) and the “EI99 (perspectives)” stage (including e/e, i/i, and h/h methodological options of EI99 - the methodological options with their particular weighting set or e/a, i/a, and h/a methodological options of EI99 - the methodological options with the average weighting set) of evaluating building technologies.

Keywords: building technologies, LCA uncertainty, Eco-indicator 99, two-stage nested mixed ANOVA test

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Authors: Balkar Singh, Gurpreet Singh, Vivek Aggarwal, Sehijpal Singh

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The present research focused to improve the machinability of Hastelloy C-276 at different machining speeds such as 31, 55, and 79 m/min. The use of CO2 gas and Minimum quantity lubrication (MQL) was applied as coolant and lubrication purposes to enhance the machinability of the superalloy. The output in the form of surface roughness (S.R) and heat generation was monitored under dry, MQL, and MQL-CO2-cooled conditions. The Design of the Experiment was prepared using MINITAB software utilizing Taguchi L-27 orthogonal arrays followed by ANOVA analysis for finding the impact of input variables on output responses. At different speeds and lubrication conditions, different behavioral patterns for Surface Roughness and the temperature was observed. ANOVA analysis depicted that the cooling environment impacted the S.R. majorly (50%) followed by cutting speed (29.84%), feed rate (5.09%), and least through depth of cut (4.95%). On the other side, the temperature was greatly influenced by cutting speed (69.12%), Cryo-MQL (8.09%), feed rate (7.59%), and depth of cut (6.20%). Experimental results revealed that Cryo-MQL cooling enhanced the Surface roughness by 12% compared to MQL condition.

Keywords: Hastelloy C-276, minimum quantity lubrication, olive oil, cryogenic Cooling (CO2)

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Authors: Svetlana Pushkar, Oleg Verbitsky

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The goal of the present study is to evaluate environmental damage from four wall technologies under the following conditions: four climate zones in Israel, two building (conventional vs. low-energy) types, and two types of fuel source [natural gas vs. photovoltaic (PV)]. The hierarchical ReCiPe method with a two-stage nested (hierarchical) ANOVA test is applied. It was revealed that in a hot climate in Israel in a conventional building fueled by natural gas, OE is dominant (90 %) over the P&C stage (10 %); in a mild climate in Israel in a low-energy building with PV, the P&C stage is dominant (85 %) over the OE stage (15 %). It is concluded that if PV is used in the building sector in Israel, (i) the P&C stage becomes a significant factor that influences the environment, (ii) autoclaved aerated block is the best external wall technology, and (iii) a two-stage nested mixed ANOVA can be used to evaluate environmental damage via ReCiPe when wall technologies are compared.

Keywords: life cycle assessment (LCA), photovoltaic, ReCiPe method, residential buildings

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Authors: Lingaraju Dumpala, Narasa Raju Gosangi

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Friction Stir Welding (FSW) is relatively new, environmentally friendly, versatile, and widely used joining technique for soft materials such as aluminum. FSW has got a lot of attention as a solid-state joining method which avoids many common problems of fusion welding and provides an improved way of producing aluminum joints in a faster way. FSW can be used for various aerospace, defense, automotive and transportation applications. It is necessary to understand the friction stir welded joints and its characteristics to use this new joining technique in critical applications. This study investigated the mechanical properties of friction stir welded aluminum 6063 alloys. FSW is carried out based on the design of experiments using L16 mixed level array by considering tool rotational speeds, tool feed rate and tool tilt angles as process parameters. The optimization of process parameters is carried by Taguchi based regression analysis and the significance of process parameters is analyzed using ANOVA. It is observed that the considered process parameters are high influences the mechanical properties of Al6063.

Keywords: FSW, aluminum alloy, mechanical properties, optimization, Taguchi, ANOVA

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Authors: Tosin Emmanuel Akinduyo, F. O. Ojewola

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This study investigated the influence of age and religion on the sexual behaviours of undergraduates in southwest Nigeria. The aim of this study is to examine the sexual behaviour of undergraduates based on moderating variables of age and religion. The research design was a descriptive research design of the survey type. The sample for the study was 1,200 undergraduates selected through a multi-stage sampling procedure. A self-constructed questionnaire titled “Sexual Behaviours Questionnaire” (SBCUQ) with Pearson reliability (r) of 0.68 was used to elicit information from the respondents. Two research questions were answered using frequency count, percentage, means, and standard deviation. The two hypotheses were tested using t-test and ANOVA. Where the result of ANOVA showed a significant difference, the Scheffe Posthoc test was used to show where the significant difference (s) occurred. The findings of the study revealed that age and religion influenced undergraduates’ sexual behaviour. Based on the findings, the government at all tiers, in collaboration with the university management, should introduce sex education as a course to enlighten undergraduates and inform them of moderation needed as expected in their sexual expressions. Professional counsellors and religious organizations should always line up seminars and workshops for undergraduates on acceptable engagement in their sexual behaviours.

Keywords: age, religion, sexual behaviuors, undergraduates

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Authors: Navajyoti Panda, R. S. Pawar

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In this study, process parameters like punch angle, die opening, grain direction, and pre-bend condition of the strip for deep draw of high strength low alloy steel HSLA 420 are investigated. The finite element method (FEM) in association with the Taguchi and the analysis of variance (ANOVA) techniques are carried out to investigate the degree of importance of process parameters in V-bending process for HSLA 420&ST12 grade material. From results, it is observed that punch angle had a major influence on the spring-back. Die opening also showed very significant role on spring back. On the other hand, it is revealed that grain direction had the least impact on spring back; however, if strip from flat sheet is taken, then it is less prone to spring back as compared to the strip from sheet metal coil. HyperForm software is used for FEM simulation and experiments are designed using Taguchi method. Percentage contribution of the parameters is obtained through the ANOVA techniques.

Keywords: bending, spring-back, v-bending, FEM, Taguchi, HSLA 420 and St12 materials, HyperForm, profile projector

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Authors: M. J. Davidson, N. Selvaraj, L. Venugopal

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The elevated temperature forming studies on the expansion of thin walled tubes have been studied in the present work. The influence of process parameters namely the die angle, the die ratio and the operating temperatures on the expansion of tube ends at elevated temperatures is carried out. The range of operating parameters have been identified by perfoming extensive simulation studies. The hot forming parameters have been evaluated for AA2014 alloy for performing the simulation studies. Experimental matrix has been developed from the feasible range got from the simulation results. The design of experiments is used for the optimization of process parameters. Response Surface Method’s (RSM) and Box-Behenken design (BBD) is used for developing the mathematical model for expansion. Analysis of variance (ANOVA) is used to analyze the influence of process parameters on the expansion of tube ends. The effect of various process combinations of expansion are analyzed through graphical representations. The developed model is found to be appropriate as the coefficient of determination value is very high and is equal to 0.9726. The predicted values are found to coincide well with the experimental results, within acceptable error limits.

Keywords: expansion, optimization, Response Surface Method (RSM), ANOVA, bbd, residuals, regression, tube

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Authors: Varsha Singh, Kishan Fuse

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This paper presents a study of the grey-Taguchi method to optimize CNC milling parameters of AA6061 T6 aluminium alloy. Grey-Taguchi method combines Taguchi method based design of experiments (DOE) with grey relational analysis (GRA). Multi-response optimization of different quality characteristics as surface roughness, material removal rate, cutting forces is done using grey relational analysis (GRA). The milling parameters considered for experiments include cutting speed, feed per tooth, and depth of cut. Each parameter with three levels is selected. A grey relational grade is used to estimate overall quality characteristics performance. The Taguchi’s L9 orthogonal array is used for design of experiments. MINITAB 17 software is used for optimization. Analysis of variance (ANOVA) is used to identify most influencing parameter. The experimental results show that grey relational analysis is effective method for optimizing multi-response characteristics. Optimum results are finally validated by performing confirmation test.

Keywords: ANOVA, CNC milling, grey relational analysis, multi-response optimization

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Authors: Konstantinos Metaxiotis, Konstantinos Liagkouras

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The objective of this study is to examine the performance of three well-known multiobjective evolutionary algorithms for solving optimization problems. The first algorithm is the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), the second one is the Strength Pareto Evolutionary Algorithm 2 (SPEA-2), and the third one is the Multiobjective Evolutionary Algorithms based on decomposition (MOEA/D). The examined multiobjective algorithms are analyzed and tested on the ZDT set of test functions by three performance metrics. The results indicate that the NSGA-II performs better than the other two algorithms based on three performance metrics.

Keywords: MOEAs, multiobjective optimization, ZDT test functions, evolutionary algorithms

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Authors: Ashish Ankus Yerunkar, Ravi Terkar

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Study aimed at evaluating the best process environment which could simultaneously satisfy requirements of both quality as well as productivity with special emphasis on reduction of cutting tool flank wear, because reduction in flank wear ensures increase in tool life. The predicted optimal setting ensured minimization of surface roughness. Purpose of this paper is focused on the analysis of optimum cutting conditions to get lowest surface roughness in turning SCM 440 alloy steel by Taguchi method. Design for the experiment was done using Taguchi method and 18 experiments were designed by this process and experiments conducted. The results are analyzed using ANOVA method. Taguchi method has depicted that the depth of cut has significant role to play in producing lower surface roughness followed by feed. The Cutting speed has lesser role on surface roughness from the tests. The vibrations of the machine tool, tool chattering are the other factors which may contribute poor surface roughness to the results and such factors ignored for analyses. The inferences by this method will be useful to other researches for similar type of study and may be vital for further research on tool vibrations, cutting forces etc.

Keywords: surface roughness (ra), machining, dry turning, taguchi method, turning process, anova method, mahr perthometer

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Authors: Luis E. Zapata, Sergio Ruiz, María F. Mantilla, Jhon A. Villamizar

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Sand as fine aggregate for concrete production needs a feasible substitute due to several environmental issues. In this work, a study of the behavior of self-compacting concrete mixtures under replacement of sand by iron slag from 0.0% to 50.0% of weight and variations of water/cementitious material ratio between 0.3 and 0.5 is presented. Control fresh state tests of Slump flow, T500, J-ring and L-box were determined. In the hardened state, compressive strength was determined and optimization from response surface analysis was performed. The study of the variables in the hardened state was developed based on inferential statistical analyses using central composite design methodology and posterior analyses of variance (ANOVA). An increase in the compressive strength up to 50% higher than control mixtures at 7, 14, and 28 days of maturity was the most relevant result regarding the presence of iron slag as replacement of natural sand. Considering the obtained result, it is possible to infer that iron slag is an acceptable alternative replacement material of the natural fine aggregate to be used in structural concrete.

Keywords: ANOVA, iron slag, response surface analysis, self-compacting concrete

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Authors: Sidharth Talan, Devendra Kumar Yadav, Yuvraj Singh Rajput, Subhajit Bhattacharjee

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Mining industry is known for its appetite to spend sizeable capital on mine equipment. However, in the current scenario, the mining industry is challenged by daunting factors of non-uniform geological conditions, uneven ore grade, uncontrollable and volatile mineral commodity prices and the ever increasing quest to optimize the capital and operational costs. Thus, the role of equipment reliability and maintenance planning inherits a significant role in augmenting the equipment availability for the operation and in turn boosting the mine productivity. This paper presents the Risk Based Maintenance (RBM) planning conducted on mine loading equipment namely Load Haul Dumpers (LHDs) at Vedanta Resources Ltd subsidiary Hindustan Zinc Limited operated Sindesar Khurd Mines, an underground zinc and lead mine situated in Dariba, Rajasthan, India. The mining equipment at the location is maintained by the Original Equipment Manufacturers (OEMs) namely Sandvik and Atlas Copco, who carry out the maintenance and inspection operations for the equipment. Based on the downtime data extracted for the equipment fleet over the period of 6 months spanning from 1^st January 2017 until 30^th June 2017, it was revealed that significant contribution of three downtime issues related to namely Engine, Hydraulics, and Transmission to be common among all the loading equipment fleet and substantiated by Pareto Analysis. Further scrutiny through Bubble Matrix Analysis of the given factors revealed the major influence of selective factors namely Overheating, No Load Taken (NTL) issues, Gear Changing issues and Hose Puncture and leakage issues. Utilizing the equipment wise analysis of all the downtime factors obtained, spares consumed, and the alarm logs extracted from the machines, technical design changes in the equipment and pre shift critical alarms checklist were proposed for the equipment maintenance. The given analysis is beneficial to allow OEMs or mine management to focus on the critical issues hampering the reliability of mine equipment and design necessary maintenance strategies to mitigate them.

Keywords: bubble matrix analysis, LHDs, OEMs, Pareto chart analysis, spares consumption matrix, critical alarms checklist

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Authors: Mary Joy B. Amoguis, Alonah Jane D. Labtic, Hyna Wary Namoca, Aira Jane V. Original

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Animal waste has been rapidly increasing due to the growing animal population and the lack of innovative waste management practices. In a country like the Philippines, animal waste is rampant. This study aims to minimize animal waste by producing garden bricks using cat stool as an additive. The research study analyzes different levels of concentration to determine the most efficient combination in terms of compressive strength and durability of cat stool as an additive to garden bricks. The researcher's first collects the cat stool and incinerates the different concentrations. The first concentration is 25% cat stool and 75% cement mixture. The second concentration is 50% cat stool and 50% cement mixture. And the third concentration is 75% cat stool and 25% cement mixture. The researchers analyze the statistical data using one-way ANOVA, and the statistical analysis revealed a significant difference compared to the controlled variable. The research findings show an inversely proportional relationship: the higher the concentration of cat stool additive, the lower the compressive strength of the bricks, and the lower the concentration of cat stool additive, the higher the compressive strength of the bricks.

Keywords: cat stool, garden bricks, cement, concentrations, animal wastes, compressive strength, durability, one-way ANOVA, additive, incineration, aggregates, stray cats

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Authors: Babak H. Tabrizi, Seyed Farid Ghaderi

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Concurrent planning of project scheduling and material ordering has been increasingly addressed within last decades as an approach to improve the project execution costs. Therefore, we have taken the problem into consideration in this paper, aiming to maximize schedules quality robustness, in addition to minimize the relevant costs. In this regard, a bi-objective mathematical model is developed to formulate the problem. Moreover, it is possible to utilize the all-unit discount for materials purchasing. The problem is then solved by the constraint method, and the Pareto front is obtained for a variety of robustness values. The applicability and efficiency of the proposed model is tested by different numerical instances, finally.

Keywords: e-constraint method, material ordering, project management, project scheduling

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Authors: Restituto I. Rodelas

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The higher education has adopted the outcomes-based education from K-12. In this approach, the teacher uses any teaching and learning strategies that enable the students to achieve the learning outcomes. The students may be required to exert more effort and figure things out on their own. Hence, outcomes-based students are assumed to be more responsible and more capable of applying the knowledge learned. Another approach that the higher education in the Philippines is starting to adopt from other countries is blended learning. This combination of classroom and fully online instruction and learning is expected to be more effective. Participating in the online sessions, however, is entirely up to the students. Thus, the effect of blended learning on the performance of students in Statistics may be mediated by outcomes-based education. If there is a significant positive mediating effect, then blended learning can be optimized by integrating outcomes-based education. In this study, the sample will consist of four blended learning Statistics classes at Jose Rizal University in the second semester of AY 2015–2016. Two of these classes will be assigned randomly to the experimental group that will be handled using outcomes-based education. The two classes in the control group will be handled using the traditional lecture approach. Prior to the discussion of the first topic, a pre-test will be administered. The same test will be given as posttest after the last topic is covered. In order to establish equality of the groups’ initial knowledge, single factor ANOVA of the pretest scores will be performed. Single factor ANOVA of the posttest-pretest score differences will also be conducted to compare the performance of the experimental and control groups. When a significant difference is obtained in any of these ANOVAs, post hoc analysis will be done using Tukey's honestly significant difference test (HSD). Mediating effect will be evaluated using correlation and regression analyses. The groups’ initial knowledge are equal when the result of pretest scores ANOVA is not significant. If the result of score differences ANOVA is significant and the post hoc test indicates that the classes in the experimental group have significantly different scores from those in the control group, then outcomes-based education has a positive effect. Let blended learning be the independent variable (IV), outcomes-based education be the mediating variable (MV), and score difference be the dependent variable (DV). There is mediating effect when the following requirements are satisfied: significant correlation of IV to DV, significant correlation of IV to MV, significant relationship of MV to DV when both IV and MV are predictors in a regression model, and the absolute value of the coefficient of IV as sole predictor is larger than that when both IV and MV are predictors. With a positive mediating effect of outcomes-base education on the effect of blended learning on student performance, it will be recommended to integrate outcomes-based education into blended learning. This will yield the best learning results.

Keywords: outcome-based teaching, blended learning, face-to-face, student-centered

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Authors: Makram Ben Jeddou

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The ABC classification is widely used by managers for inventory control. The classical ABC classification is based on the Pareto principle and according to the criterion of the annual use value only. Single criterion classification is often insufficient for a closely inventory control. Multi-criteria inventory classification models have been proposed by researchers in order to take into account other important criteria. From these models, we will consider the ZF model in order to make a sensitive analysis on the composite score calculated for each item. In fact, this score based on a normalized average between a good and a bad optimized index can affect the ABC items classification. We will then focus on the weights assigned to each index and propose a classification compromise.

Keywords: ABC classification, multi criteria inventory classification models, ZF-model

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Authors: Kostas Metaxiotis, Kostas Liagkouras

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This study presents an Expert System specially designed to be used with Multiobjective Evolutionary Algorithms (MOEAs) for the solution of the portfolio selection problem. The validation of the proposed hybrid System is done by using data sets from Hang Seng 31 in Hong Kong, DAX 100 in Germany and FTSE 100 in UK. The performance of the proposed system is assessed in comparison with the Non-dominated Sorting Genetic Algorithm II (NSGAII). The evaluation of the performance is based on different performance metrics that evaluate both the proximity of the solutions to the Pareto front and their dispersion on it. The results show that the proposed hybrid system is efficient for the solution of this kind of problems.

Keywords: expert systems, multi-objective optimization, evolutionary algorithms, portfolio selection

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Authors: Abdallah M. Abdelkawy, Tarek M. El Hossainya, I. El Mahallawib

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Recently, significant achievements have been made in development and manufacturing of nano-dispersed metal matrix nanocomposites (MMNCs). They gain their importance due to their high strength to weight ratio. The machining problems of these new materials are less widely investigated, thus this work focuses on machining of them. Aluminum-Silicon (A356)/ MMNC dispersed with alumina (Al2O3) is important in many applications include engine blocks. The final finish process of this application depends heavily on machining. The most important machining parameter studied includes: cutting force and surface roughness. Experimental trails are performed on the number of special samples of MMNC (with different Al2O3%) where the relation between Al2O3% and cutting speed, feed rate and cutting depth with cutting force and surface roughness were studied. The data obtained were statistically analyzed using Analysis of variance (ANOVA) to define the significant factors on both cutting force and surface roughness and their level of confident. Response Surface Methodology (RSM) is used to build a model relating cutting conditions and Al2O3% to the cutting force and surface roughness. The results have shown that feed and depth of cut have the major contribution on the cutting force and the surface roughness followed by cutting speed and nano-percent in MMNCs.

Keywords: machinability, cutting force, surface roughness, Ra, RSM, ANOVA, MMNCs

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Authors: Rachit Marwaha, Rahul Dev Gupta, Vivek Jain, Krishan Kant Sharma

Abstract:

Metal matrix hybrid composites (MMHCs) are now gaining their usage in aerospace, automotive and other industries because of their inherent properties like high strength to weight ratio, hardness and wear resistance, good creep behaviour, light weight, design flexibility and low wear rate etc. Al alloy base matrix reinforced with silicon carbide (10%) and graphite (5%) particles was fabricated by stir casting process. The wear and frictional properties of metal matrix hybrid composites were studied by performing dry sliding wear test using pin on disc wear test apparatus. Experiments were conducted based on the plan of experiments generated through Taguchi’s technique. A L9 Orthogonal array was selected for analysis of data. Investigation to find the influence of applied load, sliding speed and track diameter on wear rate as well as coefficient of friction during wearing process was carried out using ANOVA. Objective of the model was chosen as smaller the better characteristics to analyse the dry sliding wear resistance. Results show that track diameter has highest influence followed by load and sliding speed.

Keywords: Taguchi method, orthogonal array, ANOVA, metal matrix hybrid composites

Procedia PDF Downloads 301

Authors: Shabnam Najafi, Metin Turkay

Abstract:

Network design problem (NDP) is used to determine the set of optimal values for certain pre-specified decision variables such as capacity expansion of nodes and links by optimizing various system performance measures including safety, congestion, and accessibility. The designed transportation network should improve objective functions defined for the system by considering the route choice behaviors of network users at the same time. The NDP studies mostly investigated the random demand and route selection constraints separately due to computational challenges. In this work, we consider both random demand and route selection constraints simultaneously. This work presents a nonlinear stochastic model for land use and road network design problem to address the development of different functional zones in urban areas by considering both cost function and air pollution. This model minimizes cost function and air pollution simultaneously with random demand and stochastic route selection constraint that aims to optimize network performance via road capacity expansion. The Bureau of Public Roads (BPR) link impedance function is used to determine the travel time function in each link. We consider a city with origin and destination nodes which can be residential or employment or both. There are set of existing paths between origin-destination (O-D) pairs. Case of increasing employed population is analyzed to determine amount of roads and origin zones simultaneously. Minimizing travel and expansion cost of routes and origin zones in one side and minimizing CO emission in the other side is considered in this analysis at the same time. In this work demand between O-D pairs is random and also the network flow pattern is subject to stochastic user equilibrium, specifically logit route choice model. Considering both demand and route choice, random is more applicable to design urban network programs. Epsilon-constraint is one of the methods to solve both linear and nonlinear multi-objective problems. In this work epsilon-constraint method is used to solve the problem. The problem was solved by keeping first objective (cost function) as the objective function of the problem and second objective as a constraint that should be less than an epsilon, where epsilon is an upper bound of the emission function. The value of epsilon should change from the worst to the best value of the emission function to generate the family of solutions representing Pareto set. A numerical example with 2 origin zones and 2 destination zones and 7 links is solved by GAMS and the set of Pareto points is obtained. There are 15 efficient solutions. According to these solutions as cost function value increases, emission function value decreases and vice versa.

Keywords: epsilon-constraint, multi-objective, network design, stochastic

Procedia PDF Downloads 617

Authors: Mehmet Erdi Korkmaz, Mustafa Günay

Abstract:

Nowadays, grinding is frequently replaced with hard turning for reducing set up time and higher accuracy. This paper focused on mathematical modeling of average surface roughness (Ra) in hard turning of AISI L2 grade (DIN 1.2210) cold work tool steel with ceramic tools. The steel was hardened to 60±1 HRC after the heat treatment process. Cutting speed, feed rate, depth of cut and tool nose radius was chosen as the cutting conditions. The uncoated ceramic cutting tools were used in the machining experiments. The machining experiments were performed according to Taguchi L27 orthogonal array on CNC lathe. Ra values were calculated by averaging three roughness values obtained from three different points of machined surface. The influences of cutting conditions on surface roughness were evaluated as statistical and experimental. The analysis of variance (ANOVA) with 95% confidence level was applied for statistical analysis of experimental results. Finally, mathematical models were developed using the artificial neural networks (ANN). ANOVA results show that feed rate is the dominant factor affecting surface roughness, followed by tool nose radius and cutting speed.

Keywords: ANN, hard turning, DIN 1.2210, surface roughness, Taguchi method

Procedia PDF Downloads 339