Description: | Faculty of Engineering. Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/2358 |
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Dyuthi-T0630.pdf | (3.053Mb) |
URI: | http://dyuthi.cusat.ac.in/purl/5190 |
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Dyuthi T-2225.pdf | (22.25Mb) |
Abstract: | To ensure quality of machined products at minimum machining costs and maximum machining effectiveness, it is very important to select optimum parameters when metal cutting machine tools are employed. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The design objective preceding most engineering design activities is simply to minimize the cost of production or to maximize the production efficiency. The main aim of research work reported here is to build robust optimization algorithms by exploiting ideas that nature has to offer from its backyard and using it to solve real world optimization problems in manufacturing processes.In this thesis, after conducting an exhaustive literature review, several optimization techniques used in various manufacturing processes have been identified. The selection of optimal cutting parameters, like depth of cut, feed and speed is a very important issue for every machining process. Experiments have been designed using Taguchi technique and dry turning of SS420 has been performed on Kirlosker turn master 35 lathe. Analysis using S/N and ANOVA were performed to find the optimum level and percentage of contribution of each parameter. By using S/N analysis the optimum machining parameters from the experimentation is obtained.Optimization algorithms begin with one or more design solutions supplied by the user and then iteratively check new design solutions, relative search spaces in order to achieve the true optimum solution. A mathematical model has been developed using response surface analysis for surface roughness and the model was validated using published results from literature.Methodologies in optimization such as Simulated annealing (SA), Particle Swarm Optimization (PSO), Conventional Genetic Algorithm (CGA) and Improved Genetic Algorithm (IGA) are applied to optimize machining parameters while dry turning of SS420 material. All the above algorithms were tested for their efficiency, robustness and accuracy and observe how they often outperform conventional optimization method applied to difficult real world problems. The SA, PSO, CGA and IGA codes were developed using MATLAB. For each evolutionary algorithmic method, optimum cutting conditions are provided to achieve better surface finish.The computational results using SA clearly demonstrated that the proposed solution procedure is quite capable in solving such complicated problems effectively and efficiently. Particle Swarm Optimization (PSO) is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. From the results it has been observed that PSO provides better results and also more computationally efficient.Based on the results obtained using CGA and IGA for the optimization of machining process, the proposed IGA provides better results than the conventional GA. The improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. Finally, a comparison among these algorithms were made for the specific example of dry turning of SS 420 material and arriving at optimum machining parameters of feed, cutting speed, depth of cut and tool nose radius for minimum surface roughness as the criterion. To summarize, the research work fills in conspicuous gaps between research prototypes and industry requirements, by simulating evolutionary procedures seen in nature that optimize its own systems. |
Description: | Division of Mechanical Engineering,Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/2768 |
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Dyuthi-T0791.pdf | (1.548Mb) |
Abstract: | There is a recent trend to describe physical phenomena without the use of infinitesimals or infinites. This has been accomplished replacing differential calculus by the finite difference theory. Discrete function theory was first introduced in l94l. This theory is concerned with a study of functions defined on a discrete set of points in the complex plane. The theory was extensively developed for functions defined on a Gaussian lattice. In 1972 a very suitable lattice H: {Ci qmxO,I qnyo), X0) 0, X3) 0, O < q < l, m, n 5 Z} was found and discrete analytic function theory was developed. Very recently some work has been done in discrete monodiffric function theory for functions defined on H. The theory of pseudoanalytic functions is a generalisation of the theory of analytic functions. When the generator becomes the identity, ie., (l, i) the theory of pseudoanalytic functions reduces to the theory of analytic functions. Theugh the theory of pseudoanalytic functions plays an important role in analysis, no discrete theory is available in literature. This thesis is an attempt in that direction. A discrete pseudoanalytic theory is derived for functions defined on H. |
Description: | Department Of Mathematics and Statistics, Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/3394 |
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Dyuthi-T1371.pdf | (4.002Mb) |
Abstract: | Poor cold flow properties of vegetable oils are a major problem preventing the usage of many abundantly available vegetable oils as base stocks for industrial lubricants. The major objective of this research is to improve the cold flow properties of vegetable oils by various techniques like additive addition and different chemical modification processes. Conventional procedure for determining pour point is ASTM D97 method. ASTM D97 method is time consuming and reproducibility of pour point temperatures is poor between laboratories. Differential Scanning Calorimetry (DSC) is a fast, accurate and reproducible method to analyze the thermal activities during cooling/heating of oil. In this work coconut oil has been chosen as representative vegetable oil for the analysis and improvement cold flow properties since it is abundantly available in the tropics and has a very high pour point of 24 °C. DSC is used for the analysis of unmodified and modified vegetable oil. The modified oils (with acceptable pour points) were then subjected to different tests for the valuation of important lubricant properties such as viscometric, tribological (friction and wear properties), oxidative and corrosion properties.A commercial polymethacrylate based PPD was added in different percentages and the pour points were determined in each case. Styrenated phenol(SP) was added in different concentration to coconut oil and each solution was subjected to ASTM D97 test and analysis by DSC. Refined coconut oil and other oils like castor oil, sunflower oil and keranja oil were mixed in different proportions and interesterification procedure was carried out. Interesterification of coconut oil with other vegetable oils was not found to be effective in lowering the pour point of coconut oil as the reduction attained was only to the extent of 2 to 3 °C.Chemical modification by acid catalysed condensation reaction with coconut oil castor oil mixture resulted in significant reduction of pour point (from 24 ºC to -3 ºC). Instead of using triacylglycerols, when their fatty acid derivatives (lauric acid- the major fatty acid content of coconut oil and oleic acid- the major fatty acid constituents of monoand poly- unsaturated vegetable oils like olive oil, sunflower oil etc.) were used for the synthesis , the pour point could be brought down to -42 ºC. FTIR and NMR spectroscopy confirmed the ester structure of the product which is fundamental to the biodegradability of vegetable oils. The tribological performance of the synthesised product with a suitable AW/EP additive was comparable to the commercial SAE20W30 oil. The viscometric properties (viscosity and viscosity index) were also (with out additives) comparable to commercial lubricants. The TGA experiment confirmed the better oxidative performance of the product compared to vegetable oils. The sample passed corrosion test as per ASTM D130 method. |
Description: | School of Engineering, Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/xmlui/purl/1924 |
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Dyuthi-T0375.pdf | (1.974Mb) |
Abstract: | The thesis begins with a review of basic elements of general theory of relativity (GTR) which forms the basis for the theoretical interpretation of the observations in cosmology. The first chapter also discusses the standard model in cosmology, namely the Friedmann model, its predictions and problems. We have also made a brief discussion on fractals and inflation of the early universe in the first chapter. In the second chapter we discuss the formulation of a new approach to cosmology namely a stochastic approach. In this model, the dynam ics of the early universe is described by a set of non-deterministic, Langevin type equations and we derive the solutions using the Fokker—Planck formalism. Here we demonstrate how the problems with the standard model, can be eliminated by introducing the idea of stochastic fluctuations in the early universe. Many recent observations indicate that the present universe may be approximated by a many component fluid and we assume that only the total energy density is conserved. This, in turn, leads to energy transfer between different components of the cosmic fluid and fluctuations in such energy transfer can certainly induce fluctuations in the mean to factor in the equation of state p = wp, resulting in a fluctuating expansion rate for the universe. The third chapter discusses the stochastic evolution of the cosmological parameters in the early universe, using the new approach. The penultimate chapter is about the refinements to be made in the present model, by means of a new deterministic model The concluding chapter presents a discussion on other problems with the conventional cosmology, like fractal correlation of galactic distribution. The author attempts an explanation for this problem using the stochastic approach. |
Description: | Department of Physics, Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/3422 |
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Dyuthi-T1391.pdf | (1.429Mb) |
URI: | http://dyuthi.cusat.ac.in/purl/5438 |
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Dyuthi T-2479.pdf | (3.695Mb) |
URI: | http://dyuthi.cusat.ac.in/purl/5563 |
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Dyuthi T-2605.pdf | (1.259Mb) |
Abstract: | This thesis discusses the factors which influence the productive and financial performance of the spinning mills in Kerala. The study will also help to assess the effect of ongoing reforms in the industrial sector in India. The main objective of the study is to identify and analyse the factors affecting the efficiency of the spinning mills. The unique feature of the study is that it compares the performance of private sector in relation to its public counterparts and also performance of small sector in relation to medium sector. The study is carried out with reference to the relative performance of differmills in Kerala and to identify the sources of differences in performance. The study covers twenty one spinning mills in Kerala, of which ten are in the private sector, four under NTC, three under co—operat;ive sector and four under KSTC.Measured in terms of firm-size fifteen belong to small size with a spindleage of less than 26,000 and six are in the medium size with a spindleage of 26,000 to 50,0OO.1 The period of study is 1982-83 to 1991-92. Hence, only those companies, of which data of 10 years upto 1991-92 wereavailable, are taken for study. |
Description: | School of Management Studies, Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/3217 |
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Dyuthi-T1191.pdf | (3.085Mb) |
URI: | http://dyuthi.cusat.ac.in/purl/5234 |
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Dyuthi T-2269.pdf | (994.2Kb) |
Abstract: | This study is about the analysis of some queueing models related to N-policy.The optimal value the queue size has to attain in order to turn on a single server, assuming that the policy is to turn on a single server when the queue size reaches a certain number, N, and turn him off when the system is empty.The operating policy is the usual N-policy, but with random N and in model 2, a system similar to the one described here.This study analyses “ Tandem queue with two servers”.Here assume that the first server is a specialized one.In a queueing system,under N-policy ,the server will be on vacation until N units accumulate for the first time after becoming idle.A modified version of the N-policy for an M│M│1 queueing system is considered here.The novel feature of this model is that a busy service unit prevents the access of new customers to servers further down the line.It is deals with a queueing model consisting of two servers connected in series with a finite intermediate waiting room of capacity k.Here assume that server I is a specialized server.For this model ,the steady state probability vector and the stability condition are obtained using matrix – geometric method. |
URI: | http://dyuthi.cusat.ac.in/purl/39 |
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Dyuthi-T0001.pdf | (898.9Kb) |
Abstract: | This thesis is devoted to the study of some stochastic models in inventories. An inventory system is a facility at which items of materials are stocked. In order to promote smooth and efficient running of business, and to provide adequate service to the customers, an inventory materials is essential for any enterprise. When uncertainty is present, inventories are used as a protection against risk of stock out. It is advantageous to procure the item before it is needed at a lower marginal cost. Again, by bulk purchasing, the advantage of price discounts can be availed. All these contribute to the formation of inventory. Maintaining inventories is a major expenditure for any organization. For each inventory, the fundamental question is how much new stock should be ordered and when should the orders are replaced. In the present study, considered several models for single and two commodity stochastic inventory problems. The thesis discusses two models. In the first model, examined the case in which the time elapsed between two consecutive demand points are independent and identically distributed with common distribution function F(.) with mean (assumed finite) and in which demand magnitude depends only on the time elapsed since the previous demand epoch. The time between disasters has an exponential distribution with parameter . In Model II, the inter arrival time of disasters have general distribution (F.) with mean ( ) and the quantity destructed depends on the time elapsed between disasters. Demands form compound poison processes with inter arrival times of demands having mean 1/. It deals with linearly correlated bulk demand two Commodity inventory problem, where each arrival demands a random number of items of each commodity C1 and C2, the maximum quantity demanded being a (< S1) and b(<S2) respectively. The particular case of linearly correlated demand is also discussed |
URI: | http://dyuthi.cusat.ac.in/purl/61 |
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Dyuthi-T0010.pdf | (1.878Mb) |
Abstract: | The thesis deals with analysis of some Stochastic Inventory Models with Pooling/Retrial of Customers.. In the first model we analyze an (s,S) production Inventory system with retrial of customers. Arrival of customers from outside the system form a Poisson process. The inter production times are exponentially distributed with parameter µ. When inventory level reaches zero further arriving demands are sent to the orbit which has capacity M(<∞). Customers, who find the orbit full and inventory level at zero are lost to the system. Demands arising from the orbital customers are exponentially distributed with parameter γ. In the model-II we extend these results to perishable inventory system assuming that the life-time of each item follows exponential with parameter θ. The study deals with an (s,S) production inventory with service times and retrial of unsatisfied customers. Primary demands occur according to a Markovian Arrival Process(MAP). Consider an (s,S)-retrial inventory with service time in which primary demands occur according to a Batch Markovian Arrival Process (BMAP). The inventory is controlled by the (s,S) policy and (s,S) inventory system with service time. Primary demands occur according to Poissson process with parameter λ. The study concentrates two models. In the first model we analyze an (s,S) Inventory system with postponed demands where arrivals of demands form a Poisson process. In the second model, we extend our results to perishable inventory system assuming that the life-time of each item follows exponential distribution with parameter θ. Also it is assumed that when inventory level is zero the arriving demands choose to enter the pool with probability β and with complementary probability (1- β) it is lost for ever. Finally it analyze an (s,S) production inventory system with switching time. A lot of work is reported under the assumption that the switching time is negligible but this is not the case for several real life situation. |
URI: | http://dyuthi.cusat.ac.in/purl/57 |
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Dyuthi-T0009.pdf | (1.614Mb) |
Abstract: | In this thesis we have presented several inventory models of utility. Of these inventory with retrial of unsatisfied demands and inventory with postponed work are quite recently introduced concepts, the latt~~ being introduced for the first time. Inventory with service time is relatively new with a handful of research work reported. The di lficuity encoLlntered in inventory with service, unlike the queueing process, is that even the simplest case needs a 2-dimensional process for its description. Only in certain specific cases we can introduce generating function • to solve for the system state distribution. However numerical procedures can be developed for solving these problem. |
Description: | Department of Mathematics, Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/3824 |
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Dyuthi-T1755.pdf | (2.141Mb) |
URI: | http://dyuthi.cusat.ac.in/purl/1666 |
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Dyuthi-T0013.pdf | (1.956Mb) |
Abstract: | The thesis entitled Analysis of Some Stochastic Models in Inventories and Queues. This thesis is devoted to the study of some stochastic models in Inventories and Queues which are physically realizable, though complex. It contains a detailed analysis of the basic stochastic processes underlying these models. In this thesis, (s,S) inventory systems with nonidentically distributed interarrival demand times and random lead times, state dependent demands, varying ordering levels and perishable commodities with exponential life times have been studied. The queueing system of the type Ek/Ga,b/l with server vacations, service systems with single and batch services, queueing system with phase type arrival and service processes and finite capacity M/G/l queue when server going for vacation after serving a random number of customers are also analysed. The analogy between the queueing systems and inventory systems could be exploited in solving certain models. In vacation models, one important result is the stochastic decomposition property of the system size or waiting time. One can think of extending this to the transient case. In inventory theory, one can extend the present study to the case of multi-item, multi-echelon problems. The study of perishable inventory problem when the commodities have a general life time distribution would be a quite interesting problem. The analogy between the queueing systems and inventory systems could be exploited in solving certain models. |
Description: | Department of Mathematics and Statistics Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/3244 |
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Dyuthi-T1218.pdf | (4.503Mb) |
Dyuthi-T1218.pdf | (4.503Mb) |
Abstract: | The classical methods of analysing time series by Box-Jenkins approach assume that the observed series uctuates around changing levels with constant variance. That is, the time series is assumed to be of homoscedastic nature. However, the nancial time series exhibits the presence of heteroscedasticity in the sense that, it possesses non-constant conditional variance given the past observations. So, the analysis of nancial time series, requires the modelling of such variances, which may depend on some time dependent factors or its own past values. This lead to introduction of several classes of models to study the behaviour of nancial time series. See Taylor (1986), Tsay (2005), Rachev et al. (2007). The class of models, used to describe the evolution of conditional variances is referred to as stochastic volatility modelsThe stochastic models available to analyse the conditional variances, are based on either normal or log-normal distributions. One of the objectives of the present study is to explore the possibility of employing some non-Gaussian distributions to model the volatility sequences and then study the behaviour of the resulting return series. This lead us to work on the related problem of statistical inference, which is the main contribution of the thesis |
Description: | Department of Statistics, Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/4732 |
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Dyuthi-T1834.pdf | (3.550Mb) |
Abstract: | Natural systems are inherently non linear. Recurrent behaviours are typical of natural systems. Recurrence is a fundamental property of non linear dynamical systems which can be exploited to characterize the system behaviour effectively. Cross recurrence based analysis of sensor signals from non linear dynamical system is presented in this thesis. The mutual dependency among relatively independent components of a system is referred as coupling. The analysis is done for a mechanically coupled system specifically designed for conducting experiment. Further, cross recurrence method is extended to the actual machining process in a lathe to characterize the chatter during turning. The result is verified by permutation entropy method. Conventional linear methods or models are incapable of capturing the critical and strange behaviours associated with the dynamical process. Hence any effective feature extraction methodologies should invariably gather information thorough nonlinear time series analysis. The sensor signals from the dynamical system normally contain noise and non stationarity. In an effort to get over these two issues to the maximum possible extent, this work adopts the cross recurrence quantification analysis (CRQA) methodology since it is found to be robust against noise and stationarity in the signals. The study reveals that the CRQA is capable of characterizing even weak coupling among system signals. It also divulges the dependence of certain CRQA variables like percent determinism, percent recurrence and entropy to chatter unambiguously. The surrogate data test shows that the results obtained by CRQA are the true properties of the temporal evolution of the dynamics and contain a degree of deterministic structure. The results are verified using permutation entropy (PE) to detect the onset of chatter from the time series. The present study ascertains that this CRP based methodology is capable of recognizing the transition from regular cutting to the chatter cutting irrespective of the machining parameters or work piece material. The results establish this methodology to be feasible for detection of chatter in metal cutting operation in a lathe. |
Description: | Division of Mechanical Engineering,School of Engineering, Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/3058 |
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Dyuthi-T1032.pdf | (7.938Mb) |
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