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Modeling and Analysis of Labour Cost Estimation for Ship Repairing: A Case Study in Chittagong Dry Dock Limited
No full textThis thesis is submitted to the Department of Industrial Engineering and Management, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Industrial Engineering and Management, December 2019.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 84-88).With the increase of international trade activities through sea and resulting exponential growth of number of ships calling on coastal nations’ ports, ship repair is becoming an increasingly attractive opportunity for littoral countries. Being a coastal nation, there were rapid growth of number of local shipyards in Bangladesh for past couple of years. This factor put CDDL faced with tremendous competition in ship repair arena in the national market. Besides, docking of ships and ship repairing work, are, by nature labor intensive. Labour cost contributes significantly to total repair cost. Besides acquiring market information, CDDL must estimate labor cost accurately to give competitive quotations in order to obtain ship repair orders. Lower labour cost value allow shipyards and ship owners to get higher productivity and lower final invoice respectively.
Forecasting estimated labor cost will allow CDDL to stay competitive among the ship repair
industries. In this project paper, attempt has been made to identify the number of those independent variables that influence ship repairing labour (dependent variable) and their inter-relationship. Since labor cost for ship repair can be expressed as a function of ship’s age, deadweight, displacement, type of ship and various repair works, so a multiple linear regression model is developed to construct a labor cost estimation model. From 2002 to 2019, ship repairing labour (man-days) related information for 43 sets for fishing vessel, 30 sets for oil tanker, 51 sets for multipurpose cargo ship, 40 sets for warship, 11 sets for dredger/barge and 15 sets for tugboat of various ages, sizes and types were collected from data storage of CDDL to construct models for each ship group. Regression coefficients are found out by applying “Method of Least Squares” in regression analysis. CDDL can use this mathematical model as a guiding tool to forecast labour cost estimates more realistically for ships to be under repair.Mohammad Sajedul KarimMaster of Science in Industrial Engineering and Managemen
Analysis of Heavy Metal Concentration in Soils of a Waste Disposal Site in Khulna using Artificial Intelligence Techniques
No full textThis thesis is submitted to the Department of Civil Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Civil Engineering, September 2019.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 154-160).The collection of soil samples is labored and time consuming as well as the determination of heavy metal concentrations in laboratory was expensive. To these attempts, artificial intelligence techniques (AI) such as adaptive neuro-fuzzy inference system (ANFIS), support vector machine (SVM) and artificial neural networks (ANN) were implemented for the analysis of heavy metal concentrations in soils of a selected waste disposal site at old Rajbandh, Khulna. The aim of this study was to fix the functions, algorithms, optimization methods for AI techniques based on their best performance and then select a best technique for the analysis of heavy metal concentrations in soils. In this study, soil samples were collected from eighty-five locations at a depth 0-30 cm from the existing ground surface from the selected disposal site. In the laboratory, the concentrations of heavy metals of Pb, Cu, Ni, Zn, Co, Cd, As, Sc, Hg, Mn, Cr, Ti, Sb, Sr, V and Ba in soils were measured.
Result reveals the model with SCP, gaussmf, linear and hybrid was the best-fitted model of ANFIS for the prediction of heavy metal concentrations in soils. In addition, in SVM analysis, the model SVM-RBF with 15 folds was selected for the prediction of heavy metal concentrations in soils. In ANN, the model LT (Levenberg-marquardt and Tansig functions) with neuron structure 2-10-1 was selected. The accuracy of the predicted results were checked based on the acceptable limits of prediction parameters like R value, RMSE, MAPE, GRI and percentage recovery. Among all heavy metals analysis in ANFIS, the maximum R-value 0.999 was found with the minimum RMSE 0.12 for Sc indicating the best correlation in prediction of Sc in soils. The others value of prediction parameters (MAPE= 36.00, GRI=1.50, percentage recovery=123.43%) for Sc were found within the acceptable limits. In addition, in SVM analysis, maximum R-value 0.73 with RMSE 2.03 was found for Cu; while, maximum R-value 0.88 with the minimum RMSE 1.01 for As was found in ANN. The results demonstrated that ANFIS model was a reliable technique than that of other counterparts of SVM and ANN to analyse the heavy metal concentrations in soils with the acceptable degree of robustness and accuracy. Therefore, the performance of AI techniques may be expressed by the sequence of ANFIS > SVM > ANN. Here it can be noted that one can easily be computed the concentration of a particular heavy metal in soils by inserting GPS values (latitude and longitude) only in the developed rule viewer of ANFIS. Therefore, this newly developed model will further be helpful for other researchers in this line to analysis heavy metal concentration in soils of selected waste disposal sites.Shyamol Kumar SarkarMaster of Science in Civil Engineerin
Performance Analysis of Single Neuron Adaptive PID, WNN and ANFIS Type Controller Based PMBLDC Motor Drive
No full textThis thesis is submitted to the Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Electrical and Electronic Engineering, June 2019.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 113-117).Permanent Magnet Brushless DC (PMBLDC) Motor Drive is familiar as an innovative
research for their compact size, silent operation, reliability, high efficiency, simple
construction, easy to control and less maintenance requirements. Design cost of PMBLDC
motor drive has been reduced drastically due to the invention of rare earth magnetic
materials and advancement of power semiconductor devices. The semiconductor power
devices are turned on or off sequentially using triggering and commutation circuits. Based
on the rotor position the controller generates requisite signals to control the operation of
the power inverter. A high performance controller is required to obtain desired
performance of the drive system. It is noticed that PMBLDC Motor has a complexity to
handle multi variable and nonlinear system. The motor speed control is frequently needed
for controlling various drives such as robotics, copters, electric vehicles and other drives of
applications. The high performance drives require very fast response, high efficiency and
parameter insensitive. It is not possible to achieve desired performance with conventional
PI controller. Tuning of controller parameters is necessary to achieve desired performance.
To overcome these problems this study proposes the following controllers (1) Single
Neuron based Adaptive (SNA) Controller, (2) Single Neuron based Adaptive PID
(SNAPID) Controller, (3) Adaptive Neuro Fuzzy Inference System (ANFIS) based
Controller with Radial Basis Function (RBF), (4) ANFIS Controller based on Takagi-
Sugeno Model, (5) ANFIS Controller based on Line Voltage Model and (6) Wavelet
Neural Network (WNN) based Controller. A PI controller with constant parameter is also
designed and it is tuned by Ziegler- Nichols method. Each controller was simulated by
developing software in C++ environment and performance of each controller is compared
with PI controller. To get better speed, torque and current responses field orientation
control method and square wave reference current input to the machine are considered with
the above controllers. In this process, direct axis current is considered to zero and
quadrature axis current produces useful torque. The drive performance was tested under
different operating conditions such as constant starting condition, sudden load torque
changes, speed variation and parameter changes. All proposed controllers perform well
under speed variation and constant starting condition except fixed PI and WNN based
controller. It is also observed that their speed responses are fast. For suddenly increment of
load torque, motor speed is fallen by WNN based Controller, fixed PI and SNAPID Controller but SNA Controller, ANFIS Controller based on Takagi-Sugeno Model, ANFIS
controller based on Line Voltage Model and ANFIS Controller with RBF perform well
with constant speed. Finally, it is seen that all controllers with PMBLDC Motor drive work
effectively without any performance degradation in the increment of stator resistance
hence, the proposed controllers perform as insensitive controller with the variation of stator
resistance.Md. Belal HossenMaster of Science in Electrical and Electronic Engineerin
Micro-Characterization of Indoor Particulate Matter in Selected Areas of Jashore University of Science and Technology
No full textThis thesis is submitted to the Department of Civil Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Civil Engineering, July 2019.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 81-86).Indoor air pollution has drawn considerable attention in recent years. Indoor air quality is very important for human health especially for vulnerable group of people (the asthmatic, the children and the elderly). The indoor environment can be subdivided into different micro-environments such as residents, transport, offices, educational institutions etc. and each may have a different source of indoor pollution. Indoor particulate matter has harmful impact on human health and environment. The finer the size of particles the higher the harmful impact. In this research work an attempt has been made for characterization of indoor particulate matter at three buildings named10-storied residential Tower, Administrative and Academic building of Jashore University of Science and Technology (JUST) campus.
In the dust sample, presence of heavy metals (Ti,Fe,Cu,Zn,As,Pb,Zr) and criteria air pollutant(Pb)was found. The concentration of PM10 (μg/m3) and PM2.5 (μg/m3) measured by Tactical Air Sampler (TAS) was found highest value (PM10, 170μg/m3 and PM2.5,103μg/m3) in Academic building among the three buildings. The reason is that this building is situated near road side and construction work is going on adjacent the building. Again concentration of PM2.5 is found higher inside than outside the building in all cases. Concentration of PM10 (130μg/m3) is found higher inside than outside (76μg/m3) in Administrative Building. Concentration of PM10 and PM2.5 in all cases exceeds WHO guideline limit (WHO guideline for PM10 in 24 hour- 50μg/m3 and 1 year is 20μg/m3; For PM2.5 in 24 hour- 25μg/m3 and 1 year is 10μg/m3 ) and in academic building exceeds Bangladesh standard both in outdoor and indoor(Bangladesh standard for PM10 in 24 hour- 150μg/m3 and 1 year is 50μg/m3). Concentration of PM10 in administrative building both in outdoor and indoor and 10-storied residential tower building in outdoor is within Bangladesh 24 hour standard but exceeds Bangladesh 1 year standard. In academic building exceeds Bangladesh standard both in outdoor and indoor (Bangladesh standard for PM2.5 in 24 hour- 65μg/m3 and 1 year is 15μg/m3). Concentration of PM2.5 in administrative building exceeds Bangladesh standard in indoor but in outdoor within 24 hour standard but exceeds 1 year standard. Concentration in 10-storied residential tower in outdoor within the 24 hour standard but exceeds 1 year standard.
In XRF analysis presence of Pb (667±0.19,ppm) and Ca (61340±919,ppm) was found highest in academic building PM. Inter elemental correlation was calculated. Strong correlation (R2 >0.90) was found Pb with Zr; Sr with Ca, Ti, Zn and As; Rb with K and Cu; As with Ca, Fe and Zn; Zn with Ti and Fe; Cu with K; Fe with Ca and Ti. Strongly correlated elements originated from same source such as re-suspended road dust, trace element of earth crust, cement, paint and other construction materials. Adequate control, management, housekeeping can minimize the exposure of indoor dust to occupants.Md. Helal Uddin PatwaryMaster of Science in Civil Engineerin
A Study on the Comparison between HTML5 and OpenGL in Rendering Fractal Tree
No full textThis thesis is submitted to the Department of Computer Science and Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Masters of Science in Computer Science & Engineering, March 2019.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 21-22).This is the era of web applications as for each desktop application, there is a corresponding web application being developed. Each web application consists of interactive graphical user interface and some of them requires in-browser rendering. In this period, it’s high time to study the abilities of modern-day web applications on handling graphical operations. As both HTML5 and OpenGL are strong tools for graphical operation and both depicts rendering capabilities on different platforms, in this project, they have been compared thoroughly. To measure the effectiveness and compare the results from HTML5 and OpenGL, Fractals are considered to be drawn on web platform and on desktop graphical program. In this project, A simple HTML5 web page is implemented along with a C++ based command line program is also implemented to render fractal trees. HTML5 and OpenGL both performed significantly well in case of rendering fractal trees where HTML5 fell a little bit short in case of rendering time in case of large number of iterations. As the number of iterations increased rapidly, the rendering time required by the HTML5 increased but it performed on par with OpenGL in rendering quality.Mehbuba Zerin KhanMasters of Science in Computer Science & Engineerin