Browsing by Author "Das, Saikat"

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Admission Helper: A Mobile Applications for Undergraduate Admission Applications
(Daffodil International University, 2019-12) Islam, Shaiful; Islam, Md. Rakibul; Das, Saikat; Opu, Sohel Rihan
Admission Test is a matter of concern for all the admitted candidates. So to minimize the sufferings of these aspirants, our admission test application made in a small effort. At present, the use of smartphones can be noticed everywhere. A large part of our admissions candidates live in the village or do not have admissions coaching in the city, so they are often unaware of all university admission tests, question patterns, exact time of form filling, and other important information. Therefore, if an admission examiner wants to install this application on his emperor's phone, he can benefit greatly through internet connection very easily, in a short time and with little effort. Our application has the advantage of almost all public and private information of Bangladesh, last year's question, the university's question pattern, and online test. Not only that through this application, but an examiner can also see the results of his or her examination from any university. Through this application, you can take the online test and know the result as well. Through which a student can verify himself which will increase their confidence.
Optimization of Process Parameters in Face Milling of Stainless Steel 304 Using CNC Milling Machine for Reducing Power Consumption and Surface Roughness
(2019-12) Das, Saikat; Khondaker, Md. Hasib
The quality of a CNC machined surface depends on various factors. The factors are surface roughness, surface defects, surface texture, surface deformation etc. Among all these factors, surface roughness of a CNC machined work piece is one of the most important characteristics of a product quality. For meeting customer requirement with quality issues, better surface finish should be provided. There are some process parameters (cutting speed, depth of cut, feed rate, tool geometry) which can affect the machined surface quality as well as can influence the energy consumption rate. Energy reduction in industry has become one of the main objectives for achieving environment friendly manufacturing. Increasing energy prices are new challenges faced by modern manufacturers. A considerable amount of energy consumption is attributed to the machining energy consumption of machine tools. Predicting the wrong level of process parameters leads to high power consumption. Optimizing the machining parameters can reduce the power consumption as well as can provide good surface finish. In practice, optimization of energy consumption should be implemented while taking into consideration other parameters such as the obtained surface quality. In this work, an approach which incorporates both power consumption and surface roughness is presented for optimizing the cutting parameters in CNC machined face milling process. Stainless steel 304 was chosen as work material. For obtaining the optimum process parameters, response surface methodology can be used to find the accurate machining parameters which reduces the overall power consumption that is one of the main requirements of a manufacturer. Better surface finish is also a requirement of the customer which is computed through this research. Thus, this work can satisfy both customers & manufacturers.
Sensor based Smart Automated Gas Leakage Detection and Prevention System
(Daffodil International University, 2022-05-02) Tasnim, Zarrin; Das, Saikat; Islam, Rakibul; Biswas, Jahanur; Shamrat, F. M. Javed Mehedi; Khater, Ankit
Liquefied petroleum gas (LPG) is commonly used for heating, cooking, automotive power, and various other uses worldwide. LPG is a particularly flammable gas, and LPG leaks cause significant incidents. The cause may arise from improper installation to the use of faulty gas cylinders. Since LPG is an extremely volatile and flammable gas, a reliable safety system has been designed and developed using IoT (Internet of Things) capable of detecting gas leakage, turning on the emergency alarm, tracking the location, and sending alerts messages to users and nearest helpline number. The proposed model sort out into four modules, such as Gas Detection Module (GDM) always detect the gas leakage to avoid unexpected incidents; Location Detection Module (LDM) track the gas leakage location and pass the value to NM; Notification Module (NM) is responsible for generating the message service to notify the nearest help center and user; In the case of a gas leak, the Alarm Module (AM) is responsible for activating an emergency alarm. The result shows the system successfully performed. It can be noted that the proposed can be embedded with any environment, including home, office, ship, industry, etc.