Seeram Srinivasa Rao

Koneru Lakshmaiah Education Foundation

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S. N. Padhi

Koneru Lakshmaiah Education Foundation

Ashwini Kumar Baluguri

Koneru Lakshmaiah Education Foundation

Mamata Choudhury

Bandhavi Challa

Koneru Lakshmaiah Education Foundation

Trilochan Rout

International Institute of Information Technology

Ashok Kumar

Banasthali University

B. Balu Naik

Jawaharlal Nehru Technological University, Hyderabad

P. Nageswara Rao

Sathyabama Institute of Science and Technology

Swagata Sarkar

Indian Institute of Technology Kanpur

Swadesh Kumar Singh

Victoria University

Cooperative Institutions

Koneru Lakshmaiah Education Foundation

Institute of Engineering

North Eastern Regional Institute of Science and Technology

Andhra University

Annamalai University

Indira Gandhi Institute of Technology

Sathyabama Institute of Science and Technology

Indian Institute of Technology Kanpur

Delhi Technological University

Solamalai College of Engineering

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Design and analysis of ISO standard bolt and nut in FDM 3D printer using PLA and ABS materials

Materials Today Proceedings (2019)

V. Harshitha Seeram Srinivasa Rao

Acrylonitrile butadiene styrene

Fused Deposition Modeling

3d printer

10.1016/j.matpr.2019.07.737

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Citations (33)

IoT Based Fish Pond Monitoring System to Enhance Its Productivity

Sumeet Kumar Thayyaba Khatoon Mohammed Seeram Srinivasa Rao P. Dinesh Anton Raja Ruhi Bakhare

Modernizing fish ponds for agricultural production face major challenges in terms of capital expenditure and operational expenses. Fish farming of particular types of fish species necessitates the fulfilment of several requirements because, like several other living organisms, fish have a precise limit for an assortment of environmental criteria. For the good health and development of the organisms, big farms typically have certain kinds of water surveillance and replacement mechanization systems. To preserve the ecosystems for living fish, the people who work in the fish farming ponds must be active throughout the day. Local farmers who operate on relatively small ponds couldn't afford to compensate employees to manage daily tasks, which typically include keeping an eye on water levels, temperature, and pH levels. As a result, the prime motive for this paper is to monitor and take steps to keep the habitat's eco-friendly environment for specific species of fish, which will decrease the time required for some basic actions. This article puts forth a smart Internet of Things (IoT) based fish pond water monitoring system. Such a smart system consists of several real-time sensors that monitor and send inputs to a microcontroller and the data is stored in a real-time database. The user can track these values through a phone app that is assimilated with the cloud by having them transmitted to the cloud at periodic intervals and this helps the fish pond owners to take required action quickly and effectively when needed. As embedding devices are typically made up of an Arduino board, internet and relay frames, and a computer interface, a farmer could easily source these parts. With the help of this integration system, farmers can reduce operating costs and boost overall effectiveness by avoiding the need to hire employees for their location.

10.1109/iciptm57143.2023.10117894

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Citations (3)

Expert System for Generating Process Plans

Advances in mechatronics and mechanical engineering (AMME) book series (2024)

G. R. Sanjay Krishna Seeram Srinivasa Rao Ashwini Kumar Baluguri S. N. Padhi

Automating the process of design generation is pivotal for enhancing efficiency and productivity in various industries. This study focuses on developing methodologies and algorithms to streamline the creation of designs through automation. By leveraging feature extraction databases and advanced computational techniques, the aim is to generate designs automatically based on specific requirements and input parameters. The process involves analyzing existing design data and extracting key features that serve as building blocks for generating new designs. Optimal design sequences are determined to minimize tool changes, reduce non-cutting time, and maximize productivity. Additionally, the selection of materials, cutting parameters, and tooling is automated to ensure the creation of high-quality designs tailored to the intended applications. The study explores various approaches for automating different aspects of the design process, including CAD/CAM integration, parametric modeling, and algorithmic design generation.

10.4018/979-8-3693-1966-6.ch023

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Citations (0)

Transforming CNC Machining

Advances in mechatronics and mechanical engineering (AMME) book series (2024)

Seeram Srinivasa Rao S. N. Padhi Ashwini Kumar Baluguri Mamata Choudhury

In the realm of computer numerical control (CNC) machining, efficiency and precision are paramount. This chapter presents a groundbreaking advancement in CNC technology: Automated NC Part Program Generation. Traditional CNC programming involves labour intensive manual coding, susceptible to errors and time-consuming iterations. However, this revolutionary approach automates the generation of NC part programs, drastically reducing human intervention while enhancing accuracy and speed. By leveraging cutting-edge algorithms and machine learning techniques, this innovation empowers manufacturers to streamline their production processes. With Automated NC Part Program Generation, complex geometries and intricate machining tasks are seamlessly translated into machine-readable instructions. Moreover, the system intelligently optimizes toolpaths, minimizing material waste and tool wear while maximizing throughput.

10.4018/979-8-3693-1966-6.ch026

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Citations (0)

Deep Learning Network for Object Detection Under the Poor Lighting Condition

2022 International Conference on Automation, Computing and Renewable Systems (ICACRS) (2022)

L S Chethan S. Uma Maheswari Seeram Srinivasa Rao Naveen Mukkapati C. S. Sundar Ganesh

Object detection is a part of image processing that holds great importance in this modern world. To locate things in images or videos, a computer vision approach called object detection is utilized. To identify items in both still photos and moving films, numerous algorithms and models have been created. One of the main issues with such object detection algorithms is that they struggle to accurately identify things in images with poor lighting. This study tries to develop the best deep learning algorithm that can be used to predict items from photos with very little or no lighting to address this issue. For this,from GitHub, a dataset of images of various objects, such as tables, cats, and dogs, has been compiled. After categorization, the collected dataset is examined using two factors. The images are then preprocessed utilizing picture format conversion and histogram equalization. Two different deep learning models were produced by two different algorithms. The YOLO algorithm and the speedier RCNN algorithm are the two algorithms. The models are then trained and evaluated using the preprocessed dataset. The performance of the models during training and validation is assessed using a metric called the AP score. The YOLO algorithm has the better AP score overall, according to the analysis of the AP score. The YOLO is once again determined to be superior when the findings are displayed in a bar graph for easier understanding. The YOLO algorithm's prediction results are also examined, and it is discovered that even under conditions of extremely poor lighting, the algorithm can correctly predict the presence of one or more objects.

F1 score

10.1109/icacrs55517.2022.10029145

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Citations (0)

Multi-objective optimization with modified Taguchi approach to specify optimal robot spray painting process parameters

International journal of nonlinear analysis and applications (2021)

Swetha Danthala Seeram Srinivasa Rao B. Nageswara Rao Kasiprasad Mannepalli

Robot spray painting process can improve the quality, productivity and provide clean environment in addition to minimize the labour and cost. This process is being used in automobiles, home appliances, etc. There is a need to specify optimal spray painting process parameters to improve the quality of paint coating considering the performance indicators as thickness variation, surface roughness and film adhesion. Compared to the Taguchi orthogonal array and gray rational analysis, a simple modified Taguchi approach is adopted here to identify optimal spray painting process parameters (such as distance, pressure and speed) and obtain minimum thickness variation, minimum surface roughness and maximum film adhesion. Empirical relation for thickness variation, surface roughness and film adhesion are presented. Test data are close-to/within the estimated range.

Orthogonal array

10.22075/ijnaa.2021.5193

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Citations (3)

Study of Mechanical Properties and Microstructural behaviour of alpha- beta brass at elevated temperature

E3S Web of Conferences (2021)

Bandhavi Challa Seeram Srinivasa Rao

Deformation behaviour of metal can be analyzed by determining mechanical properties for optimizing workability. In the present investigation hot uniaxial tensile test for alpha - beta brass material have been performed by considering parameters like temperature (RT, 600 0 C and 700 0 C), strain rate (0.1/s, 0.01/s and 0.001/s) and orientation (RD, ND and TD). The various material properties such as ultimate tensile strength (σu), yield stress (σy), total elongation(%) have been evaluated over the range of temperatures, strain rates and orientation. It have been observed that changes in material properties with respect to temperature, strain rate than orientation. The material properties has been analyse the mechanical characteristics of the material. The fractured specimens at various temperatures are studied and analyzed the failure modes in the material using Scanning Electron Microscope (SEM). SEM study confirms carbides and shear band which indicate predominantly ductile fracture in all the cases.

Brass

Elongation

Tensile testing

Atmospheric temperature range

10.1051/e3sconf/202130901146

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Citations (2)

Conceptual Design of Multipurpose CNC Machine Tool

Advances in mechatronics and mechanical engineering (AMME) book series (2024)

Ashwini Kumar Baluguri Seeram Srinivasa Rao S. N. Padhi Mamata Choudhury

Multipurpose CNC machine tools are increasingly in demand due to their ability to perform multiple machining operations in a single setup. In this chapter, the authors present a conceptual design of a multipurpose CNC machine tool that can perform milling, drilling, tapping, and turning operations. It focuses on the conceptual design and development of a multipurpose CNC machine tool for small and medium-sized manufacturing industries, with a special emphasis on precision machining, high precision operations, metal cutting operations, modular structure, and hybrid mechanisms. Various theories and methods were used to propose new conceptual designs for CNC machine tools that can perform multiple functions, enhance productivity, and reduce manufacturing costs. This chapter provides insights into the latest trends and advancements in the field of CNC machine tools and their potential applications in the manufacturing industry.

Conceptual design

10.4018/979-8-3693-1966-6.ch007

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Churu's 100MW Solar Dream

Advances in mechatronics and mechanical engineering (AMME) book series (2024)

S. N. Padhi Prudhvi Teja G.Trilochan Rout Seeram Srinivasa Rao Mamata Choudhury

Every nation is actively seeking alternative energy sources to diminish reliance on fossil fuels, natural gas, and coal. Countries worldwide are striving for environmentally friendly and sustainable energy solutions, aiming to reduce dependence on fossil fuels. This chapter explores the feasibility of establishing a 100MW photovoltaic power plant in Churu city, Rajasthan, utilizing RET screen software. RET screen facilitates feasibility, benchmark, financial, and emission analyses, covering various renewable energy sources such as geothermal, bioenergy, solar, and wind power. Specifically, this project conducts a feasibility analysis of photovoltaic cells, converting solar energy into usable power. Given the abundance of solar energy, the study focuses on the viability of a solar or photovoltaic power plant, yielding positive outcomes. Consequently, this project emerges as a financially feasible and environmentally sustainable endeavor, contributing to the reduction of greenhouse gas emissions and advancing the nation towards cleaner energy production.

10.4018/979-8-3693-1966-6.ch006

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Citations (0)

Improving the thermal efficiency of a solar water heater by using PCM

Materials Today Proceedings (2023)

M. Saravanan S. Arul Selvan N. Radhakrishnan Seeram Srinivasa Rao Vipin Sharma

Phase-change material

Solar water heating

Storage water heater

10.1016/j.matpr.2023.07.233

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Citations (5)