http://localhost:8081/jspui/handle/123456789/14 2026-05-07T21:21:51Z http://localhost:8081/jspui/handle/123456789/20736 Title: EXPERIMENTAL INVESTIGATION INTO FINISHING OF FREEFORM SURFACE BY ABRASIVE FLOW MACHINING Authors: Meena, Muniram Abstract: Freeform complex surfaces have become an important part of many devices to perform necessary functions. In the applications of these surfaces, surface roughness is required at nano level or micron-level to perform the desired function efficiently. In the present work, freeform surfaces, especially hip joint, was designed and manufactured using the Selective Laser Sintering (SLS) technique. Surface finish of SLS printed parts is not good and Abrasive Flow Machining (AFM) can be used to finish these surfaces. In this process, a semi-solid abrasive media is used that can finish the complex geometry and inaccessible areas of parts. Surface finish obtained from the AFM process rely upon various workpiece-based, media-based, and machine-based parameters. In this study, extrusion pressure, media flow speed (machine based), and abrasive mesh size (media-based) parameters at three different levels are taken during the finishing. The design of experimentation was done using the Taguchi L9 orthogonal array method, and an assessment of Material Removal (MR) and surface roughness percentage change (% ∆Ra) at the surfaces was done with help of signal-to-noise ratio (S/N ratio), and analysis of variance (ANOVA). Minitab 18 software was used to optimize the output of the process responses. Experimentally, a maximum value of MR 69 mg and maximum improvement in surface roughness of 25.19% were obtained in this study. Every material, product, and production process have ecological impact. In order, to find out the impact on the environment or ecological impact a life cycle assessment study has been done on the finishing of polylactic acid parts using both hydrogel-based and polymer-based abrasive media. The PLA parts, fabricated using Fused Deposition Modeling (FDM) process, have been finished through AFM. Then, Life Cycle Assessment (LCA) analysis has been performed using SimaPro (version 9.1.0.8) software. The energy consumed during media preparation, printing of workpiece, and AFM, media constituents, and work material were considered as inventory for LCA analysis. The ReCiPe 2016 V 1.04 midpoint(E) and endpoint(E) module available was used for impact assessment. The LCA results showed that hydrogel-based AFM process has less adverse effect on environment than polymer-based AFM process. Also, power consumed at different stages was found to be a significant contributor to the impact on environment. The results of this LCA analysis provides a base for sustainability assessment in AFM process. 2022-05-01T00:00:00Z http://localhost:8081/jspui/handle/123456789/20735 Title: MACHINE LEARNING MODEL FOR PREDICTING MECHANICAL PROPERTIES OF NATURAL FIBER COMPOSITE MATERIALS Authors: Ratre, Sagar Kumar Abstract: The increasing awareness for environmental sustainability has led to emerging eco-friendly materials. Composite materials have various applications in different sectors such as automobiles, healthcare, and daily use products. The usability of natural fiber reinforced composites are essential due to its various advantages over synthetic fiber composites. Machine learning (ML) has evolved in recent times. The use of modern technologies in composites provides the necessary scope and depth in research. In this dissertation, different articles have been evaluated to screen out the data for training the ML model for predicting the mechanical properties of natural fier reinforced composites. This study deployed linear regression as ML algorithm and programming was performed on Pycharm community and Jupyter notebook. Python programming language and python libraries such as sklearn, tkinter, pandas, numpy, matplotlib has been used. The dissertation established relation among mechanical properties. The user selects the fiber and polymer and defines the volume fraction, density, area density, and fiber orientation as per the product requirement. Based on the inputs, the graphic user interface (GUI) displays the mechanical properties (ultimate tensile strength, young’s modulus, compression modulus, compressive strength, poisson ratio, strain at failure (in %)) predicted by the ML model. The interactive interface also displays the accuracy of the ML model. 2022-05-01T00:00:00Z http://localhost:8081/jspui/handle/123456789/20734 Title: STATISTICAL MODELING OF AN INTEGRATED BOILER Authors: Nautiyal, Sarvajeet Singh Abstract: In the modern world we all are able to see the amount of energy needed for fulfillment of the demand . So for meeting the demand we had established power plants that gives energy. In this scenario we have more number of thermal power plant that produces energy in the form of electricity after burning the fossils. After surveying so number of energy plants we have decided that the old existing power plants are based on the subcritical technology that has a low efficiency and it is not capable of meeting the demand of energy . So we need to focus on these plants to increasing the efficiency of the thermal power plants. That plants which is working on the subcritical technology has efficiency around 34%. But if we look modern world then modern thermal power station working on the principle of supercritical technology and these plants getting efficiency around 53%. So after discussing all the parameters we concluded that we need to increase the efficiency of old existing power plants for reducing the gap of supply and demand pattern. After getting new regression analysis model we check its capabilities and effectiveness with the help of coefficient of determination methods like we are performed R2 techniques. In this we can know the how many number of independent variables has significant effect of dependent variable. After this we performed the error analysis. First we calculate the individual unit error and then compared to actual model and after that we performed combined model error analysis. For these we used Response Surface Methodology in combination of DOE. 2022-05-01T00:00:00Z http://localhost:8081/jspui/handle/123456789/20733 Title: SUPPLY CHAIN MANAGEMENT INTEGRATED WITH BLOCKCHAIN TECHNOLOGY TOWARDS MILITARY LOGISTICS TRANSFORMATION Authors: Atmaram, Satya Sharan Abstract: The raison d' être of the topic at hand is to focus on the aspect of Military Logistics and its integration with Blockchain Technology. Supply Chain Management is not a novel concept now and has been there in the industry since 1960’s and 1970’s. It’s nothing but an addition over the Logistics Management of the erstwhile era and has actually engulfed Logistics as one of its domains. Both of them complement each other for the effective distribution of goods and services. But technology is like a river flowing in all its might, it is ever-evolving and presenting numerous challenges and rapid changes are taking almost every single day. The time for a disruption in the existing Supply Chain has come with the advent of blockchain technology as a form of Disruptive Technology that is going to change the landscape of Supply Chain Management and Logistics for ever. Blockchain technology is the basic technology behind the Cryptocurrency and fortunately not limited to the cryptocurrency domain, but has far wider implications. The main purpose of this review is to study the synergistic integration of blockchain technology with supply chain management and the ramifications in military logistics in times to come. The preview of this research work has been to understand the military logistics its nuances specially the Indian military logistics its strength , weakness , opportunities and challenges . The barrier(s) of blockchain adoption that is likely to occur and the mitigation strategies that may be of importance to negate these barriers in the military logistical framework has been the final outcome of this reasearh. In doing so the MCDM techniques of BWM(best worst methodology) and the QFD (Quality Functional Deployment) have been amalgamated together to arrive at a conclusion of the best mitigating strategy for the barriers of blockchain in supply chain. The research work starts with an introduction followed by the motivation to engage in the work. Subsequently the research problem and the objectives of the researchare dwelled upon . The research methodology adopted in the research work has also been outlined at the beginning of the research . 2022-05-01T00:00:00Z