Department of Mechanical engineering
Permanent URI for this collectionhttp://localhost:4000/handle/123456789/1921
Browse
108 results
Search Results
Item Development and optimization of pearl millet waste biocomposite ceiling tiles: a waste management approach(Springer Nature, 2025-07) Routroy, SrikantaThe present study aims to develop and optimize sustainable biocomposite ceiling tiles by partially replacing gypsum with pearl millet waste, combined with Waste Wheat Flour (WWF) and waste paper. It aims to provide a sustainable alternative to conventional gypsum-based product, maintaining thermal insulation and flexural strength. Taguchi method was employed for experimental design, by varying key parameters such as gypsum, Pearl Millet Seed Covering (PMSC), and ceiling tile thickness. The signal-to-noise (S/N) ratio was used to identify the optimal composition and Analysis of Variance (ANOVA) with regression analysis determines the significance of each factor on thermal conductivity and flexural strength. The optimized composition for minimum thermal conductivity (0.065 W/m·K) was identified as 45% PMSC and 10% gypsum at 12 mm thickness. For maximum flexural strength (1.24 MPa), the optimal mix was 55% PMSC and 30% gypsum at 14 mm thickness. The finding underscore the critical influence of gypsum and tile thickness in enhancing material performance. The developed regression models exhibited predictive R2 value of 96.90% for thermal conductivity and 94.44% for flexural strength and an error margin below 3%, confirming the robustness of the approach. This study is original and introduces pearl millet waste biocomposites as eco-friendly alternatives to gypsum ceiling tiles. These tiles hold practical implications in ceiling, partition walls and decorative finishes across various geographic regions, contributing significantly to environmental sustainability and energy-efficient building solutions.Item A multiple regression model to analyze the impact of endogenous factors on pearl millet and stover yield in India(Emerald, 2025-08) Routroy, Srikanta; Sharma, Satyendra KumarThe purpose of the study is to explore the impact of endogenous (farmer-controlled) factors on both pearl millet and stover yield. The study uses descriptive and inferential statistics to analyze farmer-controlled factors affecting pearl millet and stover yields, based on 473 survey responses from Rajasthan’s semiarid zones, analyzed with Minitab 21.4. The descriptive results indicate widespread use of desi seeds (77.4%) and organic fertilizers (67.4%), extensive crop rotation (78%), low intercropping (12%) and extensive dependence on rainfall (70%). The multiple regression analysis indicates irrigation frequency, seed type, fertilizer type and crop rotation as major drivers of yield. The most efficient combination of hybrid seeds, inorganic fertilizers, intercropping and high irrigation frequency yields the best yields. The least efficient combination of desi seeds, no fertilizer, no intercropping and very low irrigation frequency yields low yield levels. The findings validate targeted input strategies and policy reforms.Item Assessment of risk propagation in an e-waste collection system using Bayesian networks(Springer, 2025-03) Routroy, Srikanta; Dasgupta, Mani SankarThe widespread use of electrical and electronic devices has become integral to modern life, transforming communication and day-to-day work; however, this has led to a significant challenge in effectively managing the growing volume of electronic waste (e-waste). Effective e-waste management faces a substantial challenge as the collection rates remain low, primarily due to inadequate collection systems and socioeconomic disparities. The present study investigates the assessment of various prominent risks affecting the e-waste collection system. It aims to examine the e-waste collection risk propagation categorized into social, environmental, economic, technical, and policy aspects. The Bayesian network approach is utilized to address a range of potential risks. The key findings indicate inconsistencies in the data collected on e-waste, including information such as collection date and time, location, and technical details. These inconsistencies are observed both between users or customers and e-waste collection agencies, as well as among the country's administration officials. In improving the e-waste collection system, the pivotal factors contributing to improvement were found to be technical and social risks. The insights of this study provide valuable information for policymakers to make informed decisions about promoting sustainable e-waste management practices.Item Towards sustainable transportation: factors influencing electric vehicle charging stations development(Elsevier, 2025-05) Digalwar, Abhijeet K.; Routroy, SrikantaThe Indian transportation sector, reliant on fossil fuels, is predominantly accountable for the emergence of critical challenges such as greenhouse gas emissions, reliance on foreign energy sources, economic strain, and persistent health repercussions. In order to mitigate these urgent challenges, electric vehicles (EVs) are conceptualised as a viable, sustainable and ecologically sound technological solution, capable of successfully transitioning towards a sustainable low-carbon emission transportation framework and preserving finite natural resources. EVs encounter significant challenges in achieving rapid assimilation into the commercial landscape, and one of the most frequently referenced impediments to the accelerated adoption of EVs is the insufficiency of charging infrastructure along with the resultant range anxiety. Nevertheless, expanding the charging infrastructure network is financially burdensome and necessitates careful and strategic planning. Despite identifying essential factors, the inquiry “In what manner do these factors engage and interact?” has predominantly remained unaddressed in empirical investigations. Examining the interactions between these variables will empower producers and regulatory authorities to participate in systematic planning and devise suitable measures to govern these variables. The prime objective of this research is to execute an exhaustive assessment and furnish insights into the multifaceted factors/criteria influencing the establishment and development of EV charging infrastructure within a developing nation such as India. Factors are extracted from previous studies through literature reviews and expert interviews. The study also validates the identified factors empirically. Subsequently, a mixed-method approach is utilised to implement a combination of Interpretive Structural Modeling (ISM) and Decision-Making Trial and Evaluation Laboratory (DEMATEL). This methodology enables a methodical exploration of the hierarchical structures and interconnections among the variables, thereby enhancing the comprehension of their influence on the implementation and efficacy of charging infrastructure. The study identifies technological, economic, political, geographical, environmental, geopolitical, and socio-technical factors as key drivers influencing EV charging infrastructure development, highlighting the interdependencies between critical variables and providing a structured framework to enhance accessibility, scalability, and sustainability in alignment with global Sustainable Development Goals (SDGs) 7 and 13.Item Modelling factors influencing charging station location selection to accelerate ev adoption in India: an ISM-MICMAC analysis(Springer, 2023-12) Digalwar, Abhijeet Kumar; Routroy, SrikantaElectric vehicles (EVs) are rising fast to prominence as a key component of the effort to meet sustainable energy goals. The research and mass manufacturing of new energy vehicles, especially electric vehicles, offer several benefits over conventional energy vehicles, such as zero exhaust emissions, zero pollution, cleanliness, and low cost. As a result, more and more nations are paying attention and placing importance over the development of EV-fleet, but EV sales are still a modest part of all vehicle sales. The protruding reason highlighted by the literature and researchers is underdeveloped charging infrastructure. To get the most out of an EV, an appropriate charging station with optimum configuration needs to be placed in a specific location with all the infrastructure to make it supportive and sustainable hotspot for EVs. This study aims to identify all the factors that needs to be considered while selecting a location for setting up a sustainable charging station for EVs in semi-urban areas. A deeper understanding of factors is explored, using interpretive structural modelling (ISM) and MICMAC analysis. A total of 17 factors are considered for the analysis which are crucial in developing the configurations for an EV charging station. The outcomes of the paper will support the policymakers to locate, determine and decide the suitable locations, and configuration for constructing EV charging stations and escalate the EV adoption.Item A data-driven framework for optimizing multi-period ev charging infrastructure deployment(IEEE, 2024-12) Digalwar, Abhijeet Kumar; Routroy, SrikantaThe rise of electric vehicles represents a transformative shift in the automotive industry, signaling the dawn of a new era of clean, sustainable transportation, but their operation requires a distributed rapid-charging infrastructure. Building such rapid charging networks is currently capital-intensive and therefore, requires careful planning and the development of the charging infrastructure must be maintained. However, infrastructure construction is not a one-off investment but a multi-period plan. A multi-period location and capacity expansion model of the charging stations will be needed. This study proposes a novel data-driven framework for deploying suitable rapid-charging infrastructure for EVs in large urban areas. This study combines an iterative clustering technique with a geographical information system analysis tool to determine the suitable regions for developing an optimized EV charging service. The analysis intends to plan a case study for Gurugram City of India and suggest the locations that should be the potential points for consideration of charging station development.Item An integrated modelling and optimization approach for the selection of process parameters for variable power consumption machining processes(Springer, 2023-08) Routroy, Srikanta; Garg, Girish KantManufacturing industries are under intense pressure to reduce the energy usage of the machining processes without sacrificing productivity, owing to the fast-rising worldwide market and environmental issues. Variable-power consumption machining processes are highly complex than constant-power consumption machining processes, owing to change in one of the process parameters, i.e. cutting speed during end facing. Besides, integrated modelling and optimization of the variable power consumption machining processes for energy-saving have not received attention, consequently, industry deployment of energy-saving solutions is impeded. To bridge these gaps, in this work, the empirical model developed by the author is integrated for the formulation of a multi-objective optimization model of cutting energy consumption (Ecdry) and average-material removal rate (MRR¯¯¯¯¯¯¯¯¯¯¯¯) expressed by process parameters. First, the optimal parameters are determined for Ecdry and MRR¯¯¯¯¯¯¯¯¯¯¯¯ by mono-objective optimization using the Taguchi technique. Second, Grey relational analysis coupled with the Taguchi method is used to obtain the cumulative performance index of the Ecdry and MRR¯¯¯¯¯¯¯¯¯¯¯¯, and to determine their common optimal parameters, resulting in better-compromised decisions. The MRR¯¯¯¯¯¯¯¯¯¯¯¯ improves to 99.97% with only a 10.08% increase in Ecdry on common optimal parameters compared to optimal parameters with mono optimization of Ecdry. Further, analysis of variance revealed that all considered process parameters have statistical significance, and depth of cut is the most significant parameter followed by spindle speed, feed rate and tool nose radius. It was found that energy consumption values predicted by the integrated modelling and optimization approach are close to the experimental values.Item Application of Optimization and Statistical Techniques in Post-Harvest Supply Chain: A Systematic Literature Survey(CRC Press, 2021) Garg, Girish Kant; Routroy, SrikantaThe objective of this literature survey is to address the utility and potential of optimization, statistical surveys and mathematical research into post-harvest supply chains (PHSCs) to reduce losses. Empirical approaches have always helped to understand a generic issue with a specific perspective to highlight the shortcomings with the existing practice. The optimization approaches are used in the PHSC literature to design an optimum system to enhance revenues and to minimize losses. The existing PHSCs in developing countries such as India suffer enormous losses – e.g., revenue losses, physical damage of produce, microbial losses, qualitative losses, quantitative losses, etc. – in the absence of market prospects due to inefficient packaging for transportation and handling. This study covers a systematic literature survey covering the mathematical, statistical and optimization research performed in the field of PHSC and critical analysis to highlight the key aspects covered in the literature and their future scope.Item Fuzzy-TOPSIS based multi-objective optimization of machining parameters for improving energy consumption and productivity(Elsevier, 2021) Garg, Girish Kant; Routroy, SrikantaDue to the increasingly global market and environmental challenges, there is a lot of pressure on manufacturing industries to reduce the energy consumption of the machining process without compromising productivity. The objective of this work is to develop a multi-objective optimization model for the selection of optimal cutting parameters during the turning of an Aluminum workpiece using carbide inserts. Two performance characteristics: energy consumption and productivity were simultaneously optimized. The Taguchi full factorial orthogonal array L27 was used to obtain the experimental plan. The Fuzzy based Technique for Order Preference by Similarity to Ideal Solution (Fuzzy-TOPSIS) was applied to determine the optimal cutting parameters for multi-objective optimization. The optimal results obtained by Fuzzy-TOPSIS were further validated by using the Taguchi method. ANOVA results show that all the considered cutting parameters were statistically significant. Further, the depth of cut was found the most influencing cutting parameter on the energy consumption and productivity.Item Comparative analysis of environment losses in steel manufacturing supply chain using Taguchi loss function and design of experiments(Emerald, 2020-04) Routroy, SrikantaThe objective of this paper is to compare and evaluate the environmental performance of steel supply chains considering relevant environmental loss factors using Taguchi loss function (TLF) and design of experiments (DOE).