International Journal of Scientific Research in Mechanical and Materials Engineering
Submit Paper Now! International Journal of Scientific Research in Mechanical and Materials Engineering (IJSRMME) is peer-reviewed, online international journal published Bimonthly by Technoscience Academy. IJSRMME is a highly-selective journal, covering topics that appeal to a broad readership in various branches of Mechanical and Materials Engineering and related fields. The journal has many benefits, all geared toward strengthening research skills and advancing academic careers. Journal publications are a vital part of academic career advancement. To maintain a high-quality journal, manuscripts that appear in the IJSRMME Articles section have been subjected to a rigorous review process. This includes blind reviews by one or more members of the international editorial review board, followed by a detailed review by the IJSRMME editors. Email addresses for submitting articles are ijsrmme@gmail.com, editor@ijsrmme.com JOURNAL INFORMATION Title : International Journal of Scientific Research in Mechanical and Materials Engineering Frequency : Bimonthly E-ISSN : 2457-0435 Publisher : Technoscience Academy [ https://technoscienceacademy.com ] Refereed : Peer Review Copyright : Technoscience Academy, India Starting Year : 2017 Subject : Mechanical and Materials Engineering Language : English Distribution : Open Access Publication Format : PDF & HTML -> Online Document Identifier Type : DOI (https://doi.org/10.32628/IJSRMME ) Email Id : editor@ijsrmme.com, ijsrmme@gmail.com Mobile No. : +91-8160745806 (WhatsApp support only) Website : https://ijsrmme.com
Experimental Investigation and Multi-Parameter Optimization of Compression Ignition Engine Performance Using Cottonseed and Other Biodiesel Blends through Taguchi and Grey Relational Analysis
The depletion of fossil fuels and the growing concerns over environmental degradation have stimulated research into renewable biofuels as sustainable alternatives to conventional diesel. This study presents an experimental investigation and optimization of a compression ignition (C.I.) engine operated with various biodiesel–diesel blends derived from cottonseed, Jatropha and Neem oils. Experiments were conducted using a single-cylinder, 4-stroke, direct injection (DI), water-cooled diesel engine under varying loads, speeds and blend ratios. The Design of Experiments (DOE) approach was implemented using the Taguchi L9 orthogonal array to evaluate the combined influence of control parameters such as blend ratio, engine load and speed on engine performance indicators—namely Brake Thermal Efficiency (BTE), Brake Specific Fuel Consumption (BSFC) and emission characteristics. Grey Relational Analysis (GRA) was employed for multi-response optimization to identify the ideal operational parameters for maximum efficiency and minimal emissions. Results reveal that a B20 cottonseed biodiesel blend at 195 bar injection pressure provided optimal performance, achieving a peak brake thermal efficiency of 34.01% with reduced specific fuel consumption and smoke density. Comparative analysis with Jatropha and Neem biodiesels confirmed cottonseed biodiesel’s superior trade-off between performance and emission control. The developed mathematical model for thermal efficiency validated experimental results with minimal error, demonstrating the potential of cottonseed biodiesel as a viable renewable substitute for conventional diesel fuel.
Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
Smart-Flow: An IoT-Enabled Automated Petrol Pump System
Traditional fuel dispensing systems rely heavily on manual operations, which often result in inaccurate fuel measurement, long waiting times, lack of transparency, and operational inefficiencies. With the rapid growth of smart infrastructure and digital payment adoption, there is a strong need for an automated and reliable fuel dispensing solution. This paper presents Smart-Flow, an IoT-enabled automated fuel dispensing system that integrates precise flow sensing, microcontroller-based control, and hybrid payment mechanisms supporting both cash and UPI-based transactions. The system ensures accurate fuel delivery, reduces human intervention, and enables real-time data monitoring through cloud connectivity. Experimental observations indicate improved dispensing accuracy, faster service time, and enhanced transparency compared to traditional fuel stations. The proposed system is suitable for modern fuel stations and smart city applications.
Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0
A Novel Mass-Energy Equivalence from Lorentz Factor and Relativistic Momentum
Initial interpretations of Einstein’s mass-energy equivalence often foster the misconception that an object’s mass increases as its velocity approaches the speed of light. This article aims to correct this outdated view by presenting a modern perspective where mass is treated as an invariant property. By redefining momentum through proper time and time dilation, this paper provides a rigorous derivation of relativistic momentum and the accurate mass-energy equation while bridging these concepts to the fundamental energy-momentum relation.
Experimental Evaluation of the Effect of Fiber Type on Mechanical Properties of Concrete
Concrete is inherently strong in compression but weak in tension, leading to brittle failure and crack propagation under service loads. Fiber Reinforced Concrete (FRC) has been developed to address these limitations through the inclusion of discrete fibers that enhance mechanical performance. The present study experimentally evaluates the effect of different fiber types on the mechanical properties of concrete, with specific emphasis on compressive and flexural strength. Steel fibers and synthetic fibers were incorporated into M25, M30, and M40 grade concrete mixes in controlled proportions. Standard laboratory tests were conducted to assess workability, compressive strength at 7 and 28 days, and flexural strength at 28 days. The results demonstrate that while fiber inclusion has a marginal effect on compressive strength, it significantly improves flexural strength, ductility, and post-cracking behavior. Steel fiber reinforced concrete exhibited superior performance compared to synthetic fiber reinforced concrete, particularly in flexural strength enhancement and crack control. The findings confirm that fiber type plays a critical role in determining the mechanical performance of Fiber Reinforced Concrete and supports its application in structural and pavement engineering.
Finite Element Stress and Fatigue Analysis of Buried Steam Distribution Pipelines for District Heating in Philadelphia
This study presents a comprehensive finite element investigation of stress distribution, fatigue life, and deformation behavior in buried steam distribution pipelines serving Philadelphia’s district heating network. Aging pipelines in urban environments are subjected to complex loading conditions, including thermal cycling, internal pressure, soil–pipe interaction, and geometric discontinuities, all of which significantly influence long-term structural integrity. The analysis reveals that weld joints, elbows, and fixed support locations experience the highest stress concentrations due to multi-axial loading and constrained thermal expansion. Fatigue life predictions show accelerated crack initiation in areas where thermal gradients and soil stiffness variations overlap, particularly in neighborhoods with soft clay soils and shallow-burial installations. Field inspection images corroborate the numerical findings by showing visible cracking and deformation in high-stress regions. Thermal cycling emerged as the dominant fatigue driver, while insulation effectiveness proved crucial in moderating deformation severity. A combined evaluation of soil conditions and operational temperature fluctuations highlights the need for targeted engineering interventions. Recommendations include reinforcement of critical sections, improved insulation strategies, soil stabilization, and deployment of real-time monitoring systems such as fiber-optic strain sensing and thermal imaging. The study’s findings provide actionable insights for district heating operators, emphasizing the importance of risk-based asset management and integration with smart city monitoring frameworks. Overall, this research enhances understanding of the failure mechanisms governing buried steam pipelines and offers practical guidance to improve reliability, safety, and long-term performance within Philadelphia’s district heating infrastructure.
Study of Tensile Behaviour of Polymer Hybrid Composite at High Strain Rates
The present study reports the strain rate dependence of tensile properties in p-Aramid, Ultra high Molecular Weight Polyethylene (UHMWPE) and p-Aramid/UHMWPE based compression moulded hybrid composites. A Split Hopkinson’s Pressure Bar (SHPB) apparatus capable of conducting tensile testing was used for experimental investigation at different strain rate varying from 1400/s to 2000/s. The effect of strain rate on failure behaviour of such composites has been experimentally evaluated. It is found that the stress to failure in these composites is enhanced with increase of strain rate. There is a radical change in magnitude of peak stress of p-Aramid composites by 32% with the variation of strain rate from 1400/s to 2000/s as compared to 8% and 17% peak stress variation for UHMWPE and p-Aramid/UHMWPE hybrid composites, respectively. A viscoelastic material model to describe the strain rate dependent tensile behaviour of hybrid composite is also presented, where the rate dependent characteristics of the hybrid composite has been described by three term Maxwell model. The result of material model has been compared with the experimental results. It is observed to have a good match between the predicted (mathematical model) and experimental results with only variation of 4% to 9%.
Optimization of Processing Parameters for Compression Molding of a Hybrid Composite
The main aim of this work is to investigate and optimize the process variables related to the flexural strength properties of UHMWPE and p-Aramid based hybrid composite. In this work, an optimization of processing parameters of compression molding of hybrid composite has been carried out employing surface response methodology (RSM). A three level Box-Behnken design was employed based on the process parameters pressure (X1), temperature (X2) and time (X3) as the independent variables with the optimization based on flexural strength. Regression equation has been obtained to analyze flexural strength and the optimum parameters were identified. The results obtained in flexural test showed the optimized process variable derived by RSM were 145.16 kg/cm2 for pressure, 119.59 0C for temperature and 12.68 minutes for time. The best flexural property were observed if the composite panel is manufactured at optimized processing conditions. The actual values of flexural strength are in good agreement with the predicted values.
Sustainable Nano-fluid-Assisted MQL Machining of Titanium Alloys: A Review of Trends, Barriers, and Future Pathways
This review presents an integrated assessment of the current state-of-the-art in sustainable machining, with particular emphasis on advanced lubrication and cooling strategies for titanium alloys. Given the high strength, low thermal conductivity, and chemical reactivity of titanium alloys, selecting environmentally responsible and effective machining approaches is essential. The review critically examines the growing use of nanoparticle-amended vegetable oils in Minimum Quantity Lubrication (MQL) systems, highlighting their tribological advantages, enhanced heat dissipation, improved wettability, and positive influence on tool wear, cutting forces, surface integrity, and overall machining efficiency. Complementary sustainable techniques including cryogenic cooling, hybrid cooling–lubrication methods, waste-reduction practices, and energy-efficient process optimization are also evaluated to position nano-enhanced MQL within the broader framework of green manufacturing. The discussion further incorporates sustainable manufacturing principles focused on reducing machining stages, minimizing material and energy consumption, and improving operational efficiency. By synthesizing current knowledge and identifying critical research gaps related to nanoparticle stability, high-speed lubrication delivery, mist formation, and environmental impact, this review contributes to directorial future studies toward more resource-efficient, eco-friendly, and high-performance machining solutions for titanium alloys.
A Systematic Implementation of Six Sigma for Productivity Enhancement in Small-Scale Engineering Industries
In today’s highly competitive manufacturing environment, small-scale industries encounter significant challenges in maintaining consistent productivity and quality due to resource constraints and process variability. This study presents a systematic application of the Six Sigma DMAIC (Define–Measure–Analyze–Improve–Control) methodology for productivity enhancement in a small-scale engineering enterprise, Prismetic Industries. The research adopts a case-based approach, integrating process mapping, measurement system analysis, and statistical tools to identify and mitigate sources of inefficiency in machining operations. During the Define and Measure phases, key process parameters and critical-to-quality characteristics were identified to establish a baseline understanding of process performance. Detailed analysis revealed that inconsistencies in tool wear, fixture setup, and inspection practices were the primary causes of variation affecting both quality and throughput. Focused improvement actions were implemented through preventive maintenance, standardization of setup procedures, and operator training programs, resulting in marked improvement in process stability, quality consistency, and overall productivity. The Control phase emphasized long-term sustainability of these improvements through regular process monitoring, control charts, and visual management techniques. The results confirmed that the Six Sigma approach not only improved operational performance but also enhanced process discipline and employee engagement across the organization. This study demonstrates that with structured methodology, management commitment, and team collaboration, small-scale industries can effectively achieve productivity enhancement and quality improvement using Six Sigma principles.
Mechanical Characterization and End-Use Determination for composites made with Flax-LDPE Wastes
In this research work, fibre, sliver and yarn wastes of flax and LDPE wastes are used to produce composite products for fencing and boarding panel applications. With fibre to matrix volume fraction of 50:50 and for the pre planned production of 1kg of composite product, the materials have been weighed and using compression moulding machine composite samples have been produced. Mechanical testing and characterizations have been made for; impact resistance, tensile, compression and flexural strength performances. In almost all the characterizations made, the flax-LDPE composite product shows comparable and better performance properties in comparison to the commercially available fencing and boarding panel products.
Design and Development of a Cost-Effective Hydraulic Screw Jack-Based Punch-Die System for Small-Scale Manufacturing
This paper presents the design and development of a cost-effective punch-die system integrated with a hydraulic screw jack for small-scale sheet metal manufacturing applications. Conventional punching machines are often expensive, bulky, and dependent on external power sources, making them unsuitable for rural workshops, cottage industries, and educational laboratories. The proposed system addresses these limitations through a compact, frame-based design fabricated from mild steel and equipped with a 10-ton manual hydraulic screw jack. The punch and die, manufactured from EN31 and H13 tool steels, respectively, ensure durability and precision in operations such as washer fabrication. Finite Element Analysis (FEA) was conducted to evaluate stress distribution and load-bearing capacity, confirming structural safety and minimal deflection under maximum load conditions. Experimental validation demonstrated consistent punching performance for mild steel sheets up to 3–5 mm thickness, with accurate force transmission, safety, and ease of operation. The system is portable, low-maintenance, and adaptable through interchangeable die sets, making it a versatile tool for training, prototyping, and small-scale production. By eliminating dependence on electricity and high-cost machinery, this design provides a practical solution for resource-constrained environments and offers significant potential for adoption in MSMEs and vocational education.
Investigating of Hard Turning of Automotive Gears with Polycrystalline Copper Nitride (PCBN) Tools as a Substitute for Grinding
A traditional machining process, grinding, is used for finishing of hardened automotive gears with complex shapes and forms. The main limitations associated with the grinding process for such type of components are multiple setups, low productivity, less flexibility, high equipment cost, high production cost, and environmental issues related to disposal of used up coolant and grinding dust. In view of such limitations, an alternate machining method hard turning is studied in this article for finishing of the gears. The gears material is 20Mn5Cr5 steel was attained through heat treatment. In these experiments, we were conducted with PCBN tools. The CNC turning centre was used for conducting hard turning. The machining parameters: feed rate (f), depth of cut and cutting speed (vc) to be taken on response attributes: surface roughness and the tool wear. Taguchi DOE, ANOVA, and S/N ratio methods have been applied for optimization. In this study, the roughness of surface and accuracy of quality performance characteristics such as cylindricity, circularity, and straightness obtained in both the processes (hard turning and grinding) were compared. An economic analysis has been conducted for evaluating the potential of hard turning to replace grinding for short machining length components. As the result, feed rate (61%) and depth of cut (36%) highly affects the surface roughness but the cutting speed was insignificant parameter with contribution of (<2 %). The tool wear was affected most by cutting speed with a contribution of 78%. In this paper, it reported that hard turning is an alternate machining technology to cylindrical grinding in machining of hardened automotive gears using a PCBN tool on a modern CNC turning centre.
A Review Paper on Hard Turning of Automotive Gears with Polycrystalline Copper Nitride Tools as a Substitute for Grinding
A traditional machining process, grinding, is used for finishing of hardened automotive gears with complex shapes and forms. The main limitations associated with the grinding process for such type of components are multiple setups, low productivity, less flexibility, high equipment cost, high production cost, and environmental issues related to disposal of used up coolant and grinding dust. In view of such limitations, an alternate machining method hard turning is studied in this article for finishing of the gears. The gears material is 20Mn5Cr5 steel was attained through heat treatment. In these experiments, we were conducted with PCBN tools. The CNC turning centre was used for conducting hard turning. The machining parameters: feed rate (f), depth of cut and cutting speed (vc) to be taken on response attributes: surface roughness and the tool wear. Taguchi DOE, ANOVA, and S/N ratio methods have been applied for optimization. In this study, the roughness of surface and accuracy of quality performance characteristics such as cylindricity, circularity, and straightness obtained in both the processes (hard turning and grinding) were compared. An economic analysis has been conducted for evaluating the potential of hard turning to replace grinding for short machining length components.
Analysis of Falling Ball under the Influence of Gravity using MSC Adams
The paper focusses on the analysis of falling ball from a certain height under the influence of gravity. The analysis includes study of displacement, velocity and acceleration of the falling ball. The study is carried out in MSC Adams software. This includes mechanical modelling of the system, setting the initial conditions and simulating the model to understand the characteristics. Verification of the model is also carried out.
Optimizing EDM Process Parameters for Enhanced Surface Finish and Metal Removal Rate (MRR)
Electrical Discharge Machining (EDM) has emerged as a vital non-traditional machining process for producing complex geometries and machining hard-to-cut materials with high precision. Unlike conventional methods, EDM relies on thermoelectric energy in the form of controlled electrical discharges between the tool and workpiece immersed in a dielectric medium. Among the critical challenges in EDM, achieving a balance between material removal rate (MRR) and surface finish has been widely acknowledged. Higher discharge energy generally enhances MRR but deteriorates surface quality, while lower energy settings improve smoothness at the cost of reduced productivity. This study investigates the underlying mechanisms governing this trade-off and explores process parameter optimization for simultaneous improvement in MRR and surface finish. Experimental trials were conducted using varying pulse currents, discharge voltages, and duty cycles to evaluate their effects on machining performance. Surface roughness (Ra) was measured using a profilometer, while MRR was calculated based on weight loss method. The results reveal that moderate discharge energy combined with optimized duty cycle significantly improves MRR without compromising surface smoothness. The thermal and physical mechanisms, including controlled crater formation and plasma channel stabilization, are identified as key contributors to this improvement. The experimental findings demonstrate that optimized pulse current and duty cycle lead to an improvement of up to 20–25% in MRR while simultaneously reducing surface roughness by nearly 15% compared to conventional settings.
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Mechanical and Thermal Properties of Nano-Sio2 Epoxy Coir Fiber Reinforced Composites with Conventional Epoxy-Based Composites
Comprehensive analysis of nano-SiO2-reinforced epoxy composites and compared them with commonly used coir fabric. For both static and dynamic applications, coir fabric composites were considered as suitable material due to their strength and biodegradability. In this research, 15 nm SiO2 nano powder was used as a filler. Several composite laminates with different filler concentrations of 2%, 3%, and 5% SiO2 by weight of the epoxy resin were fabricated using hand lay-up method (LY556). Various testing methods, including tensile testing, impact testing, wear testing, moisture absorption testing, and thermogravimetric analysis (TGA), were employed to evaluate the properties of the final composite. The results indicated that the mechanical and thermal characteristics of the produced composite were significantly influenced by the filler material.
A Review on Aircraft Manufacturing System Design based on Ergonomic Simulation
The way aircraft are manufactured plays a crucial role in shaping efficiency, costs, and overall quality in the aerospace industry. This study delves into the key principles, methodologies, and technological advancements that define modern aircraft manufacturing system design. It examines both traditional and emerging approaches, such as assembly line optimization, automation, digital twin technology, and Industry 4.0 applications. Additionally, it explores how lean manufacturing, Just-In-Time (JIT) production, and additive manufacturing (3D printing) are helping to improve efficiency and reduce waste. Beyond the technical aspects, this research also highlights some of the major challenges in aircraft manufacturing, including complex supply chains, material selection, precision engineering, and regulatory compliance. By analysing case studies from leading aerospace manufacturers, the study uncovers best practices and the latest trends shaping the industry. Through real-world examples, it provides insights into how companies refine their production processes to meet growing demands for safety, sustainability, and cost-effectiveness. This research adds to the existing body of knowledge by offering an in-depth look at how aircraft manufacturing is evolving. The findings can serve as a valuable resource for aerospace manufacturers, engineers, and policymakers looking to make informed decisions about improving production efficiency, reducing costs, and enhancing aircraft performance. Ultimately, this paper highlights the importance of integrating advanced technologies and lean methodologies to build a more sustainable and efficient future for aircraft manufacturing.
Reviewing the Advances in Photovoltaic Materials for Solar Energy: A Global Perspective
The quest for sustainable and clean energy sources has propelled intense research and development in the field of photovoltaics, aiming to harness solar energy efficiently. This Review reviews the recent advances in photovoltaic materials on a global scale, providing a comprehensive overview of the innovations that hold promise for enhancing the efficiency, durability, and cost-effectiveness of solar energy conversion technologies.The rapid evolution of photovoltaic materials has been driven by the need to address the challenges associated with traditional silicon-based solar cells. This review explores the emergence of novel materials, such as perovskites, organic polymers, and quantum dots, which have exhibited remarkable photovoltaic properties. Perovskite solar cells, in particular, have garnered attention for their low-cost fabrication, ease of scalability, and competitive power conversion efficiencies, heralding a paradigm shift in the solar energy landscape.Moreover, the global perspective presented in this review highlights the collaborative efforts of researchers, industries, and policymakers across diverse regions. Regions such as Asia, Europe, and North America have witnessed significant investments and strategic initiatives aimed at advancing photovoltaic technologies. The exploration of regional approaches and trends offers valuable insights into the diverse strategies employed to propel the adoption of solar energy on a global scale.Furthermore, the review delves into breakthroughs in material engineering, including advancements in thin-film technologies, tandem solar cells, and innovative manufacturing processes. These breakthroughs not only contribute to improving the performance of photovoltaic devices but also pave the way for the integration of solar energy solutions into various applications, from portable electronics to building-integrated photovoltaics.In conclusion, this Review provides a snapshot of the dynamic landscape of photovoltaic materials, showcasing how global research efforts are shaping the future of solar energy. The ongoing innovations in materials science, coupled with collaborative initiatives on an international scale, are pivotal in realizing the full potential of solar energy as a sustainable and ubiquitous power source.
Sustainable Retrofitting of Existing Buildings: Techniques and Case Studies
Retrofitting existing buildings for sustainability has become a critical endeavor in the quest for more energy-efficient and environmentally friendly built environments. This abstract explores the techniques and case studies associated with sustainable retrofitting, highlighting the challenges, benefits, and best practices in this field. The sustainable retrofitting of existing buildings involves the application of innovative technologies and strategies to improve energy efficiency, reduce environmental impact, and enhance occupant comfort. Techniques such as improved insulation, energy-efficient lighting, and HVAC system upgrades are commonly employed to achieve these goals. Additionally, the integration of renewable energy sources, such as solar panels and wind turbines, can further enhance the sustainability of retrofitted buildings. Several case studies illustrate the successful implementation of sustainable retrofitting techniques. For example, the Empire State Building in New York City underwent a comprehensive retrofitting project that resulted in a 38% reduction in energy consumption and a 105,000 metric ton reduction in greenhouse gas emissions annually. Similarly, the Bullitt Center in Seattle, Washington, is a net-zero energy building that was retrofitted to achieve high levels of energy efficiency and environmental sustainability. Challenges associated with sustainable retrofitting include high initial costs, technical complexities, and the need for skilled labor. However, the long-term benefits, such as reduced energy bills, increased property value, and a smaller environmental footprint, outweigh these challenges. Best practices for sustainable retrofitting include conducting a thorough energy audit, engaging with stakeholders, and selecting cost-effective and environmentally friendly technologies. In conclusion, sustainable retrofitting of existing buildings is a key strategy for achieving energy efficiency and environmental sustainability in the built environment. By employing innovative techniques and drawing on successful case studies, stakeholders can overcome challenges and reap the benefits of sustainable retrofitting.
Systematic Review of Mobile Learning Models for Enhancing STEM Access in Public Secondary Schools
This systematic review explores the landscape of mobile learning models designed to enhance access to STEM education in public secondary schools. Drawing upon theoretical frameworks such as constructivism, socio-cultural learning, and cognitive load theory, the study critically analyzes typologies of mobile learning—including content delivery systems, collaborative platforms, and adaptive learning technologies—and assesses their pedagogical relevance and contextual implementation. The review identifies a diverse range of models that demonstrate potential in improving learner engagement, personalization, and inclusion within STEM subjects. Despite these innovations, the study reveals persistent barriers that hinder effective deployment, including technological limitations, infrastructural disparities, policy fragmentation, and insufficient teacher training. Institutional readiness, curriculum integration, and sustainable funding are highlighted as essential enablers for scaling mobile learning solutions in both urban and rural settings. The paper concludes by offering actionable recommendations for educators, policymakers, and school leaders, and outlines critical directions for future research aimed at fostering equitable, scalable, and culturally responsive mobile learning ecosystems in STEM education.
A Conceptual Model for BIM-Driven Geospatial Architecture: Rethinking Site Analysis and Spatial Intelligence in Early Design Stages
This paper proposes a conceptual model for integrating Building Information Modeling (BIM) with geospatial intelligence to enhance early-stage architectural design and spatial decision-making in large-scale urban infrastructure planning. Grounded in cognitive load theory, geodesign, and parametric design principles, the framework addresses the complexity and fragmentation of contemporary site analysis by enabling dynamic, data-rich, and spatially sensitive workflows. The model foregrounds the synergistic use of digital twins, spatial decision support systems, and algorithmic design to improve design cognition, stakeholder engagement, and resilience planning. By emphasizing interoperability and iterative feedback loops, the framework facilitates adaptive, climate-responsive infrastructure development, particularly suited for emerging economies facing rapid urbanization challenges. The study further explores institutional and cultural barriers to BIM-GIS adoption, proposing strategic pathways for education, governance, and professional transformation. Ultimately, this research advances theoretical discourse on smart urbanism and provides actionable insights for architects, planners, and policymakers aiming to future-proof infrastructure through integrated digital-spatial methodologies.
Effect, Performance and Conversion of Plastic to Crude Oil
Plastic was invented by Alexander Parkes in 1860. Plastics have become a crucible part in today’s world. Due to their light weight, durability, design flexibility, they are excessively used in industry as well as household and other fields. The demand for plastic is increasing day by day which now pose a tremendous threat to the environment. The study focus on the design and fabrication of machine to convert plastic into oil as an effort in finding environment-friendly means of waste recycling by means of pyrolysis. It is an alternative solution to increasing problem of waste disposal. Pyrolysis keeps running without oxygen and in high temperature of around 250°C for which reactor is manufactured to give the expected temperature to the response. The waste plastics are subjected to depolymerization, pyrolysis, catalytic cracking and fractional distillation to obtain different value added fuels such as petrol, kerosene, and diesel. Our Project deals with the extraction of oil from the waste plastics termed as plastic pyrolysed oil which can be marketed at much cheaper rates compared to that present in the market. As we know that both Plastics and Petroleum derived fuels are Hydrocarbons that contain the elements of Carbon & Hydrogen. Pyrolysis process becomes an option of waste-to-energy technology to deliver bio-fuel to replace fossil fuel. The advantage of the pyrolysis process is its ability to handle unsort and dirty plastic. The pre-treatment of the material is easy. Plastic is needed to be sorted and dried. Pyrolysis is also nontoxic or non-environmental harmful emission unlike incineration. In this investigation, plastic waste (poly propylene) are utilized for pyrolysis to get fuel oil that has comparable physical properties as the energizes like petroleum, diesel and so on Converting waste plastics into fuel hold great promise for both the environmental and economic scenarios.
AgroMax : Development of Low-Cost, Android-Controlled Spraying Robot Towards Smart Agriculture
Pesticide and herbicide applications play a critical role in safeguarding crops from pests and diseases. However, conventional manual spraying techniques are often inefficient, labor-intensive, and pose serious health risks to farmers due to prolonged exposure to harmful chemicals. These methods also tend to result in uneven chemical distribution and excessive usage, contributing to environmental concerns. Moreover, conventional approaches struggle to effectively target pests hidden beneath foliage, leading to suboptimal pest control. In response to these challenges, this research presents the design and development of an autonomous agricultural spraying robot aimed at enhancing precision, safety, and sustainability in modern farming. The system is equipped with sensors, a live-feed camera, and automated spraying nozzles, enabling real-time monitoring and targeted application of pesticides. This approach minimizes chemical wastage, reduces environmental impact, and enhances the effectiveness of pest management. By automating the spraying process, the robot also limits human exposure to hazardous substances, creating a safer working environment for agricultural workers. Additionally, the robot is powered by a rechargeable battery, making it an eco-friendly solution suitable for repetitive field operations. Designed for versatility, it can adapt to various crops and farm layouts, offering functions beyond spraying, such as grass cutting. This study demonstrates the potential of robotic automation in transforming conventional agricultural practices by providing a cost-effective, scalable, and sustainable solution. The proposed system contributes to increased productivity, and improved pest control, and supports the transition toward more environmentally responsible farming methods.
Enhancement of Process Parameters for CNC Turning Of Stainless Steel Utilizing a Coated Tool
The global environmental awareness is increased, and environmental regulations become more stringent, the negative effects of cutting fluids on the environment are becoming more apparent. At present, in high-productivity manufacturing enterprises, the supply, maintenance and recycling costs of cutting fluids account for 13%-17% of the manufacturing cost of the workpiece. In Computer Numerical Control turning of hard materials such as steels, cast iron and super alloys, involves high cutting forces, leads to more power consumption and decreasing tool life which may increases the machining cost. To make machining process environment friendly with minimizing cost of machining, dry cutting is the best solution. Current research work presents optimization of process parameters (cutting speed, feed rate and depth of cut) to minimize cutting forces and surface roughness for dry CNC turning of stainless steel (AISI 52100) using Titanium Aluminum Nitride (TiAlN) coated tungsten carbide tool. Design of experiments is conducted using well known Taguchi‘s L27 orthogonal array to collect cutting forces and surface roughness data. Optimization of process parameters for cutting forces is done using Taguchi method in Minitab software. The predictive model and optimization of surface roughness is done using Response surface methodology (RSM) in Minitab software. The significance of process parameters on responses is studied using developed model. The depth of cut is found to have more significance on cutting forces, followed by cutting speed. The feed rate is found to have more significance on surface roughness, followed by cutting force.
Using Optimization Technique, Friction Welding Process Parameters Are Experimentally Evaluated and Optimized On Identical Materials
In fabrication industry, joining processes play a very important role. Among various joining processes, welding process has more strength as compared to other joining processes. Friction welding is a solid state welding, which is used to join similar or dissimilar materials by applying pressure and without the need of filler materials for heat production. Also, friction welded joints can produce welds that are superior in strength of the parent material. Friction welding enables similar or dissimilar materials to be joined together by sliding one material against the other under pressure. Friction welding process includes upset time, upset pressure, and heating time, heating pressure and rotating speed. In this experimental work, friction joints are carried out by centre lathe machine. In this experimental work, metal joining were made by using centre lathe machine, welding of similar materials are done using the input process parameters like spindle speed, heating pressure, upset time, upset pressure, heating time, material to be welded, component size and configuration based on the literature review. Then the welded joints are tested to study and analyse the mechanical properties like axial shortening, hardness and impact strength to get the improved quality of welded joints and to optimize the process parameters using Taguchi method. Ranking is generated for the various combinations of input process parameters like upset time, upset pressure, heating time and heating pressure by using a multi-objective optimization technique like Grey Relational Analysis (GRA). The friction welding of similar Aluminium alloy Al6061 using centre lathe machine and find the optimal level of input parameters to improve the mechanical properties like axial shortening, hardness, impact strength are identified and presented in this work using DoE and GRA rankings.
A Review Paper on Friction Welding Process Parameters on Identical Materials Are Experimentally Evaluated and Using Optimization Technique
In fabrication industry, joining processes play a very important role. Among various joining processes, welding process has more strength as compared to other joining processes. Friction welding is a solid state welding, which is used to join similar or dissimilar materials by applying pressure and without the need of filler materials for heat production. Also, friction welded joints can produce welds that are superior in strength of the parent material. Friction welding enables similar or dissimilar materials to be joined together by sliding one material against the other under pressure. Friction welding process includes upset time, upset pressure, and heating time, heating pressure and rotating speed. In this experimental work, friction joints are carried out by centre lathe machine. In this experimental work, various types of metal joining were made using by using friction welding machine, welding of similar materials are done using the input process parameters like spindle speed, heating pressure, upset time, upset pressure, heating time, material to be welded, component size and configuration based on the literature review. Then the welded joints are tested to study and analyse the mechanical properties like axial shortening, hardness and impact strength to get the improved quality of welded joints and to optimize the process parameters using Taguchi method.
A Review Paper on Enhancement of Process Parameters for CNC Turning Of Stainless Steel Utilizing a Coated Tool
The global environmental awareness is increased, and environmental regulations become more stringent, the negative effects of cutting fluids on the environment are becoming more apparent. At present, in high-productivity manufacturing enterprises, the supply, maintenance and recycling costs of cutting fluids account for 13%-17% of the manufacturing cost of the workpiece. In Computer Numerical Control turning of hard materials such as steels, cast iron and super alloys, involves high cutting forces, leads to more power consumption and decreasing tool life which may increases the machining cost. To make machining process environment friendly with minimizing cost of machining, dry cutting is the best solution. This work aimed to optimize the most influencing process parameters to minimize cutting forces and surface roughness in CNC turning of hard bearing material AISI 52100 and to develop predictive model of surface roughness.
Enhanced Probabilistic K-Means Clustering for Student Course Classification
Student course classification plays a crucial role in understanding academic patterns and guiding educational decisions. This paper presents a probability-based K-Means clustering approach to classify students into distinct academic groups based on various attributes such as CGPA, age, and branch transition history. The proposed methodology integrates probabilistic selection to enhance the standard K-Means clustering, ensuring better adaptability in student classification. A dataset of students is analyzed using principal component analysis (PCA) for dimensionality reduction, followed by clustering to identify distinct academic patterns. The results visualize student distributions in a two-dimensional PCA space, with cluster centers representing core academic categories, including original branches and students who transitioned to a different course. The probability-based K-Means model improves clustering accuracy by dynamically adjusting centroid assignments based on probabilistic weight factors. The approach provides a structured framework for institutions to analyze student trends and improve academic advising. The experimental results demonstrate that this enhanced clustering technique offers improved classification accuracy compared to traditional clustering methods.
Assessing an Effective Approach for Adjusting Casting Process Parameters through Optimization
Foundries in India are facing lower productivity issues due to low quality of castings produced as well as wrong practices followed, therein. Minimizing rejection as well as production costs is the key area of concern in these foundries. Casting process parameters are important in the optimization of casting process. Design optimization using reliability has also emerged as a promising tool for optimization, using the probabilistic approach. This approach works on probability of failures through various parameters. Markov process is a predictive technique for generation of a stochastic model with sequence of possible events. This research study has focused on the development of a Markov chain model for investigating the casting failure. In this paper, several casting defects and parameters was carried out. Cold shut, Inclusion, Mould shift, Porosity, Shrinkage, Blow holes were the casting defects and Pouring temperature, Mould hardness, Moisture content, Improper handling, Permeability and Green compressive strength were the process parameters considered in the study. This study has proposed a hierarchical model that focuses on the casting failure in industries and accordingly the model was tested for various process parameters. The outcome of the study provides the priority ranking of the process parameters for various casting failure in real time through which the critical process parameters were identified in the order. The Pouring temperature came out as the most critical process parameter for casting failure. Also, the priority ranking of the process parameters for various casting failure in real time were identified and found to be identical.
A Review Paper on Assessing an Effective Approach for Adjusting Casting Process Parameters through Optimization
Foundries in India are facing lower productivity issues due to low quality of castings produced as well as wrong practices followed, therein. Minimizing rejection as well as production costs is the key area of concern in these foundries. Casting process parameters are important in the optimization of casting process. Design optimization using reliability has also emerged as a promising tool for optimization, using the probabilistic approach. This approach works on probability of failures through various parameters. In this paper we focus on the development of a Markov chain model for investigating the casting failure. In the study, several casting defects and parameters was carried out. This study we proposed a hierarchical model that focuses on the casting failure in industries and accordingly the model was tested for various process parameters.