Gopalakrishnan T

Predictive Maintenance (PdM) has emerged as a critical enabler of Industry 4.0, overcoming the limitations of traditional corrective and time-based preventive maintenance strategies. Through the integration of IoT-enabled sensors, advanced condition monitoring, edge computing, and artificial intelligence, PdM supports real-time health assessment, early fault detection, and data-driven maintenance decisions. This chapter outlines core PdM architectures, the role of machine learning in fault diagnosis and remaining useful life estimation, and key system integration challenges influencing intelligent asset management in modern industrial environments.

The increasing demand for low-cost and energy-efficient desalination systems has intensified interest in solar distillation technologies. The optimisation of a single-slope solar still with respect to ambient temperature, wall lining thickness, solar radiation, and wind velocity was carried out in this study using Response Surface Methodology (RSM) based on the Central Composite Design (CCD). A total of thirty experiments were carried out to assess the influence and interactions of the process parameters on freshwater productivity. The highest temperature of the basin, glass, water and vapour was 68.5°C, 63.25°C, 68.0°C and 66.5°C respectively. The productivity of the freshwater in the lined basin was also improved: from 1260 mL/day for the unlined basin to 2230 mL/day and 2330 mL/day for the 4 mm and 8 mm wall lining thicknesses, respectively, with a productivity increase of 77% and 85% respectively. The developed quadratic regression model exhibited excellent predictive accuracy, with an R2 of 0.9926. The optimum conditions resulted in a production of 2330 mL/day under a 1.96% prediction error. The distilled water met the WHO drinking water standards, which is an indicator of the ability of the proposed system to produce freshwater in a sustainable manner.

Induction motors (IMs) sustain a vast share of industrial activity but are prone to bearing wear, rotor-bar breakage, eccentricity, and insulation defects that emerge under non-stationary, noisy conditions. While Motor Current Signature Analysis (MCSA) remains attractive for its non-intrusive sensing, its discriminative power collapses at low signal-to-noise ratios (SNR) and when labelled fault exemplars are scarce. We present a unified Self-Supervised + Federated Learning (SSL–FL) framework that (i) learns transferable, noise-tolerant embeddings from large unlabelled corpora of stator current and vibration signals, and (ii) enables privacy-preserving, cross-site training without sharing raw data. Using chronological splits, SNR stress tests (0–15 dB), fault-severity breakdowns (incipient/developing/severe), non-IID federated client simulations, and leave-one-site-out transfer across CWRU, Paderborn, IMS, and an industrial pump–IM testbed, the approach consistently outperforms strong deep baselines (CNN/LSTM/Transformer), achieving 94.2% overall accuracy (92.4% incipient), 0.92 F1, and 0.90 MCC. It delivers 11–17 percentage-point gains in low-SNR regimes and 83.5% cross-domain accuracy, while attaining ~ 91% of the centralized upper bound with ~ 58% aggregation bandwidth under secure aggregation and (ε = 2.0, δ = 10⁻ 5 ) differential privacy. Performance remains stable under Dirichlet non-IID distributions (α = 0.1), confirming practical robustness to heterogeneous multi-site data. By coupling unlabelled representation learning with confidentiality-aware collaboration and severity-aware evaluation, the method advances a practical path to scalable, noise-robust, and compliant condition monitoring for Industry 4.0 assets.

This investigation examines the performance and emission characteristics of the KIRLOSKAR TV-I engine utilizing pumpkin seed oil (Cucurbita pepo L) methyl ester blended with 5% diethyl ether (DEE). Various blends containing 10%, 20%, 30%, 40%, and 50% pumpkin seed oil biodiesel were analysed for their chemical and physical properties, including viscosity, density, flash point, cetane number, and oxidation stability, in compliance with ASTM standards. Gas Chromatography-Mass Spectrometry (GC-MS) was employed to determine the fatty acid composition of the biodiesel. Experimental results revealed that the 20% biodiesel blend exhibited superior performance, combustion, and emission characteristics, making it a viable substitute for conventional diesel with minimal engine modifications. Emission analysis of the 20% blend showed a 0.65% reduction in carbon monoxide (CO), a 10.3% decrease in carbon dioxide (CO2), and a 21.1% reduction in nitrogen oxide (NOx) compared to diesel. Notably, blends without additives also demonstrated significant reductions in NOx (25.83%), CO (14.3%), and CO2 (13.8%) emissions, highlighting the environmental benefits of these biodiesel formulations.

Aluminum–SiC (Al–SiC) composites have gained significant prominence in the aerospace and automotive industries due to their exceptional combination of high strength-to-weight ratio, superior thermal conductivity, and excellent wear resistance characteristics. Despite their widespread industrial applications, the behavior of these composites under cyclical thermal conditions remains inadequately characterized and understood. This comprehensive study meticulously examines the effects of cyclic thermal shock (consisting of 20 complete cycles from 300 to 25 °C) on the mechanical properties and microstructural integrity of Al–SiC composites containing 15 vol. % SiC reinforcement. Extensive mechanical testing revealed notable property degradation patterns: ultimate tensile strength decreased by 7.8% (from 320 to 295 MPa), yield strength diminished by 8.0% (from 250 to 230 MPa), and Vickers hardness reduced by 12.5% (from 145 HV to 130 HV). More significantly, energy absorption properties exhibited pronounced deterioration, with impact toughness dropping by 33.3% and fracture toughness declining by 28.0%, indicating a substantial compromise in damage tolerance capabilities. Detailed SEM microstructural analysis identified three primary degradation mechanisms: matrix microcracking, SiC particle fragmentation, and interfacial debonding between the aluminum matrix and SiC reinforcement. These findings emphasize the critical need for enhanced interfacial bonding strength and innovative reinforcement strategies to improve thermal shock resistance in Al–SiC composites, particularly for applications involving thermal cycling conditions.

In this study, squeeze-cast Zn?Al?Cu?Mg alloys with varying Ca additions (0, 0.5, 1.0, and 1.5 wt.%) were investigated to evaluate the combined effects of microstructural evolution on mechanical and corrosion performance. Microstructural analysis showed a transition from coarse Zn-rich dendrites in the base alloy to a refined and uniform morphology with Ca additions up to 1.0 wt.%, followed by coarsening and increased porosity at 1.5 wt.% Ca due to excessive intermetallic formation. Mechanical testing indicated that the alloy with 1.0 wt.% Ca had the highest hardness (141 HV0.1) and tensile strength (359 MPa), attributed to grain refinement and dispersion strengthening, though with reduced ductility due to intermetallic brittleness. Electrochemical corrosion tests in 3.5 wt.% NaCl solution showed that the corrosion rate decreased from the base alloy to 1.0 wt.% Ca, confirming enhanced corrosion resistance due to microstructural refinement and protective film formation. However, excessive Ca addition (1.5 wt.%) increased the corrosion rate to 0.8109 mpy due to coarse intermetallics and porosity, which promoted localized attack. The results highlight that optimal Ca addition (1.0 wt.%) achieves a balance between strength, hardness, and corrosion resistance, making Ca-modified Zn?Al?Cu?Mg alloys promising candidates for structural and functional applications.

The dual compensation chamber loop heat pipe (DCCLHP) technology shows great promise for efficient thermal management in a variety of applications. This study focuses on refining the startup performance of the DCCLHP, particularly for low heat load conditions in terrestrial settings, by utilizing dual bayonet tubes. Empirical investigations examined the DCCLHP’s operational characteristics and improved thermal transfer capabilities across different orientations of the evaporator and compensation chamber (CC), including vertical, 45‐degree tilt angle, and horizontal configurations. Key results demonstrate the DCCLHP’s ability to manage low heat loads across diverse orientations, achieving over 400 W of heat transfer across a distance of 2.0 m while maintaining stable operation. Notably, the DCCLHP operation did not exhibit any significant instability issues. This work enhances the startup performance of the DCCLHP in various orientations and provides valuable insights into the confined natural circulation phenomenon, crucial for improving the overall thermal management capabilities of the system. In summary, the study highlights advancements in DCCLHP design and its potential to address thermal management challenges in diverse applications, particularly in the aerospace industry, through improved startup performance and enhanced heat transfer capabilities.

The name shape memory alloy (SMA) reveals its behavior of being an accurate heat-sensitive material in changing its shape based on the temperature. This ample review concentrates on the current scenario of including SMA in polymer matrix composites to achieve desired objectives. Polymer-based shape memory alloys are termed shape memory polymers (SMP), and they consist of deformable materials that are able to switch between their original shapes and temporary shapes, which can be generously designed. SMPs could be classified as smart materials by considering their low density, good biocompatibility, excessive deformation etc. On the other hand, many engineering applications of SMP uses have limitations and disadvantages. In this regard, the importance of SMPs has been analyzed based on the following aspects: synthesis method, fiber reinforcement, parameters that affected the polymer-based SMA, and implementation of multifunctionality materials. Fiber-reinforced polymer composites have more responsibilities for expanding interest in current innovative research and expected mechanical applications because of their significant space compared with conservative materials. A polymer composite presents effectively adaptable product properties, expected high strength-to-weight ratio, high flexibility in the manufacturing process, high corrosion resistance, and easy fabrication at a lower cost.

The composite phenomenon helps us to achieve desired properties in the material. Inclusion of nano-sized particles is influence significantly in building the desired properties of composite. Such inclusion is in practice in MMC, PMC as well as CMC. This research focuses the stiffness building phenomenon in the Aramid/E-Glass polymer composite. The inclusion of nano sized fly ash particles is preferred to built up stiffness property in the Aramid/E-Glass polymer matrix composite. The inclusion of nano particles of fly ash varied from 0%, 1%, 2%, 3%, 4% and 5%. The nanocomposites were characterized by Impact, flexural and tensile test as per applicable standard. The percentage of nano particles of fly ash inclusion is directly proportionate to the building the stiffness of nano-composite.

In aircraft design functional components are of top priority. This numerical investigation is used for evaluating the fulfilment of strength requirement of the landing gear toggle assembly. The landing gear is the structure which supports the aircraft and helps in taxiing, take-off and landing of the aircraft. Hence it is suffered by more fatigue load than the other applications. The replacement of steel to aluminium was investigated. Every part is individually analysed and its part with sub-assemblies also investigated.

The technological advantages lead to design the components and systems of great extent. The functional components and their dimensions are to be designed well for ensuring safe and reliable operations. The lift rod of helicopter is considered here for optimization. The failure mode analysis results show that the lift rod fails often and found to have less life period because of some complex force system that is encountered while landing, take-off and continuation of flight. Initially the existing design parameters and cross sections were considered as it is for observation. Based on the observation, the cross section was optimized to some extent. Then the design parameters are increased to 3 levels. The lift rod is analysed again with modified parameters. Finally, both the dimensions and shape are optimized to achieve a good design with desirable characteristics.

Tribological behaviour of contacting surfaces rigid sphere is using flat plate the with influence of normal and tangential loading (shear traction) is analysed using FEA model and surfaces being coated on flat plate by Titanium Alloy, Aluminium Alloy Molybdenum Di-sulphide. The finite element model facilitates to Evaluating the surface variables like contact stress distribution with the surface level and surface, contact pressure, shear stress and displacement. The finite element solution is validated through the hertz solution and on the successful verification.

Powerful management concepts step-up the quality of the product, time saving in producing the product thereby increase the production rate, improves tools and techniques, work culture, work place and employee motivation and morale. In this paper discussed about the case study of optimizing the tool design, tool parameters to cast off expansion plan according ECRS technique. The proposed designs and optimal tool parameters yielded best results and meet the customer demand without expansion plan. Hence the work yielded huge savings of money (direct and indirect cost), time and improved the motivation and more of employees significantly.

Abrasive water jet cutting is one of the most recently developed non-traditional manufacturing technologies. In this machining, the abrasives are mixed with suspended liquid to form semi liquid mixture. The general nature of flow through the machining, results in fleeting wear of the nozzle which decrease the cutting performance. The inlet pressure of the abrasive water suspension has main effect on the major destruction characteristics of the inner surface of the nozzle. The aim of the project is to analyze the effect of inlet pressure on wall shear and exit kinetic energy. The analysis could be carried out by changing the taper angle of the nozzle, so as to obtain optimized process parameters for minimum nozzle wear. The two phase flow analysis would be carried by using computational fluid dynamics tool CFX. It is also used to analyze the flow characteristics of abrasive water jet machining on the inner surface of the nozzle. The availability of optimized process parameters of abrasive water jet machining (AWJM) is limited to water and experimental test can be cost prohibitive. In this case, Computational fluid dynamics analysis would provide better results.

The Automobile Industry has shown increase interest for replacement of steel leaf spring with that of composite leaf spring. Substituting composite materials for conventional metallic materials has many advantages because of higher specific stiffness, strength and fatigue resistance etc. This work deals with the replacement of conventional steel leaf spring with a hybrid Composite leaf spring using E -Glass/Carbon/Graphite/Epoxy. The hybrid composite is obtained by introducing more than one fiber in the reinforcement phase. The hybrid composite is fabricated by the vacuum bag technique. The result shows that introduction of carbon and graphite fiber in the reinforcement phase increases the stiffness of the composite.

In composites de-lamination is a serious issue. Usually reinforcement in the thickness direction (z axis reinforcement) is employed to solve this issue. In this article an experimental analysis of sewing type z-axis reinforcement approach is discussed. This type is unique than 3D composite fabrication and reinforcement after curing techniques. This type of reinforcement increased interlaminar toughness of laminated composites considerably. The proposed technique is carefully considered to overcome the limitation of the conventional technique. It is improved by sewing type zaxis reinforcement into the host laminate before it has been cured and is proposed to overcome the previous limitations. Here two types of composites were fabricated and tested with Double-Cantilever Beam (DCB) test and shock loading test for validating the reinforcement performance. The different measures like load absorption and displacement in gradual loading, fracture toughness, energy absorption and status of the broken specimen were observed to measure the effect of reinforcement. The results demonstrate that the proposed method of z-axis reinforcement was extremely effective in restraining the de-lamination related to damage propagation.