Thermogravimetric analysis (TGA) was utilised to compare the thermal stability of pure phase change material (D-mannitol) to that of nano-enhanced PCM (NEPCM) (i.e., PCM containing 0.5% and 1% multiwalled carbon nanotubes (MWCNT)). Using model-free kinetics techniques, the kinetics of pure PCM and NEPCM degradation were analysed. Three different kinetic models such as Kissinger-Akahira-Sunose (KAS), the Flynn-Wall-Ozawa (FWO), and the Starink were applied to assess the activation energies of the pure and nano-enhanced PCM samples. Activation energies for pure PCM using the Ozawa, KAS, and Starink methods ranged from 71.10–77.77, 79.36–66.87, and 66.53–72.52 kJ/mol, respectively. NEPCM’s (1% MWCNT) activation energies ranged from 76.59–59.11, 71.52–52.28, and 72.15–53.07 kJ/mol. Models of machine learning were utilised to predict the degradation of NEPCM samples; these included linear regression, support vector regression, random forests, gaussian process regression, and artificial neural network models. The mass loss of the sample functioned as the output parameter, while the addition of nanoparticles weight fraction, the heating rate, and the temperature functioned as the input parameters. Experiment-based TGA data can be accurately predicted using the created machine learning models.

Wire Arc Additive Manufacturing (WAAM) is a low-cost method of fabricating large components from advanced materials such as nickel-based superalloys. Nickel-based superalloys have varied industrial applications and suit the WAAM method due to their excellent weldability when used in conjunction with metal inert gas welding equipment used in the current study. All WAAM specimens were subjected to a standard dry sliding wear test to examine wear behavior. During the wear study, load, sliding velocity, and sliding distance were all considered for both wrought and WAAM alloy. The lowest wear was observed at a lower load and higher sliding velocity, whereas the highest wear was observed at a higher load and lower sliding velocity. Wear mechanisms and wear debris corresponding to lowest and highest wear conditions were also being investigated. The transition from lowest to highest wear rate in both alloys was attributed to the transition from abrasive to adhesive and delamination wear mechanisms. Microstructure analysis revealed that the nickel-based WAAMed alloy had an equiaxed dendritic structure, whereas the nickel-based wrought alloy had a cellulose structure. Both specimens had a stable austenite structure in the Ni-Fe-Cr phase, as determined by X-ray diffraction analysis. The X-ray diffraction line profile analysis technique by the Williamson-Hall relationship revealed that WAAM alloys have higher micro-strain, higher dislocation density, and smaller crystallite size when compared to wrought alloys. The experimental results showed a 23% increase in hardness and a considerable improvement in wear resistance in the WAAMed alloy compared to the wrought alloy. GRAPHICAL ABSTRACT

The Internet of Things (IoT) is a new way of communicating that is changing the way things are monitored and controlled from a distance. Gradually, companies want to digitalize their production processes and implement control and monitoring systems on the shop floor. On the basis of the Industry 4.0 concept, internet features and database services have been incorporated into processes in order to reinvent manufacturing. This study proposes a proof-of-concept system for the management of additive manufacturing (AM) machines, where an internet integration of beacon technology in the manufacturing environment enables the rapid and intuitive interchange of production data retrieved from machines with mobile devices in various applications. Even though AM technologies can be used to customize the final product, they cannot be used to make a lot of 3D-printed jobs at once for commercial usage. Therefore, this research-based study aims to understand IoT technologies to improve the understanding and reliability of AM processes and 3D print smart materials in large quantities for manufacturers around the world. This study demonstrates the significance of the successful use of internet-based technologies in AM by examining its practical consequences in various fields. This paper gives an overview of IoT-based remote monitoring and control systems that could solve problems in AM, particularly in digital twin, human augmentation (HA), 3D bioprinters, 3D scanners, input parameters optimization, and electronics fields. IoT in AM makes production processes more efficient, reduces waste, and meets customer needs.

Dissimilar friction stir spot welds (FSSW) between the magnesium and aluminum alloys are joined, using a novel approach called refill friction stir spot welding. The present work aims to evaluate the macrostructural and mechanical properties of refill friction stir spot welded AZ31B and AA 6061-T6 alloys in two combinations, i.e., identical Mg-to-Mg and dissimilar Mg-to-Al joints, and the results are compared with the results obtained in conventional friction stir spot welding. The hardness profiles of the similar welds had the appearance of a W-shape, and the Thermo mechanically affected zone and heat-affected zone of both methods had lower hardness values than the rest of the weld. Along with the interface between the aluminum and magnesium sheets, a thin intermetallic compound layer of Al₁₂Mg₁₇ has been identified, which has led to an increase in hardness. The static shear strength of both similar and dissimilar refill spot friction welds was much greater than that of traditional spot friction welds. In both similar and dissimilar spot friction welds, two distinct failure scenarios are discovered.