Journal of Modern Processes in Manufacturing and Production
Volume:12 Issue: 3, Summer 2023

Blast air tuyeres are one of the critical components of a blast furnace that are exposed to severe conditions caused by thermal shocks, mechanical erosion, hot chemical corrosion, wettability caused by penetration of molten cast iron, and cracks caused by the thermal cycle. These factors decrease the lifetime of air tuyeres, causing unpredictable failure and costly production stoppages. The present study investigates the protection performance of three types of atmospheric plasma-sprayed ceramic coatings on air tuyeres against the harsh operating environment. As the substrate of air tuyeres, 99.95% pure copper is coated with Yttria Stabilized Zirconia YSZ8%, alumina-zirconia (AZ) and alumina-magnesia (AM). The performance of these three coatings was evaluated using mechanical wear and erosion tests, chemical hot corrosion tests, micro-hardness adhesion strength tests, and porosity measurements. Based on the results, AZ and AM coatings generally performed better than YSZ8% coating in all above-mentioned tests excluding the adhesion strength test. In the adhesion strength test, the AZ coating performance was found to be close to that of YSZ8% coating. Meanwhile, in the mechanical erosion and wear tests, the AM coating outperformed and underperformed the AZ coating, respectively. The porosity of AZ coating was also close to that of AM coating. Hence, it is expected that the blast air tuyere with AZ and AM coatings can offer better performance in blast furnace due to their superior metallurgical and mechanical properties. However, in practice, the AZ coating outperformed the AM coating in BF due to a three-fold increase in the lifecycle.

This research compares different approaches for achieving precise predictive maintenance (PdM) results from CNC machine tools. For smaller enterprises, it is crucial to be able to upgrade their existing industrial machines with industry 4.0 systems, as the global marketplace becomes more competitive. The evolution of the Internet of Things (IoT) and the creation of cyber-physical systems (CPS) in the industry has enabled big data generation. New maintenance methodologies have emerged where decisions are driven by mathematical models and data analysis. In this study, a low-cost strategy is used as a baseline to establish system accuracy. Results are then compared to a more comprehensive strategy outlining the potentials of these retrofit predictive maintenance (PdM) systems. Numerous data modeling techniques were employed to increase system accuracy while focusing on the remaining useful life (RUL) of the cutting tool. Through analysis of the selected strategies favorable correlation is evident between predicted results and physical tool wear, optimal accuracy of 95.68% is achieved by utilizing hybrid data modeling techniques. The study highlights the possibilities for enterprises looking to adopt PdM strategies and consequently capitalize on the potential of Industry 4.0.

In this research, the anomaly of flatfoot was initially introduced, followed by an examination of both traditional and new methods for designing and manufacturing orthotic insoles suitable for it. Regarding this matter, the design and construction of orthotic insoles using a stamp as a traditional method was introduced, and subsequently, the step-by-step elucidation of new methods, including foot scanning and the utilization of smart orthotic insoles in designing and manufacturing insoles suitable for flatfoot, was carried out. In both of these new methods, the design and construction of appropriate orthotic insoles involved the transfer of information obtained from the foot to relevant software and their subsequent processing. This research, while explaining the mentioned methods, described how to use engineering design software in designing and manufacturing orthotic insoles suitable for flatfoot. In conclusion, the results obtained from all three manufacturing methods were presented and compared to ascertain the advantages and disadvantages of each approach.

Thick-walled cylindrical vessels are used widely in petrochemical and power plants. New additive manufacturing technology has made it possible to make FGMs. This research studies the creep analysis in the cylindrical FGM pressure vessel by considering three models and yield criteria. Also, the governing equations were extracted by considering the FGM models, and for determining creep stresses, the partial differential equations, were solved. Norton's equation is used to determine creep strain rates. The advantage of the exponential model is that in the inner radius for all n radial and circumferential creep strains rates have a constant value that is maintained by increasing the internal pressure up to 400 MPa. The graphs are smooth, and their values tend to zero in the outer radius. The changes of creep strain rate in terms of n in different internal pressures for the exponential model in the inner radius of the vessel show that increasing n from -4 to 0, these parameters have a reduction to the form of an exponential function, and the slope of the graph has the highest value at 360 MPa.

In this study, the researchers investigated the impact of various parameters, including layer raster angle, infill extrusion width, and layer height, on mechanical properties such as tensile strength, elongation, and Young's modulus of polylactic acid printed samples. To reduce experimental costs, the Box-Behnken method was employed along with response surface methodology using Minitab software to establish the relationship between input and output variables. The results of the tension test indicated that the raster angle had a significant impact on all three properties. Furthermore, the regression equations showed that changes in infill extrusion width and layer height had a strong effect on tensile strength but had a less significant impact on elongation and Young's modulus. The optimal output parameters were determined to be 38.67 MPa tensile strength, 3.42% elongation, and 1117.47 MPa Young's modulus using input parameters of 10 degree raster angle, 170% infill extrusion width, and 0.2 mm layer height. The study validated the results obtained through experimental testing and concluded that the response surface methodology could predict part properties with high accuracy (less than 6% error) based on input parameters.

Friction stir processing (FSP) is an effective technique for surface modification and grain refinement. This method can be used to incorporate hard ceramic reinforcement into modified aluminum surfaces, allowing for the fabrication of composites with enhanced properties. In this study, FSP was utilized to fabricate surface composites of aluminum alloy 6061-T6 reinforced with zirconium-silicate particles. The effects of tool rotational and traverse speeds, as well as the number of passes, on the microstructural and mechanical properties of the composite specimens were investigated. The corresponding strength, grain size, and microhardness of the specimens were evaluated and compared with unprocessed and non-reinforced aluminum alloy. The scanning electron micrographs of the specimen cross-section showed an excellent dispersion of zirconium-silicate particles in the aluminum matrix, indicating the homogeneity of the aluminum composite and the success of the applied FSP. The results showed that increasing the number of passes from one to four caused microstructure refinement at the stir zone, resulting in enhanced tensile strength and hardness of the produced composite. An optimum value of 1000 rpm and 20 mm/min for rotational and traverse speeds was obtained. Consequently, a composite with improved mechanical properties was achieved due to the formation and distribution of reinforcing zirconium-silicate particles.