Journal of Modern Processes in Manufacturing and Production
Volume:11 Issue: 3, Summer 2022

In recent years, processes known as severe plastic deformation (SPD) have been devised to create fine-grained materials. Among these processes, equal channel angular pressing (ECAP) has been more favored than other methods due to its high efficiency, simplicity, and industrial production potential. This study aimed to investigate the sample temperature gradient during the ECAP process. For this purpose, a Taguchi experiment with influencing factors on AA2017 alloy was designed and a relationship was obtained to predict sample surface temperature. Experiments were carried out using grease, graphite powder, and MoS2 lubricants, along with routes A, BC, BA, and C. The surface temperature of the sample was measured using a laser thermometer. A finite element model was compared with the experimental conditions, and the simulation and experimental results of surface temperature were verified with an error of about 1.9%. In experiments, it was found that speed and lubricant had a significant effect on sample temperature during the process. The simulation results showed that decreasing the die angle resulted in a significant increase in temperature. Following the validation of the FEM model, the temperature gradient and distribution in the middle of the sample, wherein practical experiments could not be measured, were also investigated.

Heusler alloys are intermetallic that offer a unique and broad array of properties. These properties are both scientifically intriguing and valuable for a variety of beneficial practical applications. One of these applications is magnetic cooling, taking advantage of the giant magnetocaloric effect (GMCE) in some Heusler alloys. Since the late 1990s, numerous scientific papers were published, attempting to harness Heusler alloys for green refrigeration. Manufacturing the alloys by additive manufacturing further offers control and enables tuning of their properties by controlling their microstructure. Although the scientific literature contains extensive information on these alloys’ chemistry and performance, it is the massive volume of scientific papers that makes it difficult, if not impossible, to keep up to date with relevant discoveries. To enable predicting the composition of excellent performing giant magnetocaloric Heusler alloys, manufactured by laser powder bed fusion (LPBF), we employed artificial intelligence, specifically unsupervised learning in the current work. We trained an unsupervised learning model using word embedding and the Word2vec algorithm on different data sets in the literature to extract hidden knowledge, relations, and interactions based on words that appear in similar contexts in the text while often having similar meanings. Properties inherent to giant magnetocaloric materials were addressed in the model. The outcome was the prediction of Heusler alloys, manufactured by LPBF, with an excellent giant magnetocaloric effect.

Plasma assisted chemical vapor deposition (PACVD) technique was used to make a diamond-like carbon (DLC) coating on the Aluminum 6061- T6 substrate. The deposition was carried out using CH4 as the process gas, at different temperatures, 250°C and 300°C with constant power and flow rate. Characterization technique Raman spectroscopy was used to characterize these samples. Raman analysis of DLC coatings at different temperatures is carried out in detail for two different excitation wavelengths i.e. 514 and 785 nm and, results are presented in the paper. Blue shifts were observed in both D and G peaks of the Raman spectrum with an increase in deposition temperature, which indicates the formation of compressive strain in high-temperature deposited DLC coatings. Dispersion in both D and G peaks is observed for different excitation wavelengths suggesting that the coating is hydrogenated DLC. The degree of hydrogenation of the DLC coating appears to decrease for the deposition temperature. Nano-indentation study shows a marginal increase in hardness with an increase in deposition temperature.

The use of electro-hydraulic valves, particularly the proportional valve, has been important progress in the development of modern automated manufacturing equipment such as cutting or forming machine tools. Using these valves, electrical control signals can be converted into fluid energy in hydraulic systems. The main purpose of this study was to implement a control system for a 4-3 proportional hydraulic valve to control the position and speed of a double-acting cylinder. In this paper firstly the equipment is introduced and then the results of the implementation of the closed-loop control of this hydraulic valve controlled by PLC have been presented. The purpose of the control system is to equalize the extending and retraction times of the double-acting hydraulic cylinder. The practical results showed the electro-hydraulic system has performed well and the system has achieved the control goal to an acceptable level. In the simulation section, the performance of an open-loop control electro-hydraulic system for tracking a harmonic voltage input signal has been investigated. The electro-hydraulic circuit was designed in such a way that the stroke time of the hydraulic cylinder is independent of the external load. The results showed that applying input harmonic voltage between -10 and 10 volts causes the cylinder rod to move back and forth under external load.

Optimizing the path of the movement of moving objects such as various robots in the industry can have a significant effect on reducing manufacturing and production time and costs. In this research, using a messy genetic algorithm, a new method is presented to optimize the movement path of a mobile object such as a robot in the presence of multiple obstacles. The movement path can be considered two-dimensional or multi-dimensional, and the obstacles in the path are assumed to be circles and spheres. The method used is that first, several chromosomes are created in the zero generation and their fitness is calculated. Then, using competitive selection, the parents of the new generation are created and from there the chromosomes of the next generation are made, and their fitness is calculated. This process continues until the considered condition, i.e. the ratio of the average fitness divided by maximum fitness in each generation is satisfied. Since in the messy genetic algorithm, the length of the chromosome can be variable, the proposed algorithm can examine all types of paths with a variable number of points depending on the existing obstacles and with high efficiency, find the shortest path with an approximate difference of 3.4 percentage compared to the ideal path. This method can optimize even paths with more than three dimensions.

In this study, the effect of ferrite grain size on mechanical properties and failure micro-mechanisms of materials was investigated by using acoustic emission (AE) non-destructive testing (NDT). AE signals were obtained from tensile tests of fully annealed ferrite samples and the effective AE parameters for each sample were analyzed from the AE waveforms. Due to annealing, the ferrite grain size was different in each sample, which affected the AE signals, and to analyze the AE signals, the Sentry Function (SF) and Fast Fourier Transform (FFT) were used and the results show that performing a full annealing operation to change the grain size at different temperatures almost did not significantly affect the frequency parameter, which has a range of about 175 kHz. In addition, the amplitude was about 30-40 dB, which indicates the deformation of the ferrite, and also the amount of AE energy released during the tensile test was lower than the strain energy.