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Finite element (FE) modeling of tailor welded blanks (TWBs) is a complex phenomenon compared to FE modeling of monolithic sheets due to the change of mechanical properties caused by the welding process. This complexity involves modeling different zones generated due to the heat effect. Research on the formability of steel TWBs with dissimilar thicknesses and strength produced by manual tungsten inert gas (TIG) welding technique and formed by single point incremental forming (SPIF) involving base sheets, weld nugget (WN), and heat affected zone (HAZ) is presented, numerically. The materials selected for the study included deep drawing quality (DDQ) steel (DC06) and stainless steel (SS) (AISI 201). Variable wall angle truncated pyramid was used as test geometry, and FE software Abaqus (dynamic explicit solver) was used for the analysis. Thickness profiles and state of stress and strain in both the cases of thickness and strength differential were analyzed. A decrease in thickness was observed at the corners in both cases. However, this decrease was more prominent in the case of strength differential. The symmetry of the pattern on both sides with minimum and maximum values of stress towards the thinner side was observed in the case of thickness differential. Variation in stress was more prominent towards the side of high-strength material along maximum value in the case of strength differential. Equivalent plastic strain observed was more linear and higher towards the sides of thicker sheet and material having less strength in the case of thickness differential and strength differential, respectively. Research investigations may be applied in a similar fashion for the precise study of formability characteristics of various kinds of TWBs being used in multiple industries including automotive, vessel, and medical. [ABSTRACT FROM AUTHOR]

CNC press-brake forming is widely used to transform sheet-metal blanks into complex three-dimensional shapes in a low quantity high variety manufacturing environment. Sheet-metal bend sequence planning is a complex combinatorial problem. Process planning and tolerance reasoning for sheet-metal forming are critical to reduce manufacturing time and to address accuracy aspects. Handling time and accuracy of sheet-metal-formed components strongly depend upon the bending sequence. Process and material variations shrink the tolerance zones and therefore their effect must be incorporated in the overall sheet-metal process planning activity. Monte Carlo simulations are used in this article to evaluate the effect of process and material variations on bending accuracy. Branch-and-bound, traveling salesman problem (TSP)-based techniques are used to identify potential feasible bending sequences. Results from the Monte Carlo simulations are used as input for sheet-metal bend sequence planning. In the case study, proposed methodology is used for available industrial sheet-metal components. Resulted tolerance zones attenuated after the probabilistic deflection analysis. Expected error input from probabilistic deflection analysis produced bending sequences which resulted in formed components within designed accuracy limits. Possibility of forming out of tolerance components is also attenuated. [ABSTRACT FROM AUTHOR]

Sustainable machining necessitates energy-efficient processes, longer tool lifespan, and greater surface integrity of the products in modern manufacturing. However, when considering Ti6Al4V alloy, these objectives turn out to be difficult to achieve as titanium alloys pose serious machinability challenges, especially at elevated temperatures. In this research, we investigate the optimal machining parameters required for turning of Ti6Al4V alloy. Turning experiments were performed to optimize four response parameters, i.e., specific cutting energy (SCE), wear rate (R), surface roughness (Ra), and material removal rate (MRR) with uncoated H13 carbide inserts in the dry cutting environment. Grey relational analysis (GRA) combined with the analytic hierarchy process (AHP) was performed to develop a multi-objective function. Response surface optimization was used to optimize the developed multi-objective function and determine the optimal cutting condition. As per the ANOVA, the interaction of feed rate and cutting speed (f × V) was found to be the most significant factor influencing the grey relational grade (GRG) of the multi-objective function. The optimized machining conditions increased the MRR and tool life by 34% and 7%, whereas, reducing the specific cutting energy and surface roughness by 6% and 2% respectively. Using Taguchi-based GRA by analytic hierarchy process (AHP) weights method, the benefits of high-speed machining Ti6Al4V through multi-response optimization were achieved. [ABSTRACT FROM AUTHOR]

Specific cutting energy consumption in high-speed orthogonal machining of Al 6061-T6 alloy has been analyzed in this work. The evaluated values of specific cutting energy are presented as an energy map developed over a cutting speed-undeformed chip thickness grid. Different regions characterized by energy consumption have been defined on the developed map. Very low values of specific cutting energy (up to 0.32 J/mm3) were observed for Al 6061-T6 alloy while machining over the cutting speed of 1500 m/min. Such low energy values have not been reported earlier in literature and they demonstrate another benefit of high-speed machining along with better surface finish, low cutting forces, and high production rate. The developed energy map revealed the presence of a very high energy zone in the midst of a comparatively low energy consumption region. A detailed analysis was performed to investigate the formation of this high energy zone or “avoidance zone.” The analysis of results revealed excessive built-up edge formation within this zone. [ABSTRACT FROM AUTHOR]

The grouping of parts and machines into manufacturing cells with the objective to improve grouping efficacy is the prime focus of cell formation problem. This paper presents the hybridization of simulated annealing (SA) with genetic algorithm (GA), where exploration power of GA, to broaden the search space, is combined with the intensification power of SA. A certain percentage of best solution in each generation of GA is sent, for further intensification and trajectory search, to SA. In intensification phase (with SA), Boltzmann probability distribution functions are used to allow a downhill move, with variable temperature. Starting temperature is chosen to be a small value with rapid cooling rate to keep search in a narrow region. If same solution is repeated for a certain number of generations, then shake-off is given to escape local maxima. During this shake-off, the SA parameters are relaxed to broaden the search for best neighbourhood solution. The effectiveness of proposed hybrid heuristic algorithm is evaluated through 35 benchmark problems from the literature. The GA with intensification through SA along with shake-off performed well in terms of solution quality, i.e. produced 24 best results with overall mean of 66.20. The overall comparative study shows that the proposed approach not only achieves the best solutions consistently, with minimum computational time, but also improves the results of two problems (problems 29 and 33), reporting it for the first time. [ABSTRACT FROM AUTHOR]