Optimization of advanced manufacturing processes using socio inspired cohort intelligence algorithm

The demand of Advanced Machining Processes (AMP) is continuously increasing owing to the technological advancement. The problems based on AMP are complex in nature as it consisted of parameters which are interdependent. These problems also consisted of linear and nonlinear constraints. This makes the problem complex which may not be solved using traditional optimization techniques. The optimization of process parameters is indispensable to use AMP's at its aptness and to make it economical to use. This paper states the optimization of process parameters of Ultrasonic machining (USM) and Abrasive water jet machining (AWJM) processes to maximize the Material Removal Rate (MRR) using a socio inspired Cohort Intelligent (CI) algorithm. The constraints involved with these problems are handled using static penalty function approach. The solutions are compared with other contemporary techniques such as Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Modified Harmony Search (HS_M) and Genetic Algorithm (GA).

Optimization of Process Parameters for Enhanced Degradation of Methylene Blue by Trough Ultrasonic

Due to the complex quality and the large discharge of printing and dyeing wastewater, it will pollute the environment and affect human health. Therefore, how to use efficient and inexpensive treatment methods to treat printing and dyeing wastewater has become an urgent problem to be solved. At present, most printing and dyeing wastewater contains methylene blue pollutants. Based on the previous research in this article, the process conditions for the enhanced degradation of methylene blue by trough ultrasound are optimized. Orthogonal test results show that the optimal process parameter for the degradation of methylene blue by trough ultrasonic is pH 12.70, and the initial With a concentration of 10.00mg/L and an ultrasonic power of 200W, under the above optimal process conditions, the degradation rate of methylene blue is 77.95%; Ultrasound improves the rapid degradation of methylene blue through mechanisms such as cavitation, thermal and mechanical effects. This process can be used for the industrial degradation of methylene blue. The application provides a research basis.

OPTIMIZATION OF PROCESS PARAMETERS FOR SURFACE ROUGHNESS OF GFRP WITH AWJ MACHINING USING TAGUCHI AND GRA METHODS

For machining of composites like glass fibre reinforced polymers, abrasive water jet machining is generally used. In the present paper, an experimental investigation is described which is focused on studying the influence of AWJM process parameters on surface roughness of machined samples. Four process parameters namely water pressure, traverse speed, stand-off distance and abrasive mass flow rate are considered in the present study. Taguchi technique is used for the design of experiments and analysis of variance (ANOVA) is performed to determine the significance of parameters. It is found that water pressure and traverse speed are the major significant parameters for influencing surface roughness. Surface roughness decreases with increase in water pressure and decrease in traverse speed. For surface roughness minimization Grey Relational Analysis (GRA) technique is used for multi optimization of process parameters and experimental results are analyzed using Grey Relational Grades (GRG).

Mechanical Properties of Nylon Parts Produced by Fused Deposition Modeling

Fused deposition modeling (FDM) is a widely used additive manufacturing technique for producing polymeric parts. While most commonly used FDM filaments are PLA and ABS, nylon is a widely used thermoplastic polymer in industry. This study investigated the mechanical properties of FDM-produced specimens made of nylon and quantified the effect of process parameters such as raster orientation and nozzle temperature on the mechanical properties. As the nozzle temperature increases, specimens become stronger with higher elongations at the break. This is mainly due to the improved fusion between the layers, provided by an expansion of the heat-affected zone. On the other hand, specimens with diagonal raster orientation exhibit higher elongations than those with perpendicular and parallel raster. The findings also emphasize the synergistic effects between nozzle temperature and printing orientation, showing that optimization should consider the two parameters together. Overall, FDM can produce strong nylon parts with adequate ductility suitable for load-bearing applications. However, achieving such results requires a detailed optimization of process parameters.

Micro Textured Cutting Inserts with Solid Lubrication as Alternative Coolant to Mineral Oil-Based Cutting Fluid in Turning Operation

Turning process is a primary process in engineering industries and optimization of process parameters enhance the machining performance. Inconel 718 is a nickel-based superalloy, widely found applications in the manufacturing of blades, sheets and discs in aircraft engines and rocket engines. It provides toughness at low temperature, with stand high mechanical stresses at elevated temperature and creep resistance. In this work, turning process is carried out on Inconel 718 with micro whole textured cutting inserts filled with solid lubricants. Three different solid lubricants are used namely molybdenum-di-sulfide (MoS2), tungsten-di-sulfide (WS2) and calcium-di-fluoride (CaF2). Experiments are performed as per L9 orthogonal array. Statistical approaches such as orthogonal array, Signal-to-Noise (S/N) ratio and Analysis of Variance (ANOVA) are used to find the importance and effects of machining parameters. In this study, input parameters included are feed, cutting speed and depth of cut and output parameter includes surface roughness. Optimization of process parameters is carried out and the significance is estimated. The result suggested that WS2 followed by MoS2 and CaF2 given good surface finish value. Also, solid lubricant in machining enhances the sustainability in manufacturing.

Multi Response Optimization of Process Parameters using Taguchi based Grey Relational Method in FSW of AZ91B Magnesium Alloy

In this paper, the Taguchi method and grey relational analysis have been used to evaluate the weldability of AZ91B Magnesium alloy by friction stir welding process. Experiments were conducted using the L9 Taguchi design considering an orthogonal array consist of 3 factors and 3 levels. The rotational speed, transverse speed and angle of tilt of the tool are selected as welding parameters. Analysis of variance (ANOVA) is used to analyze the influence of the welding parameters on the responses namely, ultimate tensile strength (UTS) and hardness. The analysis results revealed that the transverse speed is the predominant parameter affecting tensile strength, hardness and quality of the weld. Confirmation test results showed that the Taguchi method coupled with grey relational analysis is very successful in the optimization of welding parameters for maximum strength and hardness in the FSW of AZ91B Magnesium alloy.