Non-traditional machining has become a popular choice for machining of hard and difficult-to-machine materials for generating complex profiles with high dimensional accuracy and surface integrity. In order to improve the performance of the processes, key machining parameters need to be optimized as the costs involved in these processes are comparably high. In this paper, four non-traditional machining processes are considered to optimize using a recently developed metaheuristic technique known as the simple optimization technique (SOPT). The performance of SOPT is compared with the performance of some well-known metaheuristic techniques used to solve the same problems. It is observed that SOPT performs in a superior manner in all these problems as compared to other metaheuristic algorithms. Being one of the simplest algorithms and ability to reach near-optimal solutions for complex, constrained optimization problems makes this algorithm a good choice for solving real-world optimization problems.

The present study explores the application of rapid prototyping (RP) for manufacturing tool electrodes in electro-discharge machining process. The performance of a metallic electrode built via selective laser sintering is compared to solid copper and brass tools during machining of D2 tool steel. In order to efficiently evaluate the influence of several parameters, Taguchi’s L 18 design is adopted to plan the experimental layout. The machining parameters considered in this study are tool type, a categorical parameter and three quantitative parameters such as duty cycle, pulse-on-time and peak current. Multiple performance measures such as material removal rate, tool wear rate, surface roughness and radial over cut of the machined cavity are considered. The multiple performance responses are converted into an equivalent single response known as grey relational grade using grey relational analysis. A nonlinear regression model is developed to relate grey relational grade with process parameters with a coefficient of determination of 0.97. In order to obtain optimal parameter settings satisfying the performance measures, three meta-heuristic algorithms are used due to their computational elegance. The comparative study indicates that particle swarm optimization and simple optimization are effective in delivering the optimized results in substantially less time compared to teaching-learning-based optimization algorithms. It is found that RP tool can perform in a superior manner for simultaneous optimization of multiple responses when compared to copper and brass tools.

Hybrid materials collected from organic and inorganic sources, which are traditionally used as brake lining materials, generally include fly ash, cashew shell powder, phenolic resins, aluminium wool, barites, lime powder, carbon powder and copper powder.The present research focuses on the specific effects produced by fly ash and aims to provide useful indications for the replacement of asbestos due to the health hazards caused by the related fibers.Furthermore, the financial implications related to the use of large-volume use of fly ash, lime stone and cashew shell powder, readily available in most countries in the world, are also discussed.It is shown that many manufacturing and automotive industries, which are currently experiencing difficulties in meeting the increasing demand for brake lining material, may take advantage from the proposed solution.

Wire electro-discharge machining (Wire-EDM) is one of the most versatile and efficient manufacturing process to machine difficult-to-cut materials. In this experiment, wire-EDM of Inconel 625 work piece material is performed by using zinc coated brass wire as wire electrode and distilled water as dielectric fluid. Input parameters taken during experimentation are pulse-on-time (Ton), pulse-off-time (Toff), and servo voltage (Sv). Here, experiments are conducted as per Taguchi’s experimental design i.e. L9 orthogonal array to study the effect of machining parameters on the output responses. To access the machining performance of the wire-EDM process during machining of Inconel 625, the output responses considered are material removal rate (MRR), kerf width (Kw), and average surface roughness (Ra) of the machined surface. For multi-objective optimization of these output responses during the wire-EDM process, desirability function approach is used to achieve better machining performance i.e. higher MRR, lower Kw and lower Ra. The optimum parametric setting for better machining performance is obtained to be Ton = 18 µm, Toff = 53 µm, Sv = 23 V. Also, analysis of variance (ANOVA) is performed to study the influence of machining parameters on the overall output performance (composite desirability). Here, pulse-on-time is found to be the highest significant factor with percentage contribution of 64.14% for composite desirability.

Abstract In this paper, a deep learning integrated reinforcement learning (DLIRL) algorithm is proposed for comprehending intelligent beamsteering in Beyond Fifth Generation (B5G) networks. The smart base station in B5G networks aims to steer the beam towards appropriate user equipment based on the acquaintance of isotropic transmissions. The foremost methodology is to optimize beam direction through reinforcement learning that delivers significant improvement in signal to noise ratio (SNR). This includes alternate path finding during path obstruction and steering the beam appropriately between the smart base station and user equipment. The DLIRL is realized through supervised learning with deep neural networks and deep Q‐learning schemes. The proposed algorithm comprises of an online learning phase for training the weights and a working phase for carrying out the prediction. Results confirm that the performance of the B5G system is improved considerably as compared to its counterparts with a spectral efficiency of 11 bps/Hz at SNR = 10 dB for a bit error rate performance of 10−5. As compared to reinforced learning and deep neural network with a deviation of ±3o and ±5°, respectively, the DLIRL beamforming displays a deviation of ±2o. Moreover, the DLIRL can track the user equipment and steer the beam in its direction with an accuracy of 92%.

The goal of this research is to show that epoxy resin (ER) / coir fiber mats (CFM) hybrid composite laminates with nano-silica particle (NP) reinforcement improve mechanical characteristics and water absorption. Lately, it has been employed in automotive, aerospace, and structural industries where coir fiber-reinforced polymers are safe for ecologically friendly composite applications. The Compression - Hand layup technique is used to make the epoxy composites reinforced with natural coir fibres and nano-silica particles in various weight fractions (5, 10, 15, 20 and 25% by weight). Mechanical parameters such as tensile, flexural, compressive, impact strength, thermal conductivity and also water absorption of composites are evaluated in this study. Scanning electron microscopy is also used to analyze the surface morphology of cracked surfaces (SEM). Hybrid nanosilica-coir fiber mat reinforced epoxy resin has decreased water absorption (percent) suggesting better mechanical qualities. Furthermore, the hybrid epoxy-containing 20% nano-silica coir mat improves all the said mechanical properties.

Electrical discharge machining (EDM) is a thermo-electrical process that can be conveniently utilized for generating complex shaped profiles on hard-to-machine conductive materials using metallic tool electrodes. In this work, composite tools made of copper-tungsten-boron carbide (Cu-W-B4C) manufactured by powder metallurgy (PM) route are used during machining of titanium alloy (Ti6Al4V). The effect of four input machining parameters viz. current, pulse-on-time, duty cycle and percentage of tungsten and boron carbide on material removal rate (MRR), tool wear rate (TWR) and surface roughness (Ra) is studied. A novel meta-heuristic approach such as simple optimization (SOPT) algorithm has been used for single and multi-objective optimization. The pareto-optimal solutions obtained by SOPT have been ranked by VIKOR method to find out the best suitable optimal solution. Analysis of experimental data suggests vital information for controlling the machining parameters to improve the machining performance.

Traditional methods for solving constrained optimization problems are not robust enough to get the solution in reasonable computational time. They have drawback of getting stuck in local optima. To overcome these problems meta-heuristic techniques are now widely used. This paper introduces simple optimization algorithm (SOPT), a meta-heuristic technique for solving constrained optimization problems. To handle the constraints, a constraint fitness priority-based ranking method is included in the algorithm. SOPT algorithm for constraint optimization is coded in MATLAB and applied to design a uniform column for minimum design cost. Result obtained is compared with the result obtained by another important meta-heuristic algorithm called cuckoo search (CS) algorithm.

The hydrodynamic journal bearing is used extensively in rotating machines because of their low wear and good damping characteristics. Present work has been carried out to obtained the realistic performance characteristics of the journal bearing. The optimization approach which was applied to predict the optimal surface textured parameters to improve efficiency of journal bearing. After studied literatures, some parameters are considered as control parameters viz; groove location, groove width, groove height, number of groove and spacing between grooves for load carrying capacity (LCC) and Frictional Torque (FT) response. The effect various surface textured parameter is simulating for optimum response using the Response surface methodology has been applied. The response surface methodology tool re gives the robust design with respect to the control factors and their level. After the optimization method the comparison have been done with published good literature.

In real world multi criteria decision making (MCDM) problem, it is tough to solve a decision matrix with vague and imprecise data. The degree of impreciseness depends on the kind of data avail-able. For interval valued data this impreciseness is less and interval-valued MCDM methods can be effectively used to solve the problem. A flexible manufacturing system (FMS) selection prob-lem was taken into consideration to find the best FMS among available alternatives. An interval extension of CODAS method is proposed in this paper which was used to solve the problem along with two other interval-valued decision-making methods i.e. interval-valued TOPSIS, interval-valued EDAS. All the three methods are distance-based approaches and it was found that the interval-valued CODAS method gave the exact same ranking with that of interval-valued TOPSIS and interval-valued EDAS.

The journal bearing is widely used in gasoline and diesel fueled piston engine in motor vehicle and allowed parts to move together smoothly. Journal bearing are considered to be sliding bearing as opposed to rolling bearing such as ball bearing. The hydrodynamic journal bearings are required and suitable for low temperature and speed. The starting resistance is much greater that running resistance due to slow build-up of lubricant film round the bearing surface. The main problem is identified in the journal bearing is that there is no provision for wear and adjustment on account of wear, and the shaft must be passed into the bearing axially, i.e. endwise. In this bearing limited load on shaft and speed of shaft is low.

Use of oral hormone therapy for hormone receptor positive breast cancer has increased and newer aromatase inhibitor drugs have been incorporated into therapy. However, there is limited data on adherence to oral hormone therapy, or on any differences among drug classes in adherence. The objectives of this study were to 1) determine levels of adherence to oral hormone therapy for breast cancer in the Medicare population, and 2) assess association between hormone therapy type and adherence. Data used were from 2010-2014 SEER-Medicare files. Inclusion criteria were female sex, diagnosis of hormone receptor positive breast cancer, and at least 2 Medicare Part D claims for tamoxifen or aromatase inhibitors. Exclusion criteria were not being continuously enrolled in Medicare. Claim-based medication adherence was calculated as proportion of days covered (PDC) in a one-year period following start of oral hormone therapy. Individuals with PDCs of 0.80 or higher were considered adherent. Multivariate logistic regression was used to assess associations between hormone therapy type and adherence, after controlling for patient demographic characteristics (age, race, income, insurance and marital status). Among 19,200 individuals who met selection criteria, 16,340 (85.1%) took aromatase inhibitors and 2,860 (14.9%) took tamoxifen. The overall proportion (95% confidence interval) of adherent patients was 76.3%, (75.2% - 78.1%). Adherent proportion among aromatase inhibitor users was 78.3%, (77.7% - 78.9%), while 64.7%, (62.9% - 66.4%) of tamoxifen users were adherent to their medication. Age, race, household income, insurance type, and marital-status were not significantly associated with adherence. Based on multivariate logistic regression, patients on an aromatase inhibitor were 1.9 times (1.8-2.1) more likely to be adherent than patients on tamoxifen (p<0.0001), after controlling for age, race, household income, insurance, and marital-status. Women with hormone receptor positive breast cancer were 1.9 times more likely to be adherent to aromatase inhibitors as compared to tamoxifen.

In the era of miniaturization, welding of thin sheets find wide spread applications in developing micro-scale products essentially used in bio-medical, aerospace and automobile industries. During welding of thin sheets, welding deformation needs to be addressed to obtain sound and strong joints. Experimental investigation has been made on laser butt welding using pulsed Nd:YAG laser. Specifically, the study attempts to examine the influence of laser parameters such as laser current, pulse width, and scanning speed on weld quality of thin sheets of 0.45 mm. The quality of weld beads have been analyzed by scanning electron microscope (SEM), optical microscope, and radiography and fractographic inspection. Further, mechanical characterization of the weld beads is made by estimating micro-hardness, residual stress, surface roughness, and welding strength. The study indicates that laser current is the most importance parameters in welding of thin sheets because it helps in obtaining good mechanical and metallurgical qualities of welded joints. The welding strength increases with increase in scanning speed to a certain level and then it reduces. Spot overlapping significantly influences on surface integrity (surface roughness) and welding strength of welded joints. Micro-hardness in fusion zone (FZ) is comparatively higher than that in the heat affected zone (HAZ) because of the difference in grain structure (coarseness) attributed to cooling rate. The study further indicates that there is significant effect of laser pulse energy on development of residual stresses in welded joints. The study is extended to develop empirical relationship between laser parameters and welding strength using non-linear regression analysis. The adequacy of the empirical model is checked by comparing the results obtained from empirical model and experimental values. A new meta-heuristic approach known as simple optimization (SOPT) algorithm has been adopted to obtain optimum parametric setting for welding strength. A relative error of 8.79% is obtained when welding strength at optimal parameter setting is compared with confirmatory experiment.

To achieve high quality of machining at low cost, optimization of cutting parameters of machining processes are required. In this work process parameters of Water Jet Machining(WJM) are optimized using a meta-heuristic algorithm called simple optimization(SOPT) algorithm. SOPT algorithm incorporated with weighted aggregation and crowding distance approach is used to solve two objective optimization problem. The non-dominated solution set obtained is compared with the set obtained from Non-dominated Sorting Genetic Algorithm(NSGA-II).

Electrical discharge machining (EDM) is a non-traditional machining process widely used in the machining of difficult to machine materials. The EDM process is extensively use in aerospace, biomedical, die and mold making industries. In this present work, EDM of AISI 1040 stainless steel work piece has been performed by using three different types of tool electrodes like AiSiMg electrode prepared via selective laser sintering (SLS) process along with conventional copper and brass tool electrodes and EDM 30 oil as dielectric fluid. The SLS process is a rapid prototyping (RP) process also called as additive manufacturing (AM) process, which can be used to produce complex shape tool electrode from metallic powder by melting and sintering with the help of laser power. The EDM is performed by varying different process parameters like discharge current (Ip) and pulse-on-time (Ton). The surface roughness parameters like average roughness (Ra), maximum height of the profile (Rt) and average height of the profile (Rz) are measured by the use of surface roughness measurement machine. To reduce the number of experiments, design of experiment (DOE) approach like Taguchi’s L9 orthogonal array has been use. The surface properties of the EDM specimen are optimized by MOORA method and the best parametric setting is reported for the EDM process. Type of tool is found to be the most significant parameters followed by discharge current and pulse-on-time. The AlSiMg RP electrode gave best surface finish followed by brass and copper. With increase in discharge current and pulse-on-time, the surface roughness value of the EDM machined surface increased. So, it preferable to use lower setting of discharge current and pulse-on-time along with AlSiMg RP electrode to get better surface finish EDM machined specimens.

In last few decades we all witnessed the development in each field. In the field of agricultural also we had seen remarkable development, big farmers are now a day’s using cultivator, harvester, tractor, advance machine tools and advance farm equipments, but in the country like India where more than 70% of farmers are small and marginal and they are still doing farming by traditional method only they are also in need of improved agricultural tools that may be hand driven or bullock driven. In this investigation on failure and analysis of agriculture nine tyne cultivator in different soil condition. Cultivator is important agricultural equipment used for soil preparation in which is stresses are form due to contact of soil, and tyne of cultivator is the actual member to contact the soil and because of this tyne is having a number stresses and find the solution which will minimize determine the stresses. The model of tynes are created by using Creo Parametric software and then by using ANSYS software FEM analysis was done to determine the stresses. The validation of results in good literature Makange et. al. [22], which was also obtained the value of stresses and deformation. In this investigation, the value of stresses and deformation is reducing by using hole and fillet creation in area where maximum stresses are found. Due to hole in tyne the stress and deformation can be reduced. It can be reduced the value of stresses and deformation as compare to Makange et. al. [22].

In the recent years, population based meta-heuristic are developed to solve non-linear optimization problems. These problems are difficult to solve using traditional methods. Simple optimization (SOPT) algorithm is one of the simple and efficient meta-heuristic techniques to solve the non-linear optimization problems. In this paper, SOPT is compared with some of the well-known meta-heuristic techniques viz. Artificial Bee Colony algorithm (ABC), Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Differential Evolutions (DE). For comparison, SOPT algorithm is coded in MATLAB and 25 standard test functions for unconstrained optimization having different characteristics are run for 30 times each. The results of experiments are compared with previously reported results of other algorithms. Promising and comparable results are obtained for most of the test problems. To improve the performance of SOPT, an improvement in the algorithm is proposed which helps it to come out of local optima when algorithm gets trapped in it. In almost all the test problems, improved SOPT is able to get the actual solution at least once in 30 runs.