Abstract Electrical discharge machining (EDM) process is established as an important non-conventional machining method because of its capability to machine very difficult-to-machine (DTM) materials like alloys, composites, die steels etc. Despite the numerous advantages, process has some limitations such as this process consumes huge amount of energy, slow material removal rate, hazardous emissions, generation of toxic dielectric and slurry which make this process an unsuitable and hazardous process. Due to these reasons it is also considered harmful for machine operator and environmental conditions. Whereas, due to increased environmental government regulations (ISO 14000 standards), the cost of manufacturing is getting increased. Therefore, it has become necessary to make the machining process very capable and safe so that both the aspects get managed. This motivates the authors to undertake critical literature scrutiny of recent hybrid integrations with EDM process to perform a safe machining of DTM materials. Also, the work performed in making the process green is reviewed. Authors, concluded that despite, the huge advancement happens in EDM hybridization like powder-mixed EDM, dry EDM, tap water EDM, vibration assisted tool or workpiece etc., still advancement is required in process mechanism which provides high machining efficiency and minimal environmental health hazards.
Abstract Present paper explores the effect of the various tool pin profiles viz. cylindrical, threaded cylindrical, threaded cam and threaded triflute on the joint quality of Friction stir welded aerospace grade aluminium alloy (AA7475). 2.5 mm thick plates of AA7475-T761 are welded using Friction stir welding (FSW) and subsequently, the welds are characterized using optical microscopy (OM) and mechanical testing. Microstructural examinations reveal that the tools with threaded cylindrical, threaded cam, and threaded triflute pin profile lead to the formation of tunneling defect and joint line remnant (JLR) in the welds probably due to imbalance in material movement caused by insufficient plunge and sticking of base material around and on the bottom of the pin. Further, it is also found that cylindrical pin profile results in the maximum tensile strength (291.8 MPa) and threaded cam pin profile gives minimum tensile strength (247.5 MPa). Low tensile strength is observed due to sticking of 0.1 mm thick layer of aluminium on the bottom of the pin leading to reduction in the active plunge causing defects formation and deteriorating the joint quality.
AbstractIn this research work, a statistical model is developed for predicting the optimal process parameters of Fused Deposition Modelling (FDM) process for layout optimization. Multi response optimization of process parameters was achieved using Response Surface Methodology technique integrated with Genetic Algorithm. Response Surface Methodology (RSM) was utilized to design and conduct experiments. 86 experiments were conducted according to central composite design considering six process parameters namely raster width, raster angle, contour width, air gap, slice height and orientation to achieve four responses namely build time, model material volume, support structure volume and production cost. RSM-genetic algorithms (GA) integrated optimization is introduced in which GA is constructed including the development of coding strategy, evaluation operator and the fitness function. The constructed GA can meet the requirement of optimization work. The fitness function is defined as the sum of compulsive constraints or responses. All the constraints/responses have assigned same weightage. A Matlab genetic algorithm solver is utilized to predict best fitness values along with the optimal individual parameters in the present work.
Slags have a central role in pyro-metallurgical processes. They bind impurity compounds and absorb reaction products like oxides and sulfides. Functional slags are made by adding lime, magnesia, fluorspar, bauxite, calcium aluminate or other compounds into the reactor vessel where they form the slag together with the targeted reaction products. Additionally, refractory materials of the vessel tend to dissolve into the slag and thus influence its properties. Converter process for steel-making is a rapid process and slag formation is extremely essential to ensure slag's metallurgical functions and to avoid harmful reactions with the refractory materials. In this contribution, the progress of understanding the phenomena controlling slag formation and means to promote it were shortly reviewed. Thermodynamic constraints in slag formation were examined and the influence of fluxing additions was experimentally stated. Prefabricated "self-fluxing" lime was tested in industrial scale and proved to be a potential slag forming agent. Slag formation in secondary metallurgy and reduction of slag with aluminum dross or granules were experienced, and the effect on desulfurization and steel cleanliness was discussed.
Abstract In this work experimental and numerical result of high speed orthogonal machining of Ti-6AL-4V titanium alloy is presented. High speed orthogonal turning is carried in a lathe using uncoated carbide inserts under dry cutting conditions. Experimental study is carried out by focusing on the measurement of cutting force and cutting temperature. The experimentation is supplemented by simulations from 2D finite element model (FEM) using Third Wave AdvantEdge software. The measured cutting forces and temperature are compared with FEA results. The major factors affecting the machinability of titanium alloy such as spindle speed, feed and cutting tool rake angles are investigated. Numerical results agree with the experimental results at higher speeds and feed levels. These results can be used for further study in high speed turning of titanium alloys.
In the present work, an attempt has been made to establish the accurate surface roughness (Ra, Rq and Rz) prediction model using response surface methodology with Box-Cox transformation in turning of Titanium (Grade-II) under minimum quantity lubrication (MQL) conditions. This surface roughness model has been developed in terms of machining parameters such as cutting speed, feed rate and approach angle. Firstly, some experiments are designed and conducted to determine the optimal MQL parameters of lubricant flow rate, input pressure and compressed air flow rate. After analyzing the MQL parameter, the final experiments are performed with cubic boron nitride (CBN) tool to optimize the machining parameters for surface roughness values i.e., Ra, Rq and Rz using desirability analysis. The outcomes demonstrate that the feed rate is the most influencing factor in the surface roughness values as compared to cutting speed and approach angle. The predicted results are fairly close to experimental values and hence, the developed models using Box-Cox transformation can be used for prediction satisfactorily.
In the present work investigation primarily focuses on identifying the presence of cutting tool vibrations during face turning process. For this purpose an online non-contact vibration transducer i.e. laser Doppler Vibrometer is used as part of a novel approach. The revisions in the values of cutting forces, vibrations and acoustic optic emission signals with cutting tool wear are recorded and analyzed. This paper presents a mathematical model in an attempt to understand tool life-under vibratory cutting conditions. Tool wear and cutting force data are collected in the dry machiningof AISI 1040 steel at different vibrationinduced test conditions. Identifying the correlation among tool wear, cutting forces and displacement due to vibration is a critical task in the present study. These results are used to predict the evolution of displacement and tool wear in the experiment. Specifically, the research tasks include: to provide an appropriate experimental data to prove the mathematical model of tool wear based on the influence of cutting tool vibrations in turning. The modeling is focused on demonstrating the scientific relationship between the process variables such as vibration displacement, vibration amplitude, feedrate, depth of cut and spindle speed while getting into account machine dynamics effect and the effects such as surface roughness and tool wear generated in the operation. Present work also concentrates on the improvement in machinability during vibration assisted turning with different cutting tools. The effect of work piece displacement due to vibration on the tool wear is critically analyzed. Finally, tool wear is established on the basis of the maximum displacement that can be tolerated in a process for an effective tool condition monitoring system.
Current processes for beneficiation of titaniferous minerals are energy-intensive and produce significant waste. The benefit of alkali roasting over existing process is that it minimises waste. Previous studies on liquid phase formation during alkali roasting of titaniferous minerals were based on the use of Na2CO3, whereas this study focuses on oxidative roasting of titaniferous minerals with either NaOH or KOH, using different alkali to mineral ratios. Phase equilibria of the Na/K-Fe-Ti-O system are calculated the results compared to observed results. This work attempts to characterise the alkali-rich liquid phase formed during roasting and determine its impact on alkali titanate and alkali ferrite separation, as it has been found that Ti-K-Fe-O and Ti-Na-Fe-O ternary phases can be present. The presence of the liquid phase at the reaction interface adversely affects the oxygen diffusion during roasting, which has consequences on the products formed.
Abstract Forecasting of inventory is an enigma to various firms at different echelon levels of supply chain. Abnormality in forecasting an inventory may leads to fluctuations in upstream supply chain. On upswing it can be uneconomical in terms of stock-out cost, while on the down trend it can be expensive in terms of stock holding costs. To amend the firms efficiency, in this paper the model developed by (Akhtar Tanveer et al. An Optimization model for Mitigating Bullwhip-Effect in a Two-Echelon Supply chain. Int conf Traf Transp Stud 2014;138:289–97) is successfully applied to steel processing firm to mitigate the Bull-whip or Whip-lash effect in the supply chain. The objective function is to minimize the variation between the actual order quantity and demand forecast of multiple products at various echelons and the simple exponential smoothing is compiled to forecast the demand of products. The model is furthermore validated by an illustration of seven products and it depicts that the model emanates an optimal set of smoothing parameters to attenuate the whip-lash effect.
In any type of welding, its heat affected zone (HAZ) is the most critical section where the probability of hydrogen or solidification cracking is prominent. Continuous efforts are being applied by researchers and welders to minimize HAZ and its alterations. For the same purpose, by varying the factors of submerged arc welding (SAW) process which directly influences the heat input and cooling rate of the weld, experiments are carried out on the plates of micro-alloyed high strength pipeline steel. Voltage, welding speed, contact tube to work distance, wire feed rate and pre-heating temperature are taken as process variables. The experiments are designed according to the central composite rotatable design approach of response surface methodology (RSM). Multi-objective optimization of HAZ characteristics (HAZ area and its hardness) is carried out using grey relational analysis (GRA). To un-correlate the correlated characteristics of HAZ, principal component analysis (PCA) approach is coupled with GRA. The results of the confirmatory test have shown an improvement of 28.51% and 5.94% in area and hardness value of HAZ respectively at optimal setting combination of SAW process parameters.
The decoupling point separates part of the supply chain oriented towards customer orders from the part based on forecast planning. This paper focuses on identification of bottlenecks and their positioning with respect to customer order decoupling point (CODP) in supply chain continuum. The research is based on a conceptual model that separates engineer to order (ETO), make to order (MTO), assemble to order (ATO) and make to stock (MTS) by a decoupling point. The important feature of this paper is that supply, demand and operational constraints are allocated in specific part of the supply chain, making it more versatile. Shifting bottleneck concepts, including impact of bottleneck position and issues concerning production and capacity planning, are studied extensively to stabilize the supply chain and reduce its complexity.
Machining of alloy materials at high cutting speeds produces high temperatures in the cutting zone, which affects the surface quality. Thus, developing a model for estimating the cutting parameters and optimizing this model to minimize the surface roughness and cutting temperatures becomes utmost important to avoid any damage to the quality surface. This paper presents the development of new models and optimizing these models of machining parameters to minimize the surface roughness and cutting temperature in end milling process by Taguchi method with the statistical approach. Two objectives have been considered, minimum arithmetic mean roughness (Ra) and cutting temperature. Due to the complexity of this machining optimization problem, a single objective Taguchi method has been applied to resolve the problem, and the results have been analyzed.
Gasifier operation is an intricate process because of the complex relationship between slag chemistry and temperature, limitations of feedstock materials, and operational preference. High gasification temperatures increase refractory degradation, while low gasification temperatures can lead to slag buildup on the gasifier sidewall or exit, either of which are problematic during operation. Maximizing refractory service life and gasifier performance require finding an optimized operating temperature range which is a function of the coal slag chemistry and viscosity. Gasifier operators typically use a slag's viscosity-temperature relationship and/or ash-fusion fluid temperature to determine the gasification temperature range. NETL has built a slag management toolset to determine the optimal temperature range for gasification of a carbon feedstock. This toolset is based on a viscosity database containing experimental data, and a number of models used to predict slag viscosity as a function of composition and temperature. Gasifier users typically have no scientific basis for selecting an operational temperature range for gasification, instead using experience to select operational conditions. The use of the toolset presented in this paper provides a basis for estimating or modifying carbon feedstock slags generated from ash impurities in carbon feedstock.
The extraction of chromium from chromite ore is based on the oxidative alkali roasting of the mineral forming water-soluble alkali chromates. Previous investigations reported the formation of a molten Na2CO3-Na2CrO4 binary mixture during roasting of chromite with sodium carbonate. The physical properties of the Na2CO3-Na2CrO4 liquid phase, which are dependent on temperature, charge and gangue composition, play an important role in the oxidation reaction and may limit the chromium recovery by hindering the oxygen transport to the reaction interface.
In this paper, for the purpose of better control as well as multi-objective optimization of bead geometry parameters, the optimal combination of submerged arc welding (SAW) process variables is determined using fuzzy logic approach. Open circuit voltage, trolley speed, contact tube to work distance, preheating temperature and wire feed rate are taken as process variables during SAW of the pipeline steel. For this experimental investigation, experiments are designed and performed according to response surface methodology (RSM). Bead width, penetration, and reinforcement are taken as the performance measures in bead geometry. In fuzzy logic, two membership function (MF) namely triangular and trapezoidal are employed for the performance comparison of SAW process. As compared to triangular MF, the use of trapezoidal MF has given the more logical and better-optimized results for bead geometry parameters. Outcomes of the study are also confirmed by conducting the confirmatory experiments.
Analysis of shrinkage characteristics of Aluminium-Silicon alloy was studied theoretically and experimentally. The Aluminium alloys considered in the study are A413 (LM6), A360 (LM9) and A380 (LM24). Extensive literature survey has suggested that cavity filling and solidification process are two most critical aspects to produce high quality casting components. A statistical model of parameters and response to understand the influence of parameters on shrinkage and casting yield studies has been presented. Experiments were conducted in foundry in industrial environment to produce commercially treated aluminium alloy castings in sand mould. Alloy was found to be most significant factor influencing shrinkage. The yield of casting was improved using insulating and exothermic sleeves. Solidification time of exothermic riser was 10% more than insulated riser. Thus, in order to produce radiographic quality casting a theoretical and experimental method is presented so that number of trials in foundry is reduced which leads to increased reliability and productivity. Study also shows that by using sleeves considerable metal is saved, energy saving during melting, improved quality, reduced cost and increased capacity of plant can be achieved.
In laser cutting, the capability of laser cutting mainly depends on optical and thermal properties of work material. The surface quality and metallurgical properties of the product is most important from the point of laser cutting quality. The present research work explores the modeling and optimization of laser beam cutting process parameters by using hybrid approach of Taguchi based fuzzy logic. The multi-response optimization of process parameters has been done to improve geometrical accuracy by minimizing the kerf width and kerf deviation. The four input parameters power, gas pressure, feed rate, pulse frequency and three output parameters kerf width (KW), kerf deviation (KD) and material removal rate (MRR) have been taken for the experimentation work. The S/N ratios taken for the KW and KD is of the smaller-the-better type and MRR is of the higher the better type. The predicting fuzzy logic model is implemented on Fuzzy Logic Toolbox of MATLAB using Mamdani technique. The fuzzy logic theory has been applied to compute the fuzzy multi-response performance index (FMRPI). This performance index is further used for multi-objective optimization. The selected samples were analyzed using scanning electron microscope. The predicted optimum results have been validated by performing the confirmation tests. The confirmation tests showed the considerable reduction in kerf deviation and increase in material removal rate.
Cutting tool vibration analysis is the effective way to understand the machining characteristics of any material. In the present work, the effect of process parameters on cutting tool vibration is estimated using Taguchi method in turning of EN25 steel. Taguchi method uses Signal-to-Noise ratio (S/N) and Analysis of Variance (ANOVA) to determine the optimum level of process parameters and significant parameters. The results showed that cutting speed of 215 m/min, feed rate of 0.07mm/rev and depth of cut of 0.5 mm are the optimum combination of process parameters. Cutting speed and depth of cut are the influencing parameters on cutting tool vibration. The results are experimentally verified and the results based on turning process response can be effectively improved.
This paper presents a convenient and an easy to use manufacturing method for parts with axisymmetric geometry on CNC milling machines. The desired form of the cavities is achieved by selecting as generatrix curve any plane curve, implicitly or parametrically defined, which fulfills specific imposed by the user criteria (functional, aesthetic or other). Each machining pass is modelled as a path composed of generatrix curve segments and semicircular arcs. The surface quality is controlled by keeping the distance between successive scallops within a programmed value. Tool motion along the desired paths is generated by G-code algorithms that exploit the parametric programming technique, a powerful CNC programming tool. The effectiveness of the proposed method is verified by simulation tests for three representative curves.
Acrylonitrile-butadiene-styrene (ABS) has great verity applications in aerospace and automobiles industries. Mechanical strength of the ABS is superior to even that of impact resistant polystyrene. In addition metallic coatings can be applied to the surface of ABS moldings. The main aim of the present work is to investigate the mechanical properties of additives of basalt fibers (BF) to ABS with (5, 10, and 15) wt% embedded into the polymer matrix by using plastic injection molding technique. This new perceptions has been done on basalt fibers that have a potential low cost with its good mechanical performance. The ultimate tensile strength that obtained from the composite with 15wt% is 56.67MPa with 40.52% increase value than neat ABS, Young's modulus gradually increases with increasing the amount of additives. Impact un-notched strength decreases with a reported increment of 24.617 KJ.m(-2). A Rockwell hardness test is also used and with the increases of additives the amount of hardness of the composite increases. A scan electron microscopy (SEM) on the fracture surface is captured to check the morphologies structure of the composite comparable with a neat ABS. and it is showed a very good distribution and bonding of the B.F. with the pure ABS. As well as the cost of the ABS and BF is reduced by a percentage of 15 %.
