Selection Of Appropriate Process Parameters Research Articles

Robust optimization for reducing welding-induced angular distortion in fiber laser keyhole welding under process parameter uncertainty

Welding-induced angular distortion is a typical out-of-plane distortion, which brings negative effects on the joints’ quality. Therefore, the selection of appropriate process parameters to minimize or control welding-induced distortion under uncertainty has become of critical importance. In this paper, a robust process parameter optimization framework is proposed to reduce welding-induced distortion in fiber laser keyhole welding under parameter uncertainty. Firstly, a three-dimensional thermal-mechanical finite element model (FEM) for simulating the welding-induced distortion is developed and validated by laser welding experiment. Secondly, a Gaussian process (GP) model is constructed to build the relationship between the input process parameters and output responses. Finally, uncertainty quantification of both process parameter uncertainty and GP model uncertainty is derived. The obtained uncertainty quantification formulas are used in the robust optimization problem to minimize welding-induced distortion. The effectiveness and reliability of the obtained robust optimum are verified by the Monte Carlo method.

Effect of Tailoring Martensite Shape and Spatial Distribution on Tensile Deformation Characteristics of Dual Phase Steels

The authors simulated the industrially used continuous annealing conditions to process dual phase (DP) steels by using a custom designed annealing simulator. Sixty-seven percentage of cold rolled steel sheets was subjected to different processing routes, including the conventional continuous annealing line (CAL), intercritical annealing (ICA), and thermal cycling (TC), to investigate the effect of change in volume fraction, shape, and spatial distribution of martensite on tensile deformation characteristics of DP steels. Annealing parameters were derived using commercial software, including thermo-calc, jmat-pro, and dictra. Through selection of appropriate process parameters, the authors found out possibilities of significantly altering the volume fraction, morphology, and grain size distribution of martensite phase. These constituent variations showed a strong influence on tensile properties of DP steels. It was observed that TC route modified the martensite morphology from the typical lath type to in-grain globular/oblong type and significantly reduced the martensite grain size. This route improved the strength–ductility combination from 590 MPa–33% (obtained through CAL route) to 660 MPa–30%. Finally, the underlying mechanisms of crack initiation/void formation, etc., in different DP microstructures were discussed.

Predictive modeling and the effect of process parameters on the hardness and bead characteristics for laser-cladded stainless steel

Laser cladding is a novel additive manufacturing and surface treatment process associated with many interactive process parameters. Using the response surface method with a central composite design, a structured design of experiments approach was chosen to examine the influence of selected process parameters on the bead geometry and hardness for single-track laser-cladded specimens using AISI 420 stainless steel powder on a AISI 1018 substrate. In the present study, robust predictive models for hardness, bead aspect ratio, and wetting angle with the substrate were determined using multiple regression analysis. The geometry and hardness relationships to the process inputs were evaluated using F-statistics from the analysis of variance and compared by utilizing perturbation plots, 3D surface mapping, and contour plots. The highly coupled non-linear relationships are evident from these analyses, but this study revealed that the laser speed has the most significant effect on the bead microhardness and the powder feed rate was found to be the most significant parameter for these bead geometry parameters. The perturbation plots confirmed this sensitivity of those process parameters. This research study gives a guideline for the selection of appropriate process parameters for the laser cladding process to achieve desired hardness and bead geometry.

Optimization of friction and wear characteristics of varied cryogenically treated hot die steel grade AISI-H13 under dry condition

Cryogenic treatment (CT) is a relatively new field, which has emerged during the last three decades of the twentieth century. However, its impact on material shaping and making tool life, and enhancement of their mechanical properties are quite remarkable. The selection of appropriate process parameters for CT is essential for cost reduction and optimum productivity. This study focuses on the influence of key parameters of CT cycles (i.e., soaking temperature and duration) on the friction and wear behavior of AISI H13 hot die steel under dry sliding conditions against hardened and tempered AISI D3 cold work tool steel (counter face) at varying sliding speeds and loads. Mathematical models have been developed for wear rate, the average coefficient of friction, and maximum contact temperature using the Box-Cox methodology. The developed mathematical models have been validated by comparing with the experimental results. Moreover, the optimum values of the process parameter have been employed to maximize the output and validate the same by confirmation of the experiments. To the best of our knowledge, this is the first study that demonstrates the modeling and optimization of sliding friction and wear characteristics of AISI H13 under varied CT cycles.

Selection of Appropriate Process Parameters for Gas Metal Arc Welding of a Steel under 100% Carbon Dioxide Gas Shield

Selection of Appropriate Process Parameters for Gas Metal Arc Welding of a Steel under 100% Carbon Dioxide Gas Shield

Selection of Appropriate Process Parameters for Gas Metal Arc Welding of a Steel under 100% Carbon Dioxide Gas Shield

Selection of Appropriate Process Parameters for Gas Metal Arc Welding of a Steel under 100% Carbon Dioxide Gas Shield

Normalised model-based processing diagrams for additive layer manufacture of engineering alloys

Additive Layer Manufacturing (ALM) is becoming a more widely accepted method for the production of near net-shape products across a range of industries and alloys. Depending on the end application, a level of process substantiation is required for new parts or alloys. Prior knowledge of the likely process parameter ranges that will provide a target region for the process integrity can save valuable time and resource during initial ALM trials. In this paper, the parameters used during the powder bed ALM process have been taken from the literature and the present study to construct normalised process maps for the ALM process by building on an approach taken by Ion et al. in the early 1990's (J.C. Ion, H.R. Shercliff, M.F. Ashby, Acta Metallurgica et Materialia 40 (1992) 1539–1551). These process maps present isopleths of normalised equivalent energy density (E0*) and are designed to provide a practical framework for comparing a range of ALM platforms, alloys and process parameters and provide a priori information on microstructure. The diagrams provide a useful reference and methodology to aid in the selection of appropriate processing parameters during the early development stages. This paper also applies the methodology to worked examples of Ti–6Al–4V depositions processed using different Electron Beam Melting parameters.

Visual Analytics as an Enabler for Manufacturing Process Decision-making

The goal of an optimal manufacturing process is to maximize product performance while minimizing cost, time, and waste. A critical component of this optimization is the appropriate selection of process parameters. While central physical concepts often serve as a starting point, specific parameter selection is frequently done manually, based on operator skill, experience, and intuition. As a result, process optimization is often iterative, non-repeatable, and lacking in traceability. Further, there is no fundamental insight gained into the relationship between process parameter selection and critical process outputs. This paper explores the use of visual analytics as an enabler for manufacturing process decision making. An emerging science, visual analytics couples analytical reasoning with the substantial capability of the human brain to rapidly internalize and understand data that is presented visually. Through the use of interactive interfaces, visual analytics provides a mechanism through which the operator, engineer, and decision-maker can cooperate in real-time with both simulation, experimental, and operational data, facilitating trade studies, what-if analysis, and providing crucial insight into correlations and relationships that drive process optimization. As an exemplar, the concept of visual analytics is applied to the simulation of a notional high pressure die casting process, with the goal of gaining insight into those parameters that contribute to high scrap rates, particularly air entrapment.

Prediction of Laser Cut Quality for Tungsten Alloy Using the Neural Network Method

The cut quality is of great importance during the laser cutting process. The quality of laser cut mainly depends on an appropriate selection of process parameters. In this paper, the effect of process parameters was analysed on the laser cut quality of an uncommon alloy, the tungsten alloy (W ≈ 92.5 % and the remainder Fe and Ni) sheet with thickness of 1 mm. This alloy has a wide application in different industrial areas, e.g. in medical applications, the automobile sectors, and the aircraft industry. This paper introduces a developed back-propagation artificial neural network (BP- ANN) model for the analysis and prediction of cut quality during the CO2 laser cutting process. In the presented study, three input process parameters were considered such as laser power, cutting speed and assist gas type, and two output parameters such as kerf width and average surface roughness. Amongst the 42 experimental results, 34 data sets were chosen for training the network, whilst the remaining 8 results were used as test data. The average prediction error was found to be 5.5 % for kerf width and 9.5 % for surface roughness. The results of the predicted kerf width and surface roughness by the BP-ANN model were compared with experimental data. Based on the results of the study, it was shown that the proposed artificial neural network model could be a useful tool for analysing and predicting surface roughness and kerf width during CO2 laser cutting processes.

Delignification of intact biomass and cellulosic coproduct of acid‐catalyzed hydrolysis

The kinetics of acid‐catalyzed hemicellulose removal and also alkaline delignification of oat hull biomass were investigated. All three operational parameters namely, catalyst concentration (0.10–0.55 N H2SO4), temperature (110–130°C), and residence time (up to 150 min) affected the efficiency of hemicellulose removal, with 100% of hemicellulose removed by appropriate selection of process parameters. Analysis of delignification kinetics (in the temperature range of 30–100°C) indicated that it can be expressed very well by a two‐phase model for the crude biomass and also for the hemicellulose‐prehydrolyzed material. The application of acid‐catalyzed prehydrolysis improved the capacity of lignin dissolution especially at lower temperatures (30 and 65°C) and accelerated the dissolution of lignin. This acceleration of delignification by prehydrolysis was possible at all levels of temperature in the bulk phase; however, results were more significant at the lower temperatures in the terminal phase. © 2015 American Institute of Chemical Engineers AIChE J, 61: 1783–1791, 2015

Process optimization in Nd:YAG laser microdrilling of alumina–aluminium interpenetrating phase composite

In laser beam micromachining process, the quality of the drilled hole is of great importance. The quality of the microdrilled hole mainly depends on appropriate selection of process parameters. Predefined diameter of hole with minimum taper is of today's demand. The composite used for microdrilling operation is alumina–aluminium (Al2O3–Al) interpenetrating phase composite (IPC), which is widely used in aircraft and space stations. Until date, no experimental study has been done to obtain microdrilled hole of desired diameter. In the present paper three hole qualities such as hole diameter at entry, at exit and hole taper have been optimized individually as well as simultaneously using a central composite design (CCD) based on response surface methodology (RSM) during pulsed Nd:YAG laser microdrilling operation on alumina–aluminium IPC sheet of 1.14mm thickness. The analysis of variance (ANOVA) test has also been done to identify the process parameters that contributed the most to get desired hole quality.

Effects of discharge energy density on wear rate and surface roughness in EDM

Electric discharge machining is one of the widely used nontraditional methods in manufacturing industry. In the present study, the effects of discharge energy density on the material removal rate, electrode wear rate, surface average roughness of the workpiece and the tool electrode were investigated. AISI 1040 steel as workpiece material and electrolytic copper as tool electrode were selected. Experiments were designed and conducted using one-factor-at-a-time approach. During the experiments, current and voltage were kept constant, whereas pulse on time and pulse off time were varied at two levels. In order to investigate and analyze the effects of discharge energy density on the responses, different diameters of the tool electrode were used. It has been observed that the discharge energy density could be considered as a significant factor for appropriate selection of process parameters for better machining characteristics.

Density of additively-manufactured, 316L SS parts using laser powder-bed fusion at powers up to 400 W

Selective laser melting is a powder-based, additive-manufacturing process where a three-dimensional part is produced, layer by layer, by using a high-energy laser beam to fuse the metallic powder particles. A particular challenge in this process is the selection of appropriate process parameters that result in parts with desired properties. In this study, we describe an approach to selecting parameters for high-density (>99 %) parts using 316L stainless steel. Though there has been significant success in achieving near-full density for 316L parts, this work has been limited to laser powers 99 %, with the density reducing rapidly at high speeds due to insufficient melting, and less rapidly at low speeds due to the effect of voids created as the process enters keyhole mode.

SELECTION OF APPROPRIATE PROCESS PARAMETERS FOR GAS METAL ARC WELDING OF MEDIUM CARBON STEEL SPECIMENS

Gas Metal Arc Welding (GMAW) is a semi-automated process used widely for accurate welding in the fabrication industry. The selection of appropriate process parameters of GMAW is essential to obtain the desired weld quality. Â In the past, much work has been done investigating a variety of workpiece and electrode material combinations. In the present work, an Analytical Hierarchy Process (AHP) based parametric optimization is tried in gas metal arc welding of C45 medium carbon steel specimens using carbon dioxide as the gas shield. The experiments were performed by varying three process parameters, weld speed, weld voltage and weld current. The AHP facilitates the selection of suitable process parameters to obtain a sound weld. In the present experimental domain, optimal conditions are evaluated to be at a weld voltage of 30 V, weld current of 160 A with a weld speed of 475.75 mm/min. http://dx.doi.org/10.13033/ijahp.v5i2.184

Parametric Optimization of Submerged ARC Welding Using L9 Orthogonal Array

Submerged arc welding process is usually employed for welding of thick workpieces. Quality of submerged arc welded components depends on various factors. Selection of appropriate process parameters for joining metallic components is needed to obtain sound weldment. Many researchers carried out investigations to find out appropriate process conditions to obtain quality submerged arc welded components with typical applications. In the present work, Taguchi's L9 orthogonal array is used to find out the parameter combinations of the experiments to perform. Weld current, weld speed and type of flux are varied to three levels to find out the appropriate condition to obtain desired bead-on-plate quality within the domain of experimental conditions chosen. It is found out that at a weld current of 400 A, welding speed of 450 mm/min and with flux with basicity index of 1.2, desired weld deposition can be obtained.

Backward Hole-Flanging Technology Using an Incremental Approach

The manufacturing of necks on the sheet metal parts using conventional hole-flanging process in small series production is sometimes too expensive or even impossible due to the complexity of the product. For these reasons, a modern manufacturing concept called the “backward incremental hole-flanging process” is proposed. It enables producing necks on the final products that can be very complex or even closed with minimal expense. Special attention is dedicated to researching technological particularities and limitations according to industrial requirements. Due to numerous input factors having various levels of influence, empirical modelling was selected with the aim of ensuring better prediction of results. It enables predicting the impact of each particular input parameter and their iterations on the selected output variables. Results show that forming tool diameter, and horizontal and vertical step sizes have the greatest influence on the process. Moreover, the appropriate selection of process parameters results on a higher forming limit ratio and consequently, on larger necks achieved without cracks in comparison to the conventional hole-flanging process. The reason could be found in local incremental deformation of the sheet metal and a more suitable stress state.

Studies on weld shape formation and Marangoni convection in Nd:YAG laser welding

Laser welding is a high energy beam welding process. Selection of process parameters is vital for the desired weld shape formation. Trial and error method for selection of appropriate process parameters prevailing in other welding processes is not suitable for laser welding. The effect of process parameters on the weld shape formation is analysed in this study with and without Marangoni convection. Finite volume method is adopted to study the heat transfer and fluid flow during the welding based on the solution of the equations of conservation of mass, momentum and energy in the weld pool. The studies are carried out on AISI 304 stainless steel of thickness 2 mm and its thermophysical properties are considered for the modelling and simulation. The simulated weld shape profiles are compared with the experimentally measured profile for different sets of welding parameters and all the simulated welds shapes are found to be in agreement.

A Study on Wear Resistance, Hardness and Impact Behaviour of Carburized Fe-Based Powder Metallurgy Parts for Automotive Applications

In order to study the mechanical and triboloical properties of powder metallurgy (PM) parts under different process parameters, the specimens were used in pack carburizing processes. These specimens made from industrial test pieces were carburized in a powder pack for about two to five hours at a temperature of about 850?C - 950?C. The effects of austenitization and quenching are investigated on some specimens. Also the wear tests are performed by means of a pin-on-disc tribotester using roll bearing steel as the counterface material. The results indicate that by appropriate selection of process parameters, it is possible to obtain high wear resistance along with moderate toughness. It is concluded that surface treatments increases the wear resistance and performance of PM parts in service conditions. By increasing the role of PM in industry which resulted from their ability to produce the complex shapes, high production rate, and dimension accuracy of final products, they need to be heat treated. Carburizing method was selected as a surface hardening method for PM parts. Results of wear and hardness show considerable enhancement in mechanical properties of PM parts.

Discrete laser spot transformation hardening of AISI O1 tool steel using pulsed Nd:YAG laser

Discrete laser spot transformation hardening is a process that creates isolated laser hardening spots, usually distributed in a certain pattern, on a component surface, covering only a fraction of the surface region that is being treated. The process offers several unique advantages for tribological applications, including improved lubrication conditions and wear performance and increased productivity. However, very limited information is available on the appropriate selection of processing parameters to achieve optimal results. In this paper, discrete laser spot hardening of AISI O1 tool steel has been studied using a pulsed Nd:YAG laser. Effect of various laser processing parameters, including laser pulse energy, pulse duration and defocus distance, on characteristics of the laser treated spots are investigated. Maps are experimentally established for processing parameter selections in discrete laser spot transformation hardening of the AISI O1 tool steel. Results show that the maximum diameter and depth of transformation hardening zones with no surface melting increase with the increase of laser pulse energy. However, they are not markedly affected by laser pulse duration. On the other hand, longer pulse durations at a given pulse energy reduce the size of softening zone surrounding the central hardening zone and are thus more favourable for most practical applications. Short laser pulse durations below 8 ms tend to produce shallower hardening zones and are not recommended for wear applications.

Modeling Cutting Forces for Five Axis Milling of Sculptured Surfaces

5-axis ball-end milling processes are used in various industries such as aerospace, automotive, die-mold and biomedical industries. 5-axis machining provides reduced cycle times and more accurate machining via reduction in machining setups, use of shorter tools due to improved tool accessibility. However, desired machining productivity and precision can be obtained by physical modeling of machining processes via appropriate selection of process parameters. In response to this gap in the industry this paper presents a cutting force model for 5-axis ball-end milling cutting force prediction. Cutter-workpiece engagement is extracted via developed solid modeler based engagement model. Simultaneous 5-axis milling tests are conducted on Al7075 workpiece material with a carbide cutting tool. Validation of the proposed model is performed for impeller hub roughing toolpaths. Validation test proves that presented model is computationally efficient and cutting forces can be predicted reasonably well. The result of validation test and detailed comparison with the simulation are also presented in the paper.