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The main objective of this experimental work is to analyze and measure the form tolerances namely flatness and squareness while machining a meso deep hole in EDM on Inconel-718 material plate.

The experiments were performed on 15 amps rated SPARKONIX-EDM as per DOE (design of experiments). Kerosene was used as a dielectric along with constant pressure of 0.2 kg/cm² for all trial runs. The currents T_on and T_off were selected as process constraints to conduct experimental trials. The MRR, EWR, machining time and form tolerances were considered as output responses. The experimental outcomes were optimized by hybrid optimization using Taguchi and GRA (grey relational analysis) method.

The EDM process parameters for Ni-based super alloy namely Inconel-718 had optimized by using GRA method coupled with Taguchi method. The optimum solution has been calculated for MRR, EWR, machining time and form tolerances namely squareness and flatness. The optimized parameters for the output responses in EDM process are Peak current (Ip) 12 Amps, 400 µs T_on (pulse on time) and 10 µs T_off (pulse off time). An attempt had also been made to attain Max. and Min. Evaluation of MRR and form tolerances, respectively. The attained optimum outcomes had also been examined through a real experiment and established to be satisfactory.

This article will facilitate the defense, aerospace and EDM industries to improve their productivity with closer tolerances.

The optimized parameters by multi-parametric optimization showed the considerable improvement in the process and will facilitate the defense, aerospace and EDM industries to improve their productivity with closer tolerances.

The purpose of this paper is to analyze and optimize the roller burnishing process parameters using the design of experiments and grey relational analysis (GRA).

In this experimental work, the carbide burnishing tool has been selected for the machining of AISI-1040 high carbon steel to get better product quality and satisfactory machining characteristics. The material surface condition while machining, burnishing tool speed, feed rate, depth of penetration and No. of passes have been selected as process constraints to conduct experimental trials.

The surface roughness (SR) and surface hardness were considered as output responses. The experimental outcomes optimized by multi-parametric optimization showed considerable improvement in the process. The roller speed and number of passes are the most significant parameters for surface hardness, whereas the surface condition and roller penetration depth have the most significance on SR.

The GRA method shows the 0.03376 improvement in grey relational grade between the experimental values and the predicted values.

The experimental outcomes optimized by multi-parametric optimization showed the considerable improvement in the process and will facilitate steel industries to enhance and improve productivity while burnishing high carbon steel (AISI-1040).

This research represents valid work, and the authors have no conflict of interests.

This paper aims to present a methodology of finding temperature dependencies of selected physical parameters of metals. The method is based on the combination of measurement of the surface temperature of material during the process of heating and subsequent solution of the inverse problem using multi-parametric optimization.

The methodology is based on measurements and numerical solution of the forward and inverse problem, taking into account all involved nonlinearities (saturation curve of the processed steel material and temperature dependences of its physical parameters). The inverse problem is solved by a genetic algorithm.

The suggested methodology was successfully verified on several metal materials whose temperature-dependent parameters are known. The calculated and measured results exhibit a very good accordance (the differences do not exceed about 10 per cent for room and higher temperatures).

At this moment, the methodology successfully works when the temperature dependence of just one material parameter is to be found (which means that the temperature dependencies of other parameters are known). The accuracy of results also depends on the correctness of other input data.

This paper provides a relatively easy possibility of finding the temperature dependencies of thermal conductivity or heat capacity of various alloys.

The paper proposes a methodology of finding the temperature dependence of a given material parameter that is not known in advance (which is of great importance in case of alloys).

The purpose of this paper is to examine the performance parameters of WEDM to improve the productivity and material removal rate (MRR) with a high surface finish of high chromium-high carbon dies steel.

The experiments were performed on AGIE CUT 220 CNC WEDM. High chromium-high carbon dies steel (D3) was used in the form of a rectangular plate. The workpiece and the brass wire having diameter ɸ 0.25 mm had linked up with +ve and –ve polarity in the DC power source, respectively. De-ionized water having a conductivity level of 0.6 µs/cm was used as the dielectric medium. The dielectric fluid was flushed from the top and bottom nozzles and material was submerged in the dielectric.

The WEDM process parameters for D3 die steel had optimized by using Grey relational analysis method couples with Taguchi method. The optimum solution has been calculated for MRR, cutting speed (Cs), machining time and surface roughness (SR) (Ra value). A fuzzy logic model using Matlab was developed for the prediction of performance parameters, namely MRR, cutting speed (Cs), machining time (M/c time) and SR with respect to changes in input parameters.

The fuzzy model shows the 96.19 percent accuracy between the experimental values and the predicted values.

The optimized parameters by multi-parametric optimization method showed considerable improvement in the process and will facilitate the WEDM, tool and die industries, defense and aerospace industries to improve the productivity with the higher surface finish.

This manuscript represents valid work and the authors have no conflict of interests. The attained optimum outcomes had also been examined through a real experiment and established to be satisfactory.

The purpose of the research is to study the consequences of total (comprehensive) automatization of entrepreneurship for interested parties through the prism of competition human and artificial intellectual capital in production and distribution in Industry 4.0.

The research is conducted with application of scenario analysis, regression analysis, imitation modeling, forecasting and non-linear multi-parametric optimization with the simplex method.

The authors perform scenario modeling of competition between human and artificial intellectual capital in production and distribution in Industry 4.0 and offer recommendations for pro-active management of competition between human and artificial intellectual capital in production and distribution in Industry 4.0.

Contrary to the existing approach to studying competition between human and artificial intellectual capital in Industry 4.0, automatization of distribution, not production, is most preferable. This shows increase of the value of human intellectual capital in distribution during its automatization based on AI. This is an unprecedented and breakthrough conclusion for the modern economic science. It allows creating a completely new direction of research of competition between human and artificial intellectual capital in production and distribution in Industry 4.0, in which optimization of social consequences is achieved not by means of restraint of automatization but by means of its stimulation. The key condition is stimulation of automatization of distribution with limited automatization of production. Based on this conclusion, it is recommended to continue research in continuation of the presented work.

This paper aims to investigate the influence of “BroncoCut-X” (copper core-ZnCu50 coating) electrode on the machining of Ti-3Al-2.5V in view of its extensive use in aerospace and medical applications. The machining parameters are selected as Spark-off Time (ST_off), Spark-on Time (ST_on), Wire-speed (S_w), Wire-Tension (WT) and Servo-Voltage (S_v) to explore the machining outcomes. The response characteristics are measured in terms of material removal rate (MRR), average kerf width (KW) and average-surface roughness (SA).

Taguchi’s approach is used to design the experiment. The “AC Progress V2 high precision CNC-WEDM” is used to conduct the experiments with ϕ 0.25 mm diameter wire electrode. The machining performance characteristics are examined using main effect plots and analysis of variance. The grey-relation analysis and fuzzy interference system techniques have been developed to combine (called grey-fuzzy reasoning grade) the experimental response while Rao-Algorithm is used to calculate the optimal performance.

The hybrid optimization result is obtained as ST_off = 50µs, ST_on = 105µs, S_w = 7 m/min, WT = 12N and S_v=20V. Additionally, the result is compared with the firefly algorithm and improved gray-wolf optimizer to check the efficacy of the intended approach. The confirmatory test has been further conducted to verify optimization results and recorded 8.14% overall machinability enhancement. Moreover, the scanning electron microscopy analysis further demonstrated effectiveness in the WEDMed surface with a maximum 4.32 µm recast layer.

The adopted methodology helped to attain the highest machinability level. To the best of the authors’ knowledge, this work is the first investigation within the considered parametric range and adopted optimization technique for Ti-3Al-2.5V using the wire-electro discharge machining.

Additive manufacturing (AM) is one of the latest and most advanced technologies that are continuously expanding into various field applications. Undoubtedly, fused deposition modeling (FDM) is one of the oldest and extensively used AM technologies not only because of the advantage of low cost, comparatively moderate production speed and negligible wastage but also due to acceptance of a wide range of thermoplastics, reinforced and blended feedstock for making the end product suitable for service. The purpose of this work to perform mechanical characterization of standard samples printed on FDM with acrylonitrile butadiene styrene (ABS), shape memory polymer (SMP; make Polyflex^TM) and ABS/Polyflex^TM blend and a comparative study from AM view point.

A low-cost desktop-based FDM setup was used for the fabrication of the test specimens under different processing conditions. Experiments were conducted as per obtained control log, and statistical analysis was conducted to understand the effect of selected variables in response of measured properties. Further, scanning electron microscopy-based micrographs were analyzed to understand the fracture mechanisms.

The obtained results highlighted that the mechanical properties of FDM parts are strongly influenced by the selected process variables. However, in case of most of the measured properties, selection of suitable feedstock has dominated the other input variables. Further, the results of test parts made with in-house developed ABS/SMP blend have showed the attainment of remarkable values of both strength and elasticity.

This work is held to empower the use of FDM technology to fabricate advanced and robust components for serving highly demanding applications.

The justification of information technology (IT) is inherently fuzzy, both in theory and practice. This is due to the largely intangible dimensions of IT projects. In view of this, this research note presents the results of ongoing research, in the application of Fuzzy Cognitive Mapping (FCM), as a tool to identify complex functional interrelationships associated with the justification of IT. This paper presents a theoretical functional model which describes these relationships and, by using an FCM, further interrelationships are developed in the context of justifying IT projects. A procedure which would address the optimisation of these intangible relationships in the form of a genetic algorithm (GA) is proposed as a process for investment justification.

The purpose of this paper is to fabricate acrylonitrile-butadiene-styrene (ABS)/high impact polystyrene (HIPS) based multi-material geometries using a low cost polymer printer. At the same time, efforts have been made to investigate the mechanical characteristics of the obtained prints and to perform the optimization using the Taguchi-Grey (TGRA) method.

Initially, the feedstock materials were in-house fabricated in the form of filament wires, workable with fused filament fabrication (FFF) technique, of 1.75 ± 0.1 mm diameter by using a single screw extruder. Multi-material structures were fabricated using variable parameters (such as: raster angles, layer height, fill density and solid layers) and the experimentation was conducted as per Taguchi L18 array. Mechanical responses obtained by performing tensile, impact and bending test were studied in response to input variables and ultimately optimized settings were obtained, for individual as well as multiple parameters). Scanning electron microscopy (SEM) analysis was performed to analyze the fractured surfaces.

The Signal/Noise (S/N) plots for the quality characteristics highlighted that selected input parameters significantly influenced the obtained values for tensile strength, impact strength and flexural strength. Micrographs of the fractured specimens showed the occurrence of brittle fracture with higher levels of perimeter, infill density and solid layers. The extent of delamination was also increased under the bending load and further increased by increasing solid layers.

The results of the study strongly advocated the utility of fabricated multi-materials structures in automotive, aerospace and other manufacturing industries.

This work represents the fabrication, testing and analysis of polymer-based multi-material structures for engineering applications.

The purpose of this paper is to establish a methodology for the design and development of patient-specific elbow implant with an elastic modulus close to that of the human bone. One of the most preferred implant material is titanium alloy which is about 8 to 9 times higher in strength than that of the human bone and is the closest than other metallic biomedical materials.

The methodology begins with the design of the implant from patient-specific computed tomography information and incorporates the manufacturing of the implant via a novel rapid prototyping assisted microwave sintering process.

The elastic modulus and the flexural strength of the implant were observed to be comparable to that of human elbow bones. The fatigue test depicts that the implant survives the one million cycles under physiological loading conditions. Other mechanical properties such as impact energy absorption, hardness and life cycle tests were also evaluated. The implant surface promotes human cell growth and adhesion and does not cause any adverse or undesired effects i.e. no cytotoxicity.

Stress shielding, and therefore, aseptic loosening of the implant shall be avoided. In the event of any trauma post-implantation, the implant would not hurt the patient.

The present study describes a methodology for the first time to be able to obtain the strength required for the medical implant without sacrificing the fatigue life requirement.