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This study aims to explore the potential of the engraving milling process to manufacture 3D structures and layouts like rotor wheels. An experimental study was carried out to manufacture a stepped rotor wheel from EN8 steel blank using a computer numeric control (CNC) engraving milling machine tool. The impact of variable parameters, namely rotational speed (SR), feed (f), and plunge feed (Pf), on maximum roughness depth (Rt) and material removal rate (MRR) was determined through a total of fourteen tests, each with two replications based on Box-Behnken design (BBD) of the response surface methodology (RSM). The best variable combination was found using desirability functional analysis (DFA) with goals of minimizing Rt and maximizing the MRR. The best values achieved at the optimal combination of variable parameters were 2.95 µm as Rt and 43.45 mm³/min as MRR. Micrographs of the rotor wheel blades and cutting tool supported the findings.

This article presents a case study on improving process efficiency in a mining equipment part fabrication company. The company was facing issues concerning communication, organisation, and workflow processes. This study investigated that ineffective communication among departments was the major weakness which was responsible for the long lead or idle time. This lead time was a waste that affected the company’s productivity. A great amount of time was spent on non-value-added processes. The Kanban Centralised Communication System was implemented. Time study and value stream mapping were also used. A significant improvement in process efficiency from 34% to 85% was achieved by reducing lead time from 4200 minutes to 1680 minutes after streamlining the communication in the company using Kanban. [ABSTRACT FROM AUTHOR]

The pursuit of energy efficiency in machining processes is a critical aspect of sustainable manufacturing. A significant portion of global energy consumption is by the industrial sector; thus, improving the energy efficiency of machining processes can lead to substantial environmental and economic benefits. The present study reviews the recent advancement made for improving the energy efficiency of machining processes. First the energy consumption of the machining processes was explored and then the key areas and developments in their energy consumption modeling were identified. Following this, the review explores various strategies for achieving energy savings in machining. These strategies include energy-efficient machine tools, the accurate modeling of the energy consumption of machining processes, the implementation of optimization techniques and the application of artificial intelligence (AI). Additionally, the review highlights the potential of AI in further reducing energy consumption within machining operations and achieving energy efficiency. A review of these energy-saving strategies in machining processes reveals impressive potential for significant reductions in energy consumption: energy-efficient design can achieve up to a 45% reduction, optimizing cutting parameters may minimize consumption by around 40%, optimizing tool paths can reduce consumption by approximately 50%, optimizing non-cutting energy consumption and sequencing can lead to savings of about 30% and employing AI shows promising energy efficiency improvements of around 20%. Overall, the present review offers valuable insights into recent advancements in making machining processes more energy-efficient. It identifies key areas where significant energy savings can be achieved. [ABSTRACT FROM AUTHOR]

This work presents the wire-EDM of WC-Co composite and optimization of process parameters using an integrated technique of response surface methodology (RSM), Vise Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) and artificial bee colony (ABC) algorithm to obtain the best set of machinability indicators. Wire feed (WF), servo voltage (SV), pulse off-time (Pon) and pulse on-time (Poff) are the variable process parameters, whereas root mean square roughness (Rq), average surface roughness (Ra) and material removal rate (MRR) are the machinability indicators considered in the present work. A total of twenty nine experiments have been conducted based on Box Behnken design (BBD) technique of response surface methodology. VIKOR has been used for normalization of responses and followed by solving empirical models using ABC algorithm to obtain optimized process parameters setting. WF-12 m/min, SV-65V, Pon-116 µs, Poff-20 µs are the optimum wire-EDM parameters obtained by intelligent RSM-VIKOR-ABC technique that produced best values of Ra-4.51 µm, Rq-5.64 µm, MRR-0.061 mm3 /min simultaneously. The validation test confirmed an improvement up to 15% in the response characteristics which proved the effectiveness of this novel hybrid technique for optimization. The optimum parameter setting is for ready industrial reference to attain best surface quality and process productivity for WC-Co composite machining by wire-EDM.

The present research investigated the turning of AZ31B magnesium alloy in a dry environment using carbide tool inserts coated with tungsten carbonitride (TiCn) and thin alumina (Al2O3). A Box–Behnken design based on fifteen experiments showed a proportional increasing trend of flank wear with all three machining parameters, i.e., cutting speed, feed rate, and depth of cut. The most influential parameter is the cutting speed. A maximum flank wear of 299.34 µm due to excessive adhesion of work material on the tool face was observed at a high cutting speed. Machining at low speed resulted in a significant reduction in tool wear due to less chipping. The tool wear and chip morphology study confirmed the results. [ABSTRACT FROM AUTHOR]

This paper presents the results of an investigation conducted on wire electric discharge machining (wire-EDM) of miniature ratchet gears. Effects of three important process parameters spark duration, 'Ton', spark-off-duration 'Toff', and wire tension 'WT' on surface quality, i.e., mean roughness depth 'Rz' and productivity, i.e., material erosion speed 'MES', have been investigated by conducting seventeen experimental trials. Both Ton and Toff have been identified as the significant parameters. Further, an optimization of wire-EDM parameters resulted in simultaneously best compromise values of Rz 5.30 µm and MES 6.75 mm/min and is achieved the following cutting regime: Ton 1.5 µs, Toff 42.5 µs, and WT 1500 g. At the end, surface quality study has been conducted to evaluate the tribological fitness of the miniature ratchet gear machined at optimum combination of wire-EDM parameter values. It was investigated that the generation of uniform and shallow craters on the flank surfaces of ratchet gear machined at optimum values of parameters, imparted smoother bearing area curve and lower coefficient of friction. The profile and flank surface of the ratchet gear also found free from cracks, burrs, and dirt. [ABSTRACT FROM AUTHOR]

This paper reports the surface quality of a miniature cylindrical titanium rod/bar (MCTB) turned by the wire electrical discharge turning (WEDT) process using a zinc-coated wire of 250 µm diameter. The surface quality was mainly evaluated by considering the very important surface roughness parameters, i.e., the mean roughness depth. A Box–Behnken design (BBD) of the response surface methodology (RSM) based on 17 experimental runs was conducted, where the spark duration "Ton" was found as the most influential parameter affecting the mean roughness depth "RZ" of the miniature titanium bar. Further, using the grey relational analysis (GRA) technique of optimization, we obtained the least value of "RZ" 7.42 µm after machining a miniature cylindrical titanium bar with the optimum combination of WEDT's variable parameters: Ton—0.9 µs, SV—30 V, and DOC—0.35 mm. This optimization led to a 37% reduction in the surface roughness Rz of the MCTB. The tribological characteristics of this MCTB were also found favorable after conducting a wear test. After completing a comparative study, we can claim that our results are better than those of the past research conducted in this area. The findings of this study are beneficial for the micro-turning of cylindrical bars made from a variety of difficult-to-machine materials. [ABSTRACT FROM AUTHOR]

Shape memory alloys are important biomaterials but difficult-to-machine (DTM). Their machining needs to be done using intelligent techniques to obtain a better machinability. Hybrid optimization is one of such techniques which can perform modeling and optimization of machining parameters for the best values of machinability indicators. Wire electric discharge machining (WEDM) of shape memory alloy has been found as a prominent alternate to the conventional machining techniques; however it needs the assistance of intelligent techniques to machine such materials to obtain the optimum values of machinability indicators. In this paper, WEDM of shape memory alloy Ni55.8Ti was reported. WEDM was carried out by varying four process parameters i.e. servo voltage SV, pulse-on time Pon, pulse-off time Poff, and wire feed rate WF using Taguchi L16 robust design of experiment technique. A hybrid optimization technique TOPSIS-Fuzzy-PSO has been successfully used to optimize these parameters (SV-50V; Pon-1µs; Poff-17 µs; WF-4 m/min) for the best possible values of material removal rate (MRR) – 0.049 g/min, maximum roughness – 11.45 µm, and recast layer – 22.10 µm simultaneously. [ABSTRACT FROM AUTHOR]

In the present work, an attempt is made to partially replace high cost silica sand with sustainable eco-friendly cow-dung. The practical utility of cow dung as an additive material that facilitates binding in sand moulds has been tested. The Taguchi method is used to plan and conduct nine experiments with three replicates each. Pareto analysis of variance study is performed to understand the practical significance of moulding sand variables, that is, percentage of cow dung, clay, water, and degree of ramming on sand mould properties. The conflicting multiple objective functions (maximize mould hardness, and minimize collapsibility and gas evolution) are optimized by utilizing the Data Envelopment Analysis Ranking (DEAR) method. The optimal parameters i.e. 6% of clay, 4% of water, 5% of cow-dung and 4 numbers of ramming strokes are obtained by applying a hybrid Taguchi-DEAR method. These parameters show the best moulding properties are: mould hardness 55, gas evolution 5.9 ml·g-1, and collapsibility 470 g·cm-2. Thereafter, a Lovejoy coupling made of aluminium is cast in the sand mould prepared with cow dung and without cow dung, with the optimum set of parameters. The mechanical properties, surface finish, and microstructure of the casting cast with cow-dung are better than that without cow- dung. [ABSTRACT FROM AUTHOR]

In the present research, Ni55.8Ti shape memory alloy has been machined by wire electric discharge machining (wire-EDM) process. The effects of input parameters such as spark gap voltage, pulse on-time, pulse off-time, and wire feed on productivity, i.e., metal removal rate (MRR) and surface quality, i.e., mean roughness depth (Rz), have been investigated. Empirical modeling and ANOVA study have been done after conducting 16 experiments based on Taguchi's L16 design of experiment technique. Ranking and crowding distance–based non-dominated sorting algorithm-II (NSGA-II) is used for process optimization. The error percentage varies within ± 6% between experimental results and the predicted results developed by NSGA-II. It has been observed that the wire-EDM machining of Ni55.8Ti alloy at optimum parameters resulted in improved MRR —0.021 g/min—and surface quality with good surface finish (Rz—6.2 μm) and integrity as significant reduction in the formation of cracks, lumps, and deposited layers. [ABSTRACT FROM AUTHOR]

Surface roughness parameters are important indicators for determining the operating performance, tribology behavior, wear and tear characteristics, and service life of engineered parts including gears. This article presents the investigation on surface roughness, and tribology and wear aspects of miniature brass gears manufactured by abrasive water jet machining. Experiments have been conducted based on Taguchi's robust design technique with L9 orthogonal array to machine external spur-type miniature gears of brass having 8.4 mm pitch diameter, 12 teeth, and 5 mm thickness. The effect of three important process parameters namely water jet pressure, abrasive mass flow rate, and stand-off distance on mean roughness depth of miniature gears are analyzed. Surface roughness is found to decrease with the increase in the water jet pressure and abrasive mass flow rate, and increases with the increase in the stand-off distance. Particle swarm optimization technique has been used for parametric optimization to minimize the surface roughness of miniature gears. Confirmation experiment conducted at optimized abrasive water jet machining parameters resulted in superfine surface finish with mean roughness depth value of 4.1 µm superior than the finish obtained by other advanced processes for brass gears. The investigated values of bearing area characteristics, skewness, kurtosis, and friction coefficient confirm the tribological fitness of the miniature brass gear machined at optimum abrasive water jet machining parameters. [ABSTRACT FROM AUTHOR]

This paper reports about the analysis and optimization of micro-geometry parameters (i.e. total profile deviation 'Fa' and accumulated pitch deviation 'Fp') of the wire electric discharge machined (WEDMed) fine-pitch miniature spur gears made of brass. Effects of four WEDM process parameters namely voltage, pulse-on time, pulse-off time and wire feed rate on the micro-geometry of the miniature gears were analyzed by conducting the experiments designed using Box-Behnken approach of response surface methodology (RSM). Analysis of variance study found all four input parameters significant. Larger deviations in profile and pitch were observed with higher values of the voltage and pulse-on time, and with lower values of wire feed rate and pulse-off time. Multi-performance optimization of WEDM parameters was done using the desirability analysis to minimize profile deviation and pitch deviation simultaneously. The values of Fa and Fp of the gear obtained by the confirmation experiment conducted at the optimized WEDM parameters were as 11.5μm and 9.1μm respectively. These values categorize the WEDMed gear having DIN quality number as 7 and 5 respectively for profile and pitch which are better than those obtained by the conventional miniature gear manufacturing processes. [ABSTRACT FROM AUTHOR]

This article reports about analysis and optimization of surface roughness parameters (i.e. average roughness Ra and maximum roughness Rt) of wire electrical discharge machined fine-pitch miniature spur gears made of brass. Effects of four wire electrical discharge machining process parameters (i.e. voltage, pulse-on time, pulse-off time and wire feed rate) on the surface roughness parameters of the miniature gears were studied by conducting 29 experiments with two replicates each and designed based on Box–Behnken approach of response surface methodology. Analysis of variance study found all four input parameters to be significant. Experimentally, the surface roughness has been found to increase with higher voltage and longer pulse-on time and decrease with longer pulse-off time and higher wire feed rate. Desirability analysis was used to optimize the wire electrical discharge machining parameters, so as to minimize the Ra and Rt simultaneously. Optimum values of Ra and Rt obtained from the confirmation experiments conducted at the optimized wire electrical discharge machining parameters are superior than the values reported in the literature. Artificial neural network model has been developed for prediction of the surface roughness of the wire electrical discharge machined miniature gears. Very close agreement was found among the surface roughness values predicted by response surface methodology and artificial neural network with the corresponding experimental values. [ABSTRACT FROM PUBLISHER]

This paper reports the results of investigation conducted on CO 2 laser cutting of miniature gears of stainless steel 304. In this work, analysis of the effects of important laser parameters such as power, cutting speed, focal position, and gas pressure on average surface roughness (R a) has been investigated. Stainless steel spur gears having 9.04 mm outside diameter and 4.5 mm face width have been cut using a CO 2 laser system with nitrogen as assisted gas. A total of twenty nine experiments have been conducted based on BBD (Box-Behnken Design) technique of response surface methodology where aforementioned laser parameters varied at three levels each. ANOVA study found focal position as the most significant parameter. Further, the Desirability based optimization of laser parameters obtained best values of R a - 0.43 μm at laser power- 2407 W, cutting speed- 1.25 m/min, focal position- (-) 2.4 mm, gas pressure- 12.5 bar. A scanned electron microscopy study also revealed the good surface morphology of the miniature gear machined at optimum parameters. [ABSTRACT FROM AUTHOR]

• Analysis and optimization of machinability of Al 7075 for aerospace application is presented. • Effect of machining parameters on form error and surface roughness is investigated. • Optimization is done for good surface quality and material removal rate. • Empirical models are developed for correlation of process parameters and machinability indicators. • Optimal turning parameters for ready industrial use are recommended for Al 7075. This paper presents a systematic investigation on analysis and optimization of surface quality during turning of high strength Al 7075. In this central composite design based study, the effect of four important machining parameters such as cutting speed, feed rate, depth of cut, and tool nose radius on the surface quality characteristics namely form error i.e. cylindricity error and circularity error, and average surface roughness has been investigated. The material removal rate is also considered as an important response parameter. The analysis of variance study has been conducted to find the statistically significant parameters. The derived empirical relationships predicted the randomly generated test cases with less than 8.51%. Optimization for multiple outputs with conflicting requirements has been done using the principal component analysis and JAYA algorithm that resulted in the absolute deviation of 7.97% with average roughness- 0.64 µm, circularity error- 4.34 µm, cylindricity error- 0.365 µm, and material removal rate-28.63 cm3/min. [ABSTRACT FROM AUTHOR]