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Metal matrix composites (MMCs) are engineered materials formed by the combination of metal matrix and reinforcement materials. They have a stiff and hard reinforcing phase in metallic matrix. The matrix includes metals such as aluminum, magnesium, copper and their alloys. The purpose of this paper is to describe the development of an aluminum alloy‐aluminum oxide composite using a new combination of vortex method and pressure die casting technique and the subsequent tribological studies.

An aluminum alloy‐aluminum oxide composite was developed using vortex method and pressure die casting technique. The aluminum alloy‐1 wt% aluminum oxide was die cast using LM24 aluminum alloy as the matrix material and aluminum oxide particles of average particle size of 16 μm as a reinforcement material. The friction and wear characteristics of the composite were assessed using a pin‐on‐disc set‐up; the test specimen, 8‐mm diameter cylindrical specimens of the composite, was mated against hardened En 36 steel disc of 65 HRC. The tests were conducted with normal loads of 9.8, 29.4 and 49 N and sliding speeds of 3, 4 and 5 m/s for a sliding distance of 5,000 m. The frictional load and the wear were measured at regular intervals of sliding distance.

The effects of normal load and sliding speed on tribological properties of the MMC pin on sliding with En 36 steel disc were evaluated. The wear rate increases with normal load and sliding speed. The specific wear rate marginally decreases with normal load. The coefficient of friction decreases with normal load and sliding speed. The wear and friction coefficient of the aluminum alloy‐aluminum oxide MMC are lower than the plain aluminum alloy. The wear and coefficient of friction of the entire specimens are lower.

The development of aluminum alloy‐aluminum oxide composite using vortex method and pressure die casting technique will revolutionize the automobile and other industries, since a near net shape at low cost and very good mechanical properties are obtained.

There are few papers available on the development of (or tribological studies of) MMCs including aluminium/aluminium alloy‐ceramic composites developed by combination of vortex method and pressure die casting technique.

The literature reveals there is a limited knowledge regarding the extraction of long natural fibers, in particular those extracted from leaves. This investigation aims to present the extraction process and the characterization of long natural cellulose fibers from doum palm leaves (Hyphaene thebaica L.), with properties suitable for polymeric composite materials and textile applications.

The resulting H. thebaica L. fibers were identified using Attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, X-ray diffraction (XRD), thermogravimetric analysis (TGA) and scanning electron microscopy (SEM). The physical properties of the extracted fibers were measured to estimate the reliability of extraction conditions. Mechanical properties were evaluated to determine ultimate strength, Young’s modulus and strain-at-failure of the fibers of the doum leaves.

The following properties of the doum palm are listed in this paper: physical properties of doum palm fibers (H. thebaica L.), TGA, XRD of doum palm fibers, tensile properties of doum palm fibers and surface morphology of doum palm fibers.

Like synthetic fibers, the inclusion of short or long natural fibers into the polymer matrix can increase tensile, flexural and compressive strengths of these matrixes. Compared to the short-length natural fibers, longer-length fibers provide better reinforcements and therefore accord higher performances to the composites. Long fibers can also provide exceptional opportunities to develop a new class of advanced lightweight composites and have the potential to rival glass fiber in the manufacture of composite materials, using matrix materials, such as polypropylene, epoxy and phenolic resins.

The following values are presented in this paper: density of doum palm fibers = 1.14-1.40 g/cm², linear density (Tex) = 33.10 ±11.5, equivalent diameter (µm) = 178.72 ± 41.7, diameter (µm) = 137.02-220.42, tensile strength (MPa) = 124.84-448.10, Young’s modulus (GPa) = 8.06-19.59, strain-at-failure (%) = 0.81-2.86.

The most promising replacements for the industrial applications are particle reinforced metal matrix composites because of their good and combined mechanical properties. Currently, the need of matrix materials for industrial applications is widely satisfied by aluminium alloys. The purpose of this paper is to evaluate the tribological behaviour of the zinc oxide (ZnO) particles reinforced AA6061 composites prepared by stir casting route.

In this study, AA6061 aluminium alloy matrix reinforced with varying weight percentages (3%, 4.5% and 6%) of ZnO particles, including monolithic AA6061 alloy samples, is cast by the most economical fabrication method, called stir casting. The prepared sample was subjected to X-ray photoelectron spectroscopy (XPS) analysis, experimental density measurement by Archimedian principle and theoretical density by rule of mixture and hardness test to investigate mechanical property. The dry sliding wear behaviour of the composites was investigated using pin-on-disc tribometer with various applied loads of 15 and 20 N, with constant sliding velocity and distance. The wear rate, coefficient of friction (COF) and worn surfaces of the composite specimens and their effects were also investigated in this work.

XPS results confirm the homogeneous distribution of ZnO microparticles in the Al matrix. The Vickers hardness result reveals that higher ZnO reinforced (6%) sample have 34.4% higher values of HV than the monolithic aluminium sample. The sliding wear tests similarly show that increasing the weight percentage of ZnO particles leads to a reduced wear rate and COF of 30.01% and 26.32% lower than unreinforced alloy for 15 N and 36.35% and 25% for 20 N applied load. From the worn surface morphological studies, it was evidently noticed that ZnO particles dispersed throughout the matrix and it had strong bonding between the reinforcement and the matrix, which significantly reduced the plastic deformation of the surfaces.

The uniqueness of this work is to use the reinforcement of ZnO particles with AA6061 matrix and preparing by stir casting route and to study and analyse the physical, hardness and tribological behaviour of the composite materials.

The aim of this paper is to study the tribological behaviour of Fe‐C‐Al cast iron at different temperatures using universal pin‐on‐disk machine.

The cold set resin bonded sand mould casting process was employed to develop Fe‐C‐Al cast iron and Fe‐C‐Si cast iron. The microstructures of materials were studied using field emission scanning electron microscope. The wear and friction tests were conducted using universal pin‐on‐disk machine at 25°C, 100°C, 200°C and 300°C temperature. The worn surface was characterized using scanning electron microscopy.

The lower wear rate was found for Fe‐C‐Al cast iron compared to Fe‐C‐Si cast iron and delamination type wear morphology was observed in both types of cast iron materials. The results also showed that the friction coefficient value of Fe‐C‐Al cast iron was lower than that of Fe‐C‐Si cast iron at different temperatures. It can be concluded that the overall tribological behaviour of Fe‐C‐Al cast iron at higher temperatures was better than conventional Fe‐C‐Si cast iron.

The information on the development and tribological properties of the Fe‐C‐Al cast iron at different temperatures is scarce in the literature. The special type of cold set resin bonded sand mould was used for casting this Fe‐C‐Al cast iron material. Therefore, the current study is quite new and it is hoped that it will provide a high value to the automotive and other engineering researchers for the application of this material.

AA2014 is a copper-based alloy and is typically used for production of complex machined components, given its better machinability. The purpose of this paper was to study the effects of variation in weight percentage of ceramic Al₂O₃ particulates during electrical discharge machining (EDM) of stir cast AA2014 composites. Scanning electron microscopy (SEM) examination was carried out to study characteristics of EDMed surface of Al₂O₃/AA2014 composites.

The effect of machining parameters on performance measures during sinker EDM of stir cast Al₂O₃/AA2014 composites was examined by “one factor at a time” (OFAT) method. The stir cast samples were obtained by using three levels of weight percentage of Al₂O₃ particulates, i.e. 0 Wt.%, 10 Wt.% and 20 Wt.% with density 1.87 g/cc, 2.35 g/cc and 2.98 g/cc respectively. Machining parameters varied were peak current (1-30 amp), discharge voltage (30-100 V), pulse on time (15-300 µs) and pulse off time (15-450 µs) to study their influence on material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR).

MRR and SR decreased with an increase in weight percentage of ceramic Al₂O₃ particulates at the expense of TWR. This was attributed to increased microhardness for reinforced stir cast composites. However, microhardness of EDMed samples at fixed values of machining parameters, i.e. 9 amp current, 60 V voltage, 90 µs pulse off time and 90 µs pulse on time reduced by 58.34, 52.25 and 46.85 per cent for stir cast AA2014, 10 Wt.% Al₂O₃/AA2014 and 20 Wt.% Al₂O₃/AA2014, respectively. SEM and quantitative energy dispersive spectroscopy (EDS) analysis revealed ceramic Al₂O₃ particulate thermal spalling in 20 Wt.% Al₂O₃/AA2014 composite. This was because of increased particulate weight percentage leading to steep temperature gradients in between layers of base material and heat affected zone.

This work was an essential step to assess the machinability for material design of Al₂O₃ reinforced aluminium metal matrix composites (AMMCs). Experimental investigation on sinker EDM of high weight fraction of particulates in AA2014, i.e. 10 Wt.% Al₂O₃ and 20 Wt.% Al₂O₃, has not been reported in archival literature. The AMMCs were EDMed at variable peak currents, voltages, pulse on and pulse off times. The effects of process parameters on MRR, TWR and SR were analysed with comparisons made to show the effect of Al₂O₃ particulate contents.

The purpose of this paper is to determine the optimum level of geometrical parameters such as helix angle, nose radius, rake angle and machining parameters such as cutting speed, feed rate and depth of cut to arrive minimum surface roughness and tool wear during end milling of Al 356/SiC metal matrix composites (MMCs) using high speed steel end mill cutter.

L27 Taguchi orthogonal design with six factors and three levels is employed for conducting experiments. Analysis of variance (ANOVA) is carried out using Minitab16 software to find the influence of each input parameter on output performance measure. Grey-fuzzy logic multi optimisation algorithm is used to find the optimum level of the input parameters for minimum surface roughness and tool wear simultaneously.

It is found that optimal combination of helix angle 40°, nose radius 0.8 mm, rake angle 12°, cutting speed 90 m/min, feed rate 0.04 mm/rev and depth of cut 1.5 mm have generated minimum surface roughness of 0.4063 µm and tool wear of 0.0375 mm. From ANOVA analysis, it is found that cutting speed influence is more on output performance followed by helix angle and rake angle compared with other machining and geometrical parameters.

The influence of tool geometry during end milling of MMC using Grey-fuzzy logic algorithm has not been explored previously.

The present research work aims to study the friction coefficient in functionally graded rapid prototyping of Al–Al₂O₃ composite prepared via fused deposition modelling (FDM)-assisted investment casting (IC) process. The optimized settings of the process parameters (namely, filament proportion, volume of FDM pattern, density of FDM pattern, barrel finishing (BF) time, BF media weight and number of IC slurry layers) suggested in the present research work will help fabricate parts possessing higher frictional coefficient.

Initially, melt flow index (MFI) of two different proportions of Nylon6-Al–Al₂O₃ (to be used as an alternative FDM filament material) was tested on the melt flow indexer and matched with MFI of commercially used acrylonitrile–butadiene–styrene filament. After this, the selected proportions of Nylon6-Al–Al₂O₃ were prepared in the form of the FDM filament by using a single screw extruder. Further, this FDM filament has been used for developing sacrificial IC patterns in the existing FDM system which was barely finished to improve their surface finish. Castings developed were tested for their wear resistance properties on a pin-on-disc-type tribo-tester under dry conditions at sliding conditions to check their suitability as a frictional device for industrial applications. In the methodology part, Taguchi L18 orthogonal array was used to study the effect of selected process variables on the coefficient of friction (μ).

It has been found that filament proportion, volume of FDM pattern and density of FDM pattern have significantly affected the μ-values. Further, density of the FDM pattern was found to have 91.62 per cent contribution in obtaining μ-values. Scanning electron micrographs highlighted uniform distribution of Al₂O₃ particles in the Al-matrix at suggested optimized settings.

The present methodology shows the development of a functional graded material that consisted of surface reinforcement with Al₂O₃ particles, which could have applications for manufacturing friction surfaces such as clutch plates, brake drum, etc.

This paper describes the effect of process parameters on wear properties of the Al–Al₂O₃ composite developed as a functionally graded material by the FDM-based pattern in the IC process.

An optimized model is often deployed to reduce trial and error in experimental approach and obtain the multi-variant correlation. In this study, response surface methodology (RSM), namely, Box–Behnken design (BBD) approach, has been used to optimize the characterization of lubricant with additives. BBD is based on multivariate analysis whereby the effects of different parameters are considered simultaneously. It is a non-linear system which is more representative of the actual phenomenon. This study aims to investigate the effect of three independent variables, namely, speed, load and concentration of TiO₂, on the coefficient of friction (CoF).

RSM was applied to get the multiplicity of the self-determining input variables and construct mathematical models. Mathematical models were established to predict the CoF and to conduct a statistical analysis of the independent variables’ interactions on response surface using Minitab 16.0 statistical software. Three parameters were regulated: speed (X₁), load (X₂) and concentration of TiO₂ (X₃). The output measured was the CoF.

The result obtained from BBD has shown that the most influential parameter was speed, followed by concentration of TiO₂ nanoparticles and then normal load. Analysis of variance indicated that the proposed experiment from the quadratic model has successfully interpreted the experimental data with a coefficient of determination R² = 0.9931. From the contour plot of BBD, the optimization zone for interacting variables has been obtained. The zone indicates two regions of lower friction values (<0.04): concentration between 0.5 to 1.0 Wt.% for a speed range of 1,000 to 2,000 rpm, and load between 17 to 20 kg for a speed in the range of 1,200 to 1,900 rpm. The optimized condition shows that the minimum value of CoF (0.0191) is at speed of 1,782 rpm, load of 20 kg and TiO₂ concentration of 1.0 Wt.%.

In general, it has been shown that RSM is an effective and powerful tool in experimental optimization of multi-variants.

The purpose of this paper is to develop an effective methodology for implementing lean manufacturing strategies and a leanness evaluation metric using continuous performance measurement (CPM).

Based on five lean principles, a systematic lean implementation methodology for manufacturing organizations has been proposed. A simplified leanness evaluation metric consisting of both efficiency and effectiveness attributes of manufacturing performance has been developed for continuous evaluation of lean implementation. A case study to validate the proposed methodology has been conducted and proposed CPM metric has been used to assess the manufacturing leanness.

Proposed methodology is able to systematically identify manufacturing wastes, select appropriate lean tools, identify relevant performance indicators, achieve significant performance improvement and establish lean culture in the organization. Continuous performance measurement matrices in terms of efficiency and effectiveness are proved to be appropriate methods for continuous evaluation of lean performance.

Effectiveness of the method developed has been demonstrated by applying it in a real life assembly process. However, more tests/applications will be necessary to generalize the findings.

Results show that applying the methods developed, managers can successfully identify and remove manufacturing wastes from their production processes. By improving process efficiency, they can optimize their resource allocations. Manufacturers now have a validated step by step methodology for successfully implementing lean strategies.

According to the authors' best knowledge, this is the first known study that proposed a systematic lean implementation methodology based on lean principles and continuous improvement techniques. Evaluation of performance improvement by lean strategies is a critical issue. This study develops a simplified leanness evaluation metric considering both efficiency and effectiveness attributes and integrates it with the lean implementation methodology.

This paper aims to develop a lean manufacturing road map for industrial firms by selecting the appropriate lean tools relying on the predefined strategic objectives and the firm constraints. It also illustrates how to prioritize these tools considering their interrelationship.

Relying on the predefined strategic objectives, operational objectives can be set by using the balanced scorecard (BSC). Afterwards, the theory of constraints (TOC) is introduced to investigate the manufacturing system and to determine its constraints. For these constraints, the principle of fault tree analysis (FTA) is used to determine their root causes. Consequently, lean manufacturing tools/initiatives can be proposed. Finally, the fuzzy-decision making trial and evaluation laboratory (fuzzy-DEMATEL) method is implemented to prioritize these initiatives and to construct a suitable lean road map by managing experts’ knowledge.

The practical results indicate that diagnosing the manufacturing system and managing experts’ knowledge to select the appropriate lean initiatives, and prioritizing these initiatives relying on the understanding of their interrelationship could support achieving the strategic targets without consuming extra time or resources.

The study is limited to manufacturing firms. Besides, it reinforces the need for investigating the effectiveness of the proposed approach on service sectors.

The study provides a methodology with a real application, to manage experts’ knowledge for developing an effective lean improvement road map. The methodology could be adopted by any manufacturing firm.

The study supports decision makers of a firm to select the improvement initiatives by an original structural approach, which integrates BSC, TOC, FTA and fuzzy-DEMATEL. Besides, the interrelationships among the selected lean initiatives are considered, and results show the importance of analysing these interrelationships during the construction of the lean improvement plan. Moreover, its effectiveness and applicability are validated via a practical case study.