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The purpose of this paper is to examine the quality of the turned surface. The quality of the surface produced depends on the nature of the chips, which are produced while turning metal matrix composites. This quality is a function of the machining parameters, tool material, tool configuration and elements of the composites.

In this study, the turning of AA7075/15 wt.% SiC (particle size 20–40 µm) composites is investigated. Thirty experiments were conducted, and the chip-formation mechanism in turning AA7075/SiCp composites at various combinations of cutting speeds, feed and depth of cuts was studied.

It is observed from the response surface methodology-based experimentation that in turning of coarser reinforcement (particle size 20–40 µm) composites, total gross fracture occurs. This causes small slices of chips and a higher shear plane angle. The nature of chips produced at various combinations of cutting speeds, feed and depth of cuts is different. The chips generated were segmented, spiral in cylindrical form, connected C type, chips with saw tooth, curled chips, washer C type chips, half-curved segmented chips and small-radii segmented chips.

The novelty of this research is that, so far, very little work has been published on the detailed analysis of chips produced during turning of AA7075/15 wt.% SiC (particle size 20–40 µm) composites.

This study aims to thoroughly examine the milling process applied to fused filament fabrication (FFF) parts. The primary objective is to identify the key variables in creating smooth surfaces on FFF specimens and establish trends about specific parameters.

In this study, PLA and ABS samples fabricated by FFF are subjected to side milling in several experiments. Achievable surface quality is studied in relation to material properties, milling parameters, tooling and macrostructure. The surface finish is quantified using profile measurements of the processed surfaces. The study classifies the created chips into categories that can be used as criteria for the anticipated quality. Spectral analysis is used to examine the various surface formation modes. Thermal monitoring is used to track chip formation and surface temperature changes during the milling process.

This study reveals that effective heat dissipation through proper chip formation is vital for maintaining high surface quality. Recommended methodology demands using a tool with a substantial flute volume, using high positive rake and clearance angles and optimizing the feed-per-tooth and cutting speed. Disregarding these guidelines may cause the surface temperature to surpass the material’s glass transition, resulting in inferior quality characterized by viscous folding. For FFF thermoplastics, optimal milling can bring the average surface roughness down to the micron level.

This research contributes to the field by providing valuable guidance for achieving superior results in milling FFF parts. This study includes a concise summary of the theoretically relevant insights, presents verification of the key factors by qualitative analysis and offers optimal milling parameters for 3D-printed thermoplastics based on systematic experiments.

This work aims to describe the face milling analysis on Inconel X-750 superalloy using coated carbides. The formed chips and tool wear were further analyzed at different cutting parameters. The various impact of cutting parameters on chip morphology was also analyzed. Superalloys, often referred to as heat-resistant alloys, have exceptional tensile, ductile and creep strength at high operating temperatures and good fatigue strength, and often better corrosion and oxidation resistance at extreme heat. Because of these qualities, these alloys account for more than half of the weight of sophisticated aviation, biomedical and thermal power plants today. Inconel X-750 is a high-temperature nickel-based superalloy that is hard to machine because of its extensive properties. At last, the discussion regarding the tool wear mechanism was analyzed and discussed in this article.

The machining parameters for the study are cutting speed, feed rate and depth of cut. One factor at a time approach was implemented to investigate the effect of cutting parameters on the cutting forces, surface roughness and material removal rate. The scatter plot was plotted between cutting parameters and target functions (cutting forces, surface roughness and material removal rate). The six levels of cutting speed, feed rate and depth of cut were taken as cutting parameters.

The cutting forces are primarily affected by the cutting parameters, tool geometry, work material etc. The maximum forces Fx were encountered at 10 mm/min cutting speed, 0.15 mm/rev feed rate and 0.4 mm depth of cut, further maximum forces Fy were attained at 10 mm/min cutting speed, 0.25 mm/rev feed rate and 0.4 mm depth of cut and maximum forces Fz were attained at 50 mm/min cutting speed, 0.05 mm/rev feed rate and 0.4 mm depth of cut. The maximum surface roughness value was observed at 40 mm/min cutting speed, 0.15 mm/rev feed rate and 0.5 mm depth of cut.

The effect of machining parameters on cutting forces, surface roughness, chip morphology and tool wear for milling of Inconel X-750 high-temperature superalloy is being less researched in the present literature. Therefore, this research paper will give a direction for researchers for further studies to be carried out in the domain of high-temperature superalloys. Furthermore, the different tool wear mechanisms at separate experimental trials have been explored to evaluate and validate the process performance by conducting scanning electron microscopy analysis. Chip morphology has also been evaluated and analyzed under the variation of selected process inputs at different levels.

Because many cutting fluids contain hazardous chemical constituents, industries and researchers are looking for alternative methods to reduce the consumption of cutting fluids in machining operations due to growing awareness of ecological and health issues, government strict environmental regulations and economic pressures. Therefore, the purpose of this study is to raise awareness of the minimum quantity lubrication (MQL) technique as a potential substitute for environmental restricted wet (flooded) machining situations.

The methodology adopted for conducting a review in this study includes four sections: establishment of MQL technique and review of MQL machining performance comparison with dry and wet (flooded) environments; analysis of the past literature to examine MQL turning performance under mono nanofluids (M-NF); MQL turning performance evaluation under hybrid nanofluids (H-NF); and MQL milling, drilling and grinding performance assessment under M-NF and H-NF.

From the extensive review, it has been found that MQL results in lower cutting zone temperature, reduction in cutting forces, enhanced tool life and better machined surface quality compared to dry and wet cutting conditions. Also, MQL under H-NF discloses notably improved tribo-performance due to the synergistic effect caused by the physical encapsulation of spherical nanoparticles between the nanosheets of lamellar structured nanoparticles when compared with M-NF. The findings of this study recommend that MQL with nanofluids can replace dry and flood lubrication conditions for superior machining performance.

Machining under the MQL regime provides a dry, clean, healthy and pollution-free working area, thereby resulting the machining of materials green and environmentally friendly.

This paper describes the suitability of MQL for different machining operations using M-NF and H-NF.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2023-0131/

This study aims to establish a thermally coupled two-dimensional orthogonal cutting model to further improve the modeling process for systematic evaluation of material damage, stiffness degradation, equivalent plastic strain and other material properties, along with cutting temperature distribution and cutting forces. This enhances modeling efficiency and accuracy.

A two-dimensional orthogonal cutting thermo-mechanical coupled finite element model is established in this study. The tanh material constitutive model is used to simulate the mechanical properties of the material. Velocity-dependent friction model between the workpiece and the tool is considered. Material characteristics such as material damage, stiffness degradation, equivalent plastic strain and temperature field during cutting are evaluated through computation. Contact pressure and shear stress on the tool surface are extracted for friction analysis.

Speed-dependent friction models predict cutting force errors as low as 8.6%. The prediction errors of various friction models increase with increasing cutting forces and depths of cut, and simulation results tend to be higher than experimental data.

The current research results provide insights into understanding and controlling tool-chip friction in metal cutting, offering practical recommendations for friction modeling and machining simulation work.

The originality of this research is guaranteed, as it has not been previously published in any journal or publication.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0162/

In industrial applications, formaldehyde-based wood adhesives have been used extensively because of their low costs and high reactivity. However, their real-world applications are hindered by some main bottlenecks, especially the formaldehyde emission and usage of nonrenewable raw materials. The purpose of this study is the development of sustainable and formaldehyde-free wood adhesive formulation.

In this study, starch and tannin-based wood adhesive were synthesized. Chemical structures and thermal properties of the prepared bio-based resin formulations were elucidated by using Fourier transform infrared and differential scanning calorimetry analysis, respectively. Laboratory scale particleboard production was carried out to determine the performance of the developed resin formulations. Obtained results were evaluated in dry medium (P2) according to European norms EN 312 (2010). Furthermore, the board formaldehyde content was determined by using the perforator method according to the European Norm EN 12460-5.

The results show that the improved starch and tannin-based wood adhesives were successful in their adhesive capacity, and the formaldehyde content of the final product was obtained as low as 0.75 mg/100 g. This paper highlights that the presented adhesive formulations could be a potential eco-friendly and cost-effective alternative to the formaldehyde-based wood adhesives for interior particleboard production.

Starch-based resins in the liquid form needed to be continuously mixed throughout their shelf life to prevent the starch from settling because it was not possible to dissolve the precipitated starch again after a while. For this reason, starch was given to the chips in powder form while preparing the particleboard.

In conclusion, this study shows that the developed bio-based resin formulations have a high potential to be used for producing interior-grade particleboards instead of commercial formaldehyde-based wood adhesives because the obtained results generally satisfied the interior grade particleboard requirements according to European norms EN 312, P2 class (2010). In addition, it was determined that the produced boards had significantly low formaldehyde content. The low formaldehyde content of the final boards was not because of the resin but because of the natural structure of the wood raw material, press parameters and environmental factors.

The developed bio-based resin system made it possible to obtain boards with significantly low formaldehyde content compared to commercial resins.

The developed bio-based resin formulation made it possible to produce laboratory-scale board prototypes at lower press factors and board densities compared to their counterparts.

This paper aims to reduce waste management and generate wealth by investigating the novelty of combining chicken feather fiber and bamboo particles to produce hybrid biocomposites. This is part of responsible production and sustainability techniques for sustainable development goals. This study aims to broaden animal and plant fiber utilization in the sustainable production of epoxy resins for engineering applications.

This research used two reinforcing materials [chicken feather fiber (CFF) and bamboo particles (BP)] to reinforce epoxy resin. The BPs were kept constant at 6 Wt.%, while the CFF was varied within 3–15 Wt.% in the composites to make CFF-BP polymer-reinforced composite (CFF-BP PRC). The mechanical experiment showed a 21% reduction in densities, making the CFF-BP PRC an excellent choice for lightweight applications.

It was discovered that fabricated composites with 10 mm CFF length had improved properties compared with the 15 mm CFF length and pristine samples, which confirmed that short fibers are better at enhancing randomly dispersed fibers in the epoxy matrix. However, the ballistic properties of both samples matched. There is a 40% increase in tensile strength and a 54% increase in flexural strength of the CFF-BP PRC compared to the pristine sample.

According to the literature review, to the best of the authors’ knowledge, this is a novel study of chicken fiber and bamboo particles in reinforcing epoxy composite.

The purpose of the current study is development of effective and fast algorithm for optimization the arrangement of temporary fasteners during aircraft assembly.

Combinatorial nature, uncertain input data, sensitivity to mechanical properties and geometric tolerances are the specific features of the fastening optimization problem. These characteristics make the problem-solving by standard methods very resource-intensive because the calculation of the objective function requires multiple solution of contact problems. The work provides an extended description of the geodesic algorithm (GA) which is a novel non-iterative optimization approach avoiding multiple objective function calculations.

The GA makes it possible to optimize the arrangement of temporary fasteners during the different stages of the assembly process. The objective functions for the optimization are number of installed fasteners and quality of contact between joined parts. The mentioned properties of the GA also make it possible to introduce an automatic procedure for optimizing fastener arrangement into everyday practice of aircraft manufacturing.

The algorithm has been applied to optimization of the assembly process in Airbus company.

Performance of the GA is orders of magnitude greater than standard optimization algorithms while maintaining the quality of results. The use of the assembly process specifics is the main limitation of the GA, because it cannot be automatically applied to optimization problems in other areas. High speed of work and quality of the results make it possible to use it for real optimization problems on assembly line in the production of commercial airliners.

The purpose of this study is to develop a novel general mathematical model to find the optimal product mix of commercial graphite products, which has a complex production process with alternative sub-processes in the graphite mining production process.

The network optimization was adopted to model the complex graphite mining production process through the optimal allocation of raw graphite, byproducts, and saleable products with comparable sub-processes, which has different processing capacities and costs. The model was tested on a selected graphite manufacturing company, and the optimal graphite product mix was determined through the selection of the optimal production process. In addition, sensitivity and scenario analyses were carried out to accommodate uncertainties and to facilitate further managerial decisions.

The selected graphite mining company mines approximately 400 metric tons of raw graphite per month to produce ten types of graphite products. According to the optimum solution obtained, the company should produce only six graphite products to maximize its total profit. In addition, the study demonstrated how to reveal optimum managerial decisions based on optimum solutions.

This study has made a significant contribution to the graphite manufacturing industry by modeling the complex graphite mining production process with a network optimization technique that has yet to be addressed at this level of detail. The sensitivity and scenario analyses support for further managerial decisions.

This paper aims to study the relationship between the ball grid array (BGA) flip-chip underfilling process parameter and its void formation region.

A set of top-down scanning acoustic microscope images of BGA underfill is collected and void labelled. The labelled images are trained with a convolutional neural network model, and the performance is evaluated. The model is tested with new images, and the void area with its region is analysed with its dispensing parameter.

All findings were well-validated with reference to the past experimental results regarding dispensing parameters and their quantitative regional formation. As the BGA is non-uniform, 85% of the test samples have void(s) formed in the emptier region. Furthermore, the highest rating factor, valve dispensing pressure with a Gini index of 0.219 and U-type dispensing pattern set of parameters generally form a lower void percentage within the underfilling, although its consistency is difficult to maintain.

This study enabled manufacturers to forecast the void regional formation from its filling parameters and array pattern. The filling pressure, dispensing pattern and BGA relations could provide qualitative insights to understand the void formation region in a flip-chip, enabling the prompt to formulate countermeasures to optimise voiding in a specific area in the underfill.

The void regional formation in a flip-chip underfilling process can be explained quantitatively with indicative parameters such as valve pressure, dispensing pattern and BGA arrangement.