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This study aims to comparatively analyze the cut parts obtained as a result of cutting the Ni-based Inconel 625 alloy, which is widely used in the aerospace industry, with the wire electro-discharge machining (WEDM) and abrasive water jet machining (AWJM) methods in terms of macro- and microanalyses.

In this study, calipers, Mitutoyo SJ-210, Nikon SMZ 745 T, scanning electron microscope and energy dispersive X-ray were used to determine kerf, surface roughness and macro- and microanalyses.

Considering the applications in the turbine industry, it has been determined that the WEDM method is suitable to meet the standards for the machinability of Inconel 625 alloy. In contrast, the AWJM method does not meet the standards. Namely, while the kerf angle was formed because the hole entrance diameters of the holes obtained with AWJM were larger than the hole exit diameters, the equalization of the hole entry and exit dimensions, thanks to the perpendicularity and tension sensitivity of the wire electrode used in the holes drilled with WEDM ensured that the kerf angle was not formed.

It is known that the surface roughness of the parts used in the turbine industry is accepted at Ra = 0.8 µm. In this study, the average roughness value obtained from the successful drilling of Inconel 625 alloy with the WEDM method was 0.799 µm, and the kerf angle was obtained as zero. In the cuts made with the AWJM method, thermal effects such as debris, microcracks and melted materials were not observed; an average surface roughness of 2.293 µm and a kerf of 0.976° were obtained.

The purpose of this study is to investigate the impact of titanium oxide (TiO₂) filler on the abrasive wear properties of bamboo fiber reinforced epoxy composites (BFRCs) using a Taguchi approach. The study aims to enhance the abrasive wear resistance of these composites by introducing TiO₂ filler as a potential reinforcement, thus contributing to the development of sustainable and environmentally friendly materials.

This study focuses on the fabrication of epoxy/bamboo composites infused with TiO₂ particles within the Wt.% range of 0–8 Wt.% using hand layup techniques. The resulting composites were subjected to wear testing according to ASTM G99-05 standards. Statistical analysis of the wear results was carried out using the Taguchi design of experiments (DOE). Additionally, an analysis of variance (ANOVA) was used to determine the influential control factors impacting the specific wear rate (SWR) and coefficient of friction (COF).

The study illuminates how integrating TiO₂ filler enhances abrasive wear in epoxy/bamboo composites. Statistical analysis of SWR highlights abrasive grit size (grit) as the most influential factor, followed by normal load, Wt.% of TiO₂ and sliding distance. Analysis of the COF identifies normal load as the primary influential factor, followed by grit, Wt.% of TiO₂ and sliding distance. The Taguchi predictive model closely aligns with experimental results, validating its reliability. The morphological study revealed significant differences between the unfilled and TiO₂-filled composites. The inclusion of TiO₂ improved wear resistance, as evidenced by reduced surface damage and wear debris.

This research paper aims to integrate TiO₂ filler and bamboo fibers to create an innovative hybrid composite material. TiO₂ micro and nanoparticles show promise as filler materials, contributing to improved tribological properties of epoxy composites. The utilization of Taguchi’s DOE and ANOVA for statistical analysis provides valuable guidance for academic researchers and practitioners in optimizing control variables, especially in the context of natural fiber reinforced composites.

The criteria importance through intercriteria correlation (CRITIC) and range of value (ROV) combined methods were used to determine a single index for all multiple responses.

This paper used cold metal transfer (CMT) and pulse metal-inert gas (MIG) welding processes to study the weld-on-bead geometry of AA2099-T86 alloy. This study used Taguchi's approach to find the optimal setting of the input welding parameters. The welding current, welding speed and contact-tip-to workpiece distance were the input welding parameters for finding the output responses, i.e. weld penetration, dilution and heat input. The L9 orthogonal array of Taguchi's approach was used to find out the optimal setting of the input parameters.

The optimal input welding parameters were determined with combined output responses. The predicted optimum welding input parameters were validated through confirmation tests. Analysis of variance showed that welding speed is the most influential factor in determining the weld bead geometry of the CMT and pulse MIG welding techniques.

The heat input and weld bead geometry are compared in both welding processes. The CMT welding samples show superior defect-free weld beads than pulse MIG welding due to lesser heat input and lesser dilution.

This study aims to investigate the optimal process parameters of the wire-cut electrical discharge machining (WCEDM) for the machining of the GZR-AA7475 hybrid metal matrix composite (HMMC). HMMCs are prepared with 2 Wt.% graphite and 4 Wt.% zirconium dioxide reinforced with aluminium alloy 7475 (GZR-AA7475) composite by using the stir casting method. The objective is to enhance the mechanical properties of the material while preserving its unique features. WCEDM with a 0.18 mm molybdenum wire electrode is used for machining the composite.

To conduct experimental studies, a Taguchi L27 orthogonal array was adopted. Input variables such as peak current (I_p), pulse-on-time (T_ON) and flushing pressure (P_F) were used. The effect of process parameters on the output responses, such as material removal rate (MRR), surface roughness rate (SRR) and wire wear ratio (WWR), were investigated. The grey relational analysis (GRA) is used to obtain the optimal combination of the process parameters. Analysis of variance (ANOVA) was also used to identify the significant process parameters affecting the output responses.

Results from the current study concluded that the optimal condition for grey relational grade is obtained at T_ON = 105 µs, I_p = 100 A and P_F = 90 kg/cm². Peak current is the most prominent parameter influencing the MRR, whereas SRR and WRR are highly influenced by flushing pressure.

Identifying the optimal process parameters in WCEDM for machining of GZR-AA7475 HMMC. ANOVA and GRA are used to obtain the optimal combination of the process parameters.

This study explores how titanium oxide (TiO₂) filler influences the specific wear rate (SWR) in flax fiber-reinforced epoxy composites (FFRCs) through a Taguchi approach. It aims to boost abrasive wear resistance by incorporating TiO₂ filler, promoting sustainable and eco-friendly materials.

This study fabricates epoxy/flax composites with TiO₂ particles (0–8 wt%) using hand layup. Composites were tested for wear following American Society for Testing and Materials (ASTM) G99-05. Statistical analysis used Taguchi design of experiments (DOE), with ANOVA identifying key factors affecting SWR in abrasive sliding conditions.

The study illuminates how integrating TiO2 filler particles into epoxy/flax composites enhances abrasive wear properties. Statistical analysis of SWR highlights abrasive grit size (grit) as the most influential factor, followed by normal load, wt% of TiO₂ and sliding distance. Grit size has the highest effect at 43.78%, and wt% TiO₂ filler contributes 15.61% to SWR according to ANOVA. Notably, the Taguchi predictive model closely aligns with experimental results, validating its reliability.

This paper integrates TiO₂ filler and flax fibers to form a novel hybrid composite with enhanced tribological properties in epoxy composites. The use of Taguchi DOE and ANOVA offers valuable insights for optimizing control variables, particularly in natural fiber-reinforced composites (NFRCs).

The purpose of this study is to propose a new mathematical model that integrates strategic decision-making with tactical-operational decision-making in order to optimize production and scheduling decisions.

This study presents a multi-objective optimization framework to make production planning, scheduling and maintenance decisions. An epsilon-constraint method is used to solve small instances of the model, while new hybrid optimization algorithms, including multi-objective particle swarm optimization (MOPSO), non-dominated sorting genetic algorithm, multi-objective harmony search and improved multi-objective harmony search (IMOHS) are developed to address the high complexity of large-scale problems.

The computational results demonstrate that the metaheuristic algorithms are effective in obtaining economic solutions within a reasonable computational time. In particular, the results show that the IMOHS algorithm is able to provide optimal Pareto solutions for the proposed model compared to the other three algorithms.

This study presents a new mathematical model that simultaneously determines green production planning and scheduling decisions by minimizing the sum of the total cost, makespan, lateness and energy consumption criteria. Integrating production and scheduling of a shop floor is critical for achieving optimal operational performance in production planning. To the best of the authors' knowledge, the integration of production planning and maintenance has not been adequately addressed.

The purpose of this paper is to examine the mechanical characteristics and optimization of wear parameters of hybrid (TiO₂ + Y₂O₃) nanoparticles with Al matrix using squeeze casting technique.

The hybrid aluminium matrix nanocomposites (HAMNCs) were fabricated with varying concentrations of titanium oxide (TiO₂) and yttrium oxide (Y₂O₃), from 2.5 to 10 Wt.% in 2.5 Wt.% increments. Dry sliding wear test variables were optimized using the Taguchi method.

The introduction of hybrid nanoparticles in the aluminium (Al) matrix was evenly distributed in contrast to the base matrix. HAMNC6 (5 Wt.% TiO₂ + 5 Wt.% Y₂O₃) reported the maximum enhancement in mechanical properties (tensile strength, flexural strength, impact strength and density) and decrease in porosity% and elongation% among other HAMNCs. The results showed that the optimal combination of parameters to achieve the lowest wear rate was A3B3C1, or 15 N load, 1.5 m/s sliding velocity and 200 m sliding distance. The sliding distance showed the greatest effect on the dry sliding wear rate of HAMNC6 followed by applied load and sliding velocity. The fractured surfaces of the tensile sample showed traces of cracking as well as substantial craters with fine dimples and the wear worn surfaces were caused by abrasion, cracks and delamination of HAMNC6.

Squeeze-cast Al-reinforced hybrid (TiO₂+Y₂O₃) nanoparticles have been investigated for their impact on mechanical properties and optimization of wear parameters.

This paper aims to investigate the effect of physical vapor deposition (PVD)-coated stencil wall aperture on the life span of fine-pitch stencil printing.

The fine-pitch stencil used in this work is fabricated by electroform process and subsequently nano-coated using the PVD process. Stencil printing process was then performed to print the solder paste onto the printed circuit board (PCB) pad. The solder paste release was observed by solder paste inspection (SPI) and analyzed qualitatively and quantitatively. The printing cycle of up to 80,000 cycles was used to investigate the life span of stencil printing.

The finding shows that the performance of stencil printing in terms of solder printing quality is highly dependent on the surface roughness of the stencil aperture. PVD-coated stencil aperture can prolong the life span of stencil printing with an acceptable performance rate of about 60%.

Stencil printing is one of the important processes in surface mount technology to apply solder paste on the PCB. The stencil’s life span greatly depends on the type of solder paste, stencil printing cycles involved and stencil conditions such as the shape of the aperture, size and thickness of the stencil. This study will provide valuable insight into the relationship between the coated stencil wall aperture via PVD process on the life span of fine-pitch stencil printing.

In recent decades, the student population in dormitories has increased notably, primarily attributed to the growing number of international students. Dormitories serve as pivotal environments for student development. The coordination and compatibility among students can significantly influence their overall success. This study aims to introduce an innovative method for roommate selection and room allocation within dormitory settings.

In this study, initially, using multi-attribute decision-making methods including the Bayesian best-worst method and weighted aggregated sum product assessment, the incompatibility rate among pairs of students is calculated. Subsequently, using a linear mathematical model, roommates are selected and allocated to dormitory rooms pursuing the twin objectives of minimizing the total incompatibility rate and costs. Finally, the grasshopper optimization algorithm is applied to solve large-sized instances.

The results demonstrate the effectiveness of the proposed method in comparison to two common alternatives, i.e. random allocation and preference-based allocation. Moreover, the proposed method’s applicability extends beyond its current context, making it suitable for addressing various matching problems, including crew pairing and classmate pairing.

This novel method for roommate selection and room allocation enhances decision-making for optimal dormitory arrangements. Inspired by a real-world problem faced by the authors, this study strives to offer a robust solution to this problem.

This paper aims to focus on a medical goods distribution problem and pharmacological waste collection by plug-in hybrid vehicles with some real-world restrictions. In this research, considering alternative energy sources and simultaneous pickup and delivery led to a decrease in greenhouse gas emissions and distribution costs, respectively.

Here, this problem has been modeled as mixed-integer linear programming with the traveling and energy consumption costs objective function. The GAMS was used for model-solving in small-size instances. Because the problem in this research is an NP-hard problem and solving real-size problems in a reasonable time is impossible, in this study, the artificial bee colony algorithm is used.

Then, the algorithm results are compared with a simulated annealing algorithm that recently was proposed in the literature. Finally, the results obtained from the exact solution and metaheuristic algorithms are compared, analyzed and reported. The results showed that the artificial bee colony algorithm has a good performance.

In this paper, medical goods distribution with pharmacological waste collection is studied. The paper was focused on plug-in hybrid vehicles with simultaneous pickup and delivery. The problem was modeled with environmental criteria. The traveling and energy consumption costs are considered as an objective function.