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This paper aims to investigate how the build orientation simultaneously affects the tensile properties, geometrical measurements and surface roughness in material extrusion (MEX) produced parts.

An extensive experimental campaign was designed and carried out to elucidate the relationship between the rotation angles (input), defining the part orientation within the build volume, and the (output) variables measured by using 3D models reconstruction, roughness tester and tensile testing machine. Response surface methodology is used to capture the trend of each output relative to the input, while principal component analysis is used to identify relationships among outputs, providing a holistic understanding of how build orientation simultaneously influences mechanical properties, geometrical measurements and surface characteristics.

The study reveals that build orientation significantly affects nearly all output variables, with a pronounced dependency on the out-of-plane rotation angle. A key finding is the inverse correlation between mechanical strength and both geometrical measurements and surface roughness. This indicates that optimizing build orientation can enhance mechanical strength while minimizing geometrical defects.

This research, a newer addition to the existing literature, contributes to the field of additive manufacturing (AM) by offering an innovative analysis of the interaction between mechanical properties, geometric precision and surface roughness in relation to build orientation. It enhances the understanding of MEX processes and provides valuable insights into optimizing build orientation, thereby improving the competitiveness of AM over traditional production methods.

This paper aims to use hybrid manufacturing (HM) to overcome several drawbacks of material extrusion three-dimensional (3D) printers, such as low dimension ranging from 0.2 to 0.5 µm, resulting in a noticeable staircase effect and elevated surface roughness.

Subtractive manufacturing (SM) through computer numerical control milling is renowned for its precision and superior surface finish. This study integrates additive manufacturing (AM) and SM into a single material extrusion 3D printer platform, creating a HM system. Two sets of specimens, one exclusively printed and the other subjected to both printing and milling, were assessed for dimension accuracy and surface roughness.

The outcomes were promising, with postmilling accuracy reaching 99.94%. Significant reductions in surface roughness were observed at 90° (93.4% decrease from 15.598 to 1.030 µm), 45° (89% decrease from 26.727 to 2.946 µm) and the face plane (71% decrease from 12.176 to 3.535 µm).

The 3D printer was custom-built based on material extrusion and modified with an additional milling tool on the same gantry. An economic evaluation based on cost-manufacturing demonstrated that constructing this dual-function 3D printer costs less than US$560 in materials, offering valuable insights for researchers looking to replicate a similar machine.

The modified general 3D printer platform offered an easy way to postprocessing without removing the workpiece from the bed. This mechanism can reduce the downtime of changing the machine. The proven increased dimension accuracy and reduced surface roughness value increase the value of 3D-printed specimens.

The use of additive manufacturing in many branches of industry is increasing significantly because of its many advantages, such as being able to produce complex parts that cannot be produced by classical methods, using fewer materials, easing the supply chain with on-site production, being able to produce with all kinds of materials and producing lighter parts. The binder jetting technique, one of the additive manufacturing methods researched within the scope of this work, is predicted to be the additive manufacturing method that will grow the most in the next decade, according to many economic reports. Although additive manufacturing methods have many advantages, they can be slower than classical manufacturing methods regarding production speed. For this reason, this study aims to increase the manufacturing speed in the binder jetting method.

Adaptive slicing and variable binder amount algorithm (VBAA) were used to increase manufacturing speed in binder jetting. Taguchi method was used to optimize the layer thickness and saturation ratio in VBAA. According to the Taguchi experimental design, 27 samples were produced in nine different conditions, three replicates each. The width of the samples in their raw form was measured. Afterward, the samples were sintered at 1,500 °C for 2 h. After sintering, surface roughness and density tests were performed. Therefore, the methods used have been proven to be successful. In addition, measurement possibilities with image processing were investigated to make surface roughness measurements more accessible and more economical.

As a result of the tests, the optimum printing condition was decided to be 180–250 µm for layer thickness and 50% for saturation. A separate test sample was then designed to implement adaptive slicing. This test sample was produced in three pieces: adaptive (180–250 µm), thin layer (180 µm) and thick layer (250 µm) with the determined parameters. The roughness values of the adaptive sliced sample and the thin layer sample were similar and better than the thick layer sample. A similar result was obtained using 12.31% fewer layers in the adaptive sample than in the thin layer sample.

The use of adaptive slicing in binder jetting has become more efficient. In this way, it will increase the use of adaptive slicing in binder jetting. In addition, a cheap and straightforward image processing method has been developed to calculate the surface roughness of the parts.

This study aims to examine the impact of specific printing factors, such as layer height, line width and build orientation, on the overall quality of fused filament fabrication (FFF) 3D printed structures. The project also intends to use response surface methodology (RSM) to maximize ultimate tensile strength (UTS) while lowering surface roughness and printing time.

This study used an FFF printer to fabricate samples of polylactic acid (PLA), which were then subjected to assessments of tensile strength and surface roughness. A tensile test was conducted under standardized conditions according to the ASTM D638 standard test method using the AG-50 kN Shimadzu Autograph. The Mitutoyo Surftest SJ-210, which utilizes a needle-tipped inductive method, was used to determine surface roughness. RSM was used for optimization.

This work provides useful insights into how the printing parameters affect FFF 3D printed structures, which may be used to optimize the printing process and improve PLA-based 3D printed products' qualities. The determined optimal values for building orientation, layer height and line width were 0°, 0.1 mm and 0.6 mm, respectively. The total desirability value of 0.80 implies desirable outcomes, and good agreement between experimental and projected response values supports the suggested models.

Previous RSM studies for 3D printing parameter optimization focused on mechanical properties or surface aspects, however, few examined multiple responses and their interactions. This study emphasizes the relevance of FFF parameters like line width, which are often overlooked but can dramatically impact printing quality. Mechanical properties, surface quality and printing time are integrated to comprehend optimization holistically.

Surface roughness and delamination during the milling of carbon fiber reinforced polymer (CFRP) composite parts in aviation can lead to component rejection. This article aims to optimize cutting conditions to reduce these failures while ensuring compliance with aviation standards. By improving machinability, the goal is to minimize part rejection rates and scrap, optimizing costs and increasing safety.

Full factorial experimental design and response surface methodology (RSM) were used to establish relationships between the cutting parameters and the cutting force, delamination and surface roughness. To validate the model and identify significant parameters, analysis of variance (ANOVA) was performed. The cutting parameters were optimized to reduce cutting force and improve surface quality using ANOVA and RSM.

The lowest response values can be achieved with a cutting speed of 285.35 m/min and a feed of 358.57 mm/min using the Aluminum Chromium Nitride (AlCrN)-coated tool. Accordingly, the optimum cutting force was obtained as 190.97 N, delamination depth as 1.562 mm and surface roughness as 1.431 µm. It has been seen that the obtained surface roughness and delamination values are consistent with aviation literature studies, sectoral data and standards.

This study uniquely examines cutting force, surface roughness and delamination using Titanium Aluminum Nitride (TiAlN)- and AlCrN-coated tools instead of traditional Poly Cyristaline Diamond (PCD) tools. It employs a two-stage experimental framework, starting with a full factorial design followed by RSM. The initial data have been used as inputs for optimization in the second stage to achieve more accurate results.

The aim of the study is to optimize the cutting parameters (cutting tool diameter, cutting speed and feed) to minimize energy consumption and surface roughness in the slot milling process of AISI 316 stainless steel on CNC milling machine.

Growing environmental concerns and cost reduction efforts around the world have made energy efficiency in manufacturing processes a priority goal. Improving energy efficiency in the machining sector is one of the biggest challenges in this area, and slot milling is a critical manufacturing process that directly affects energy consumption. Cutting power, cutting force and surface roughness values were measured during the experimental process. In addition, energy performance of the process was evaluated by calculating specific energy consumption (SEC) and specific cutting energy consumption (SCEC). Experimental data were modeled using machine learning methods of regression analysis and artificial neural networks (ANN).

As a result, the lowest SEC and SCEC values, that is the highest energy efficiency, were obtained at 12 mm tool diameter, 75 m/min cutting speed and 0.25 mm/tooth feed. In addition, the optimum cutting parameters for different machining scenarios (roughing and finishing) were determined taking into account the purposes of the machining process (max. or min of energy efficiency, machining time, surface quality, etc.). The optimum cutting parameters for general purpose slot milling and acceptable machining purposes were found to be 12 mm tool diameter, 150 m/min cutting speed and 0.15 mm/tooth feed.

This study emphasizes the critical importance of energy efficiency and the correct selection of machining parameters for sustainable manufacturing practices.

• Slot milling cutting performance of AISI 316

• Measurement of cutting power, cutting force and surface roughness

• Prediction with Regression and ANN methods

Slot milling cutting performance of AISI 316

Measurement of cutting power, cutting force and surface roughness

Prediction with Regression and ANN methods

This study aims to investigate the impact of varying the number of minimum quantity lubrication (MQL) nozzles, wind pressure, spindle speed and type of lubrication on surface roughness, fatigue life and tool wear in the drilling of aluminum alloy 6061-T6.

The effect of using different lubricants such as palm oil, graphene/water nanofluid and SiO₂/water in the MQL method was compared with flood and dry methods. The lubricant flow and feed rate were kept constant throughout the drilling, while the number of nozzles, wind pressure and spindle speed varied. After preparing the parts, surface roughness, fatigue life and tool wear were measured, and the results were analyzed by ANOVA.

The results showed that using MQL with four nozzles and graphene/water nanofluid reduced surface roughness by 60%, followed by SiO₂ nanofluid at 56%, and then by palm oil at 50%. Increasing the spindle speed in MQL mode with four nozzles using graphene nanofluid decreased surface roughness by 52% and improved fatigue life by 34% compared to the dry mode. SEM results showed that tool wear and deformation rates significantly decreased. Increasing the number of nozzles caused the fluid particles to penetrate the cutting area, resulting in improved tool cooling with lubrication in all directions.

Numerous attempts have been made worldwide to eliminate industrial lubricants due to environmental pollution. In this research, using nanofluid with wind pressure in MQL reduces environmental impacts and production costs while improving the quality of the final workpiece more than flood and dry methods.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2024-0021/

This study aims to enhance pedestrian safety by investigating the slip resistance of facility floors with ceramic tile surfaces and identifying critical surface roughness parameters that influence slip resistance.

Dynamic friction tests and comprehensive surface roughness analyses were conducted on ceramic tiles. Statistical analysis identified optimal roughness ranges for key parameters (R_a, R_p, R_t, R_z and R_v) to ensure the dynamic friction coefficient exceeds 0.5 to meet safety requirements. This study assessed different textures under dry, damp and foamy conditions.

The findings reveal that ceramic tile surfaces with higher peak heights and deeper valleys provide superior traction, particularly in damp and foamy conditions. The results demonstrate that specific surface textures can effectively mitigate slip and fall hazards by enhancing grip and increasing surface interaction points. This study establishes optimal roughness ranges for the critical parameters, providing a robust framework for improving slip resistance.

This study offers practical guidelines for designing safer ceramic tiles, emphasising the importance of tailored surface roughness to improve traction. It highlights the importance of considering environmental factors in slip resistance assessments, offering valuable insights for manufacturers, designers and policymakers. By focusing on specific surface textures, this study advances the development of safer built environments in public facilities. Future research directions should explore a broader range of tile finishes, footwear types and contaminant scenarios to refine the understanding of traction performance further.

The additive manufacturing process, such as fused filament fabrication based on material extrusion, fabricates the samples layer-by-layer. The various parameters in the process significantly affect the dimensions, structure and mechanical properties of the fabricated parts. The purpose of this paper is to investigate the surface and mechanical properties that can affect the contact characteristics with other materials during tribological tests.

The investigation of 3D-printed Polyetheretherketone (PEEK) includes the measurement of dimensions, microhardness, surface roughness, surface energy and tensile strength to define material characteristics. The crystallinity is measured using an X-ray diffractometer to understand the hardness behaviour.

The printing parameters affect its surface roughness, hardness and crystallinity. This change in parameters such as layer thickness and infill density impacts mechanical properties such as hardness and surface roughness, which will influence the contact mechanism with the counter body during any tribological test. The change in a single parameter during the sample fabrication and the change in the surface and mechanical properties are observed.

The material cost plays an important role in conducting numerous destructive tests, which is a major limitation to conducting parameter optimisation by varying more parameters. The study is limited to the as-fabricated samples rather than finished samples and without any heat treatment. Achieving optimal parameters is integral to the success of additive manufacturing, ensuring the production of components with consistent performance.

The study aims at the application of 3D-printed PEEK for bush or journal bearings that can be directly used in practice. The mechanical properties discussed in this paper can fill the gap between theory and practice.

The research provides all fundamental properties, including the printing parameters and their effect on the dimensions and surface structure, which are required to understand the material and its use. The results are consistent as at least four samples were tested for tribological behaviour. The conclusion is updated as per suggestions.

The study outlines the relationship between the change in layer thickness and infill density with changes in surface energy, surface roughness, hardness and tensile strength. The deformation and adhesion during the friction test depend on these properties.

The aim of this paper is to study the effect of laser shock peening (LSP) on mechanical behaviour of the laser-directed energy deposition (LDED)-based printed 15-5 PH stainless steel with U and V notches. The study specifically concentrates on the evaluation of effect of scan strategy, machining and LSP processing on microstructural, texture evolution and fatigue behaviour of LDED-printed 15-5 PH steel.

For LSP treatment, 15-5 PH steel was printed using LDED process with bidirectional scanning strategy (XX [θ = 0°) and XY [θ = 90°]) at optimised laser power of 600 W with a scanning speed of 300 mm/min and a powder feed rate of 3 g/min. Furthermore, LSP treatment was conducted on the V- and U-notched fatigue specimens extracted from LDED-built samples at laser energy of 3.5 J with a pulse width of 10 ns using laser spot diameter of 3 mm. Post to the LSP treatment, the surface roughness, fatigue life assessment and microstructural evolution analysis is performed. For this, different advanced characterisation techniques are used, such as scanning electron microscopy attached with electron backscatter diffraction for microstructure and texture, X-ray diffraction for residual stress (RS) and structure information, Vicker’s hardness tester for microhardness and universal testing machine for low-cycle fatigue.

It is observed that both scanning strategies during the LDED printing of 15-5 PH steel and laser peening have played significant role in fatigue life. Specimens with the XY printing strategy shows higher fatigue life as compared to XX with both U- and V-notched conditions. Furthermore, machining and LSP treatment led to a significant improvement of fatigue life for both scanning strategies with U and V notches. The extent of increase in fatigue life for both XX and XY scanning strategy with V notch is found to be higher than U notch after LSP treatment, though without LSP samples with U notch have a higher fatigue life. As fabricated sample is found to have the lowest fatigue life as compared to machines and laser peened with both scan strategies.

This study presents an innovative method to improve the fatigue life of 15-5 PH stainless steel by changing the microstructure, texture and RS with the adoption of a suitable scanning strategy, machining and LSP treatment as post-processing. The combination of preferred microstructure and compressive RS in LDED-printed 15-5 PH stainless steel achieved with a synergy between microstructure and RS, which is responsible to improve the fatigue life. This can be adopted for the futuristic application of LDED-printed 15-5 PH stainless steel for different applications in aerospace and other industries.